pH 4.0
200
pH 5.7
pH 7.0
pH 8.0
0
I
/ mA
100
-100
B
-200
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KC lsat.
CHEMIA
2/2013
STUDIA
UNIVERSITATIS BABEŞ-BOLYAI
CHEMIA
2/2013
EDITORIAL BOARD
STUDIA UNIVERSITATIS BABEŞ-BOLYAI
CHEMIA
ONORARY EDITOR:
IONEL HAIDUC - Member of the Romanian Academy
EDITOR-IN-CHIEF:
LUMINIŢA SILAGHI-DUMITRESCU
EXECUTIVE EDITOR:
CASTELIA CRISTEA
EDITORIAL BOARD:
PAUL ŞERBAN AGACHI, Babeş-Bolyai University, Cluj-Napoca, Romania
LIVAIN BREAU, UQAM University of Quebec, Montreal, Canada
HANS JOACHIM BREUNIG, Institute of Inorganic and Physical Chemistry,
University of Bremen, Bremen, Germany
MIRCEA DIUDEA, Babes-Bolyai University, Cluj-Napoca, Romania
JEAN ESCUDIE, HFA, Paul Sabatier University, Toulouse, France
ION GROSU, Babeş-Bolyai University, Cluj-Napoca, Romania
EVAMARIE HEY-HAWKINS, University of Leipzig, Leipzig, Germany
FLORIN DAN IRIMIE, Babeş-Bolyai University, Cluj-Napoca, Romania
FERENC KILAR, University of Pecs, Pecs, Hungary
BRUCE KING, University of Georgia, Athens, Georgia, USA
ANTONIO LAGUNA, Department of Inorganic Chemistry, ICMA, University of
Zaragoza, Zaragoza, Spain
JURGEN LIEBSCHER, Humboldt University, Berlin, Germany
KIERAN MOLLOY, University of Bath, Bath, UK
IONEL CĂTĂLIN POPESCU, Babeş-Bolyai University, Cluj-Napoca, Romania
CRISTIAN SILVESTRU, Babeş-Bolyai University, Cluj-Napoca, Romania
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CUPRINS – CONTENT – SOMMAIRE – INHALT
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS, Synthesis of
Tripropionin from Crude Glycerol the By-Product of Biodiesel Production ......... 7
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA
STANCA, DAN RĂDULESCU, Removal of Anionic Dye Congo Red from
Synthetic Wastewater using Immobilised Fir Sawdust (Abies Alba)........... 23
ADINA GHIRIŞAN, SIMION DRĂGAN, Kinetic Study of Carrots Drying ............... 35
NINA DJAPIC, Thermodynamic Study of Hydrangea Aspera Chlorophyll Catabolites
by Reverse Phase Liquid Chromatography ................................................. 43
ALEXANDRA LǍPUŞAN, FLAVIU TǍBǍRAN, SORIN DANIEL DAN, ROMOLICA
MIHAIU, CORNEL CǍTOI, MARIAN MIHAIU, Characterization of Buffalo
Milk Fat Globules using the Confocal Laser Scanning Microscopy ............ 53
ISTVÁN MIHÁLY TAKÁCS, AUGUSTIN MOT, RADU SILAGHI-DUMITRESCU,
GRIGORE DAMIAN, Site Directed Spin Labeling of Hemerythrin and
Hemoglobin ................................................................................................. 61
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA, Maximal
Harary Index of Unicyclic Graphs with a Given Matching Number .................. 71
ANIKÓ PÉTER, TÍMEA DERGEZ, IBOLYA KISS, FERENC KILÁR, FAST GC-MS
Method for Quantification of Gamma-Butyrolactone in Biological Matrices...... 87
ALEXANDRA TOMA, DENISA HAPĂU, MARA NAGHI, LAURIAN VLASE,
CRISTINA MOGOŞAN, VALENTIN ZAHARIA, Heterocycles 34. Synthesis
and Anti-Inflammatory Activity of new Polyheterocyclic Schiff Bases and
Mannich Bases............................................................................................. 93
GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN
POPESCU, Electrochemical Behavior of the Hemin Modified Graphite
Electrode for H2O2 Detection...................................................................... 105
FARIBA TADAYON, MAHNOOSH HANASAEI, Determination of Cobalt and
Nickel after Modified-Cold-Induced Aggregation Microextraction based
on Ionic Liquid in Hair and Water Samples................................................ 115
MOHAMMAD REZA FARAHANI, KATALIN KOLLO, MIRANDA PETRONELLA
VLAD, Second-connectivity index of Capra-designed planar Benzenoid
series Can(C6)............................................................................................. 127
MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD, Computing
first and second Zagreb Index, first and second Zagreb Polynomial of
Capra-Designed Planar Benzenoid Series Can(C6) ......................................133
DANA – ADRIANA ILUŢIU – VARVARA, DAN RĂDULESCU, Assessment of Air
Pollution with Sulphur Dioxide from Electric Arc Furnaces ....................... 143
ELHAM HEIATIAN, FARHOUSH KIANI, SASAN SHARIFI, AZAR BAHADORI,
FARDAD KOOHYAR, Equilibrium and Thermodynamic Study of Complexes
of Thallium with Uracil at Different Temperatures and Constant Ionic
Strength ..................................................................................................... 151
LATHA PUSHPALATHA, Kinetics and Mechanism of Oxidation of Malic Acid by
N-Chloronicotinamide (NCN) in the Presence of a Micellar System.......... 161
NORBERT MUNTEAN, GABRIELLA SZABÓ, The Antioxidant Activity of Tea
Infusions Tested by Means of Briggs-Rauscher Oscillatory Reaction ....... 175
Studia Universitatis Babes-Bolyai Chemia has been selected for coverage
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with V. 53 (1) 2008, this publication is indexed and abstracted in the following:
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STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 7 – 22)
(RECOMMENDED CITATION)
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL
THE BY-PRODUCT OF BIODIESEL PRODUCTION
ZSANETT HERSECZKIa, GYULA MARTONa, ANDRAS DALLOSa
ABSTRACT. Glycerol is a by-product obtained during the production of biodiesel.
An increase in biodiesel production would decrease the market price of glycerol.
The objective of this study was to investigate glycerol purification, esterification
of glycerol by propionic acid and the field of application of the product. Crude
glycerol from a Hungarian biodiesel factory was partly refined, soaps, water,
methanol and pigments were removed and glycerol still containing inorganic
salts was used for certain esterification reactions. A cost effective process
for utilization of crude glycerol was created, which can be applied not only for
tripropionin production but preparation of other glycerol esters like glyceryl
triacetate, glyceryl tributyrate. Moreover, effect of tripropionin blending on engine
performance characteristics and environmental repercussions were studied.
Keywords: glycerol, biodiesel, tripropionin, fuel additives, oxygenate
INTRODUCTION
Biodiesel produced by the transesterification of vegetable oils or animal
fats with short-chain alcohols (typically methanol) is a promising alternative
fuel for diesel engines, because of the limited resources of fossil fuels and
environmental concerns [1].
Ideally, three molecules of fatty acid methyl esters (FAME) and one
molecule of glycerol are formed when starting from any molecule of a
triglyceride (TG) and three moles of methanol [2].
Crude glycerol (G-phase) as an unrefined residue of the biodiesel
synthesis shows usually a content of glycerol varying between 30 wt% and
60 wt%. The larger biodiesel plants tend to give the highest “purities”, often
around 75 wt% to 90 wt% [3]. The rest of the “crude glycerol” consists primarily
of remaining, unconverted triglycerides, unreacted methanol, some dissolved
biodiesel, fatty acids, alkali hydroxides, different semi-saponified triglycerides,
a
University of Pannonia, H-8200 Veszprem, POB 158, Hungary, herseczki@freemail.hu
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
alkali salts of fatty acids, water, pigments and some other remains of the
vegetables originated by the oil production.
Fact is that approximately 15-20% of the converted feedstock is released
as crude glycerol. The accumulation of crude glycerol not only hampers the
development of the biodiesel industry, but it also creates economic and
environmental problems [4].
It was projected that the world biodiesel market would reach 168 million
tons by 2016, which implied that approximately 25 million tons of crude
glycerol would be produced [5]. Too much surplus of crude glycerol from biodiesel
production will impact the refined glycerol market [6]. For example, in 2007,
the refined glycerol's price was rather low, approximately $0.66 per kg (compared
to $1.55 before the expansion of biodiesel production) in the United States.
Accordingly, the price of crude glycerol decreased from about $0.55 per kg
to $0.11 per kg [7].
Glycerol from biodiesel production is widely recognized as a waste
stream, the disposal of which has become a heavy load for the biodiesel plants.
The application of common base technologies like distillation, filtration,
extraction, incineration, but even biologically waste treatment of “crude glycerol”
is becoming hampered for numerous reasons. These processes are very
expensive and exhibit a low yield [8].
Therefore, to release the pressure from the flooded glycerol market
nowadays, the development of processes to convert glycerol to commodity
chemicals with larger markets than traditional ones capable of absorbing a
great part of the newly produced glycerol is becoming increasingly urgent.
Some of these strategies include selective reduction – hydrogenolysis to
propylene glycol, dehydroxylation to 1,3-propanediol-, halogenation to
obtain epichlorohydrin, dehydration to produce acrolein, acrylic acid or 3hydroxypropionaldehyde and selective oxidation [9]. Meanwhile developing
the technology of glycerol conversion to high value products will also add
value to the production of biodiesel [10]. Among different alternatives, the
esterification of glycerol with propionic acid to yield tripropionin as a valuable
transportation fuel additive is such an option.
The research line, described in the present work, is focusing on
purification of crude glycerol and the synthesis process for converting partly
purified glycerol in to tripropionin. Influences of raw materials (different
glycerol qualities), reaction conditions were investigated and optimized.
RESULTS AND DISCUSSION
Purification of crude glycerol
During our experiments we have made some general observations
for the purification process:
8
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
• The high viscosity of the crude glycerol is hampering the handling of
this phase by enhanced force on pumps and agitators. The increase of the
processing temperature can be a solution for this problem.
• The presence of methanol and other light components is of
advantage to reduce the viscosity.
• A dilution of crude glycerol by ~25% water was found to be optimal
for viscosity reduction.
Dilution by water and acid treatment
The effect of dilution of crude glycerol by water was investigated. The
glycerol phase was diluted by 20, 25, 30 and 50% water, thereafter heated up
to 80°C and the neutralization process with H3PO4 was started. The reaction of
an acid with the soaps gives free fatty acids (FFA). Since FFA’s are insoluble
in glycerol, these components will rise to the top so that they can be skimmed
off. Some glycerol-insoluble salts will also precipitate out.
The reaction mixture showed heavy foaming between pH 11 and 6.
After a stirring time of 30 minutes it was allowed to settle. Thereafter, the
reaction mixture formed three layers:
1.
2.
3.
a top layer containing free fatty acids
a middle layer which is the glycerol-rich layer
a bottom inorganic salt rich precipitate.
The layers were separated by simple phase separation.
The quantity of water, used for dilution does not influence the phase
separation. The handling of the crude G-phase is easier in case of higher
water dilution but it would increase the cost of purification. Nevertheless a
dilution by 25% water seemed to be optimal and this quantity was used in
the following experiments.
Table 1. Effect of pH on phase separation after acid treatment of G-phase
Time (min) necessary for phase
separation
Clearance of phase boundary
2
pH
3
20
30
100
++
+++
+
4
Also, the influence of pH was investigated. As Table 1 demonstrates
at pH value of 4 a diffuse phase formed at the border of the layers and almost
two hours were needed for separation. The clearest phase boundary between
the two layers was obtained at pH value of 3, it was found to be the optimum
during acid treatment.
9
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
Neutralization by Ca(OH)2
The excess of the phosphoric acid was neutralized by a 25 wt%
Ca(OH)2 aqueous slurry. The lowest solubilities of phosphates in crude glycerol
were seen to exist near a pH value of 5. The effect of pH (pH=6 and pH=7)
was investigated, however filtration was more difficult at higher pH values.
Adsorption by activated carbon
Due to the fact that all filtrates showed a yellow to brownish color, it
was investigated whether color bodies could be adsorbed by activated carbon
(powder). Table 2 contains the results.
Table 2. Effect of activated carbon on color removal of partly purified G-phase
Amount of activated carbon (wt%)
Color of filtrate after adsorption
(Gardner)
0
1
2
3
4.8
1.5
1
1
Original color of crude glycerol coming from the biodiesel plant
decreased from 6.7 to 4.8 Gardner during the first processing steps (acid
treatment and neutralization). Obviously the upper free fatty acid-rich phase
removed a lot of color bodies. An addition of 2 wt% of activated carbon
allowed to decrease the color of partly purified G-phase, moreover the
odour was reduced by activated carbon, as well.
Purification by distillation
The decolorized solution was containing glycerol, water and salts,
only. All water was removed by distillation at 62-67°C under vacuum (~ 3
kPa). After the light removal the glycerol content of this partly purified glycerol
went up to 91.05 wt%.
Distillation of glycerol is a rather expensive step in the purification
process of crude glycerol, moreover under distillation conditions the salt
content causes an enormous viscosity increase of the distillation feedstock,
which necessitates so called “salt towers”, an expensive type of equipment,
both by investment and by operation cost, too. That is the reason why partly
purified glycerol containing inorganic salts was also tested as raw material
in synthesis of tripropionin.
Material balance of crude glycerol purification
After physical and chemical treatment, per kg crude glycerol 0.443
kg glycerol (average value) was recovered having a purity of 91.05 wt%.
10
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
Expensive distillation of glycerol was not necessary to reach this purity. Table 3
summarizes the properties of the purified crude glycerol of this work in
comparison with results of other publications [11, 12].
Originally, contaminants correlated to the matter organic nonglycerol (MONG) group material represented the highest level of impurities.
Due to the acid treatment, the MONG content could be reduced from 44.95
wt% down to 4.86 wt%.
The majority of ash content of 4.81 wt% correlates with the
transesterification catalyst (KOH).
Table 3. Comparison of purified crude glycerol properties obtained
from this work with other works
Author
Source of
crude
glycerol
Glycerol
(wt%)
(a)
Ooi et al Palm kernel
17.7
[11]
oil
Kongjao
Waste
28.56
et al
used-oil
[12]
This work Rape-seed 49.14
Ash
(wt%))
MONG
(wt%)
Water
(wt%)
(b)
(a)
(b)
(a)
(b)
(a)
(b)
51.4
58.7
13.8
17.7
25.9
5.9
8.9
93.34
2.65
4.5e-4
56.13 5.16
6.7
1.5
91.05
4.81
3.64
44.95 4.86
1.1
0.45
(a) Concentration of glycerol and impurities content in the original crude glycerol
(b) Concentration of glycerol and impurities content in the purified crude glycerol
Figure 1 shows the measured material balance of our crude glycerol
refining process. 82 wt% of the original glycerol content was recovered.
This seems to be a promising result when considering the numerous
purification steps.
Certain purification steps can be eliminated depending on the further
utilization. For example the adsorption step on charcoal and filtration could
be left out, if the partly purified glycerol still containing inorganic salts is
used as raw material in synthesis of a value-added glycerol derivative, whose
color needs to be reduced after the reaction.
11
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
Figure 1. Material balance of crude glycerol purification
Preparation of tripropionin
Triproprionin can be produced in an acid-catalyzed reaction of glycerol
with propionic acid (see Scheme 1).
Di- and tri-propyl esters of glycerol are potential oxygenate-additives
to diesel fuels because of their good properties as blending components, but
also having excellent solubility in diesel fuel. Mono-propyl ester of glycerol is
more polar and has a low solubility in diesel fuel and therefore the esterification
of glycerol must be directed to the maximum yield of di- and tri-esters.
12
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
HO
OH
+
3
O
O
O
OH
O
O
OH
+
3 H2 O
O
O
Scheme 1
The boiling point of dipropionin and tripropionin are BpDP=292°C,
BpTP=290.7°C (BpMP=n.a.), therefore the separation of tripropionin from
mixture containing mono-di and tripropionin by distillation is impossible.
To simplify the process our aim was to synthesize tripropionin by a
one-step process with the highest possible selectivity.
The influence of the main reaction parameters, like reaction
temperature, quality of raw material and the catalyst on the esterification of
glycerol with propionic acid was studied.
The esterification of glycerol (G) with propionic acid (PA) is a
complex of three acid catalyzed consecutive equilibrium reactions with
formation of monopropionin (MP), dipropionin (DP) and tripropionin (TP).
G + PA
MP + PA
DP + PA
MP + H2O
DP + H2O
TP + H2O
The reaction was carried out in presence of sulfuric acid starting
from pure glycerol and partly purified glycerol, still containing inorganic salts.
The formed reaction water was removed by straight-forward distillation in
absence of entraining solvents. The comparison of the results starting from
different raw materials is shown in Table 4.
A better result namely a conversion of 100% and a selectivity of 98 %
yield was obtained in case of pure glycerol, as it was predicted before the
experiments.
Table 4. Effect of quality of raw material on esterification of glycerol by propionic
acid in presence of sulfuric acid (propionic acid/glycerol molar ratio:
6:1, 2-fold excess, reaction temperature: 120-160°C)
Raw
material
Pure
glycerol
Glycerol
cont. salt
Catalyst
Entraining
solvent
H2SO4
H2SO4
Selectivity %
MP
DP
TP
XG %
YTP %
-
0.0
2.0
98.0
100.0
98.0
-
0.0
13.2
86.8
100.0
86.8
13
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
When the starting glycerol was containing salt the yield of tripropionin
dropped down to 86.8% (see Table 4)
The zeotropic removal of water requires a separation tower. Without a
separation tower a significant loss of propionic acid was obtained.
Role of entraining solvents and ion exchange resins
Homogeneous catalysts are very effective but require additional
handling steps. It is imperative to remove catalysts before distillation, therefore,
higher production costs have to be expected [13]. Appropriate fixed-bed
catalysts could be incorporated into a packed-bed, continuous flow reactor,
simplifying the product separation and purification, but also reducing the
waste formation.
In esterification reactions of carboxylic acids with alcohols it is standard
to use homogeneous catalysts like sulfuric acid, methane sulfonic acid,
hydrofluoric acid, p-toluene-sulfonic acid or the like. Usually, such homogeneous
catalysts have to be removed by additional treatment steps during the process.
Therefore, heterogeneous catalysts are becoming more and more in
the focus of the industry. The literature is containing numerous publications
describing heterogeneous acid catalysts for esterification processes.
So for instance, good results were reported using ion-exchange resins
like Amberlyst A15 or Nafion in esterification processes [14, 15]. Generally
speaking, the catalytic activity of organic resins is strongly depending on their
swelling properties. Resin swelling capacity is fundamental since it controls
substrate accessibility to the acid sites and, therefore, affects its overall
reactivity. Once swelled, the resin pores usually become macropores. This
means that big molecules with long hydrocarbon chains show no diffusion
limitations and can readily access the acid sites in the bulk.
Table 5. Characteristics of ion-exchange resins (Amberlyst 15 and 36)
Average
Catalyst CrossAcidity
pore
(short
linked
(mmol/g) diameter
name) structure
(nm)
A 15 (Dry)
V
4,7
30
A 36 (Wet)
M
5,4
24
SBET
(m2/g)
Particle
size
(mm)
Moisture
capacity
(%)
Tmax
(°C)
53
33
0,6-0,85
≤1,6
53-59
120
150
A: Amberlyst. Crosslinked structure: V-very, M-medium
Despite of the fact that most ion-exchange resins are not stable at
temperatures above 140 °C [16], which limits their application to reactions
that require higher temperatures, Amberlyst A15 and A36 were investigated.
14
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
Physical characteristics of ion-exchange resin catalysts are summarized
in Table 5 [17].
The use of entraining agents for the water removal is of great help
not to exceed the maximal operation temperature of ion-exchange resins in
esterification reactions. Together with ion-exchange resins as esterification
catalyst MIBK and n-hexane were tested as entraining agents.
It can be seen from Table 6 the highest yield was reached when raw
material was pure glycerol and MIBK was used as entraining solvent in
presence of Amberlyst A36 catalyst. Due to the higher boiling point of MIBKwater azeotrope, the temperature of the reaction media was higher (110120°C) than in case of n-hexane (68-74°C) and higher temperature may be
favored by Amberlyst A36.
When raw material was pure glycerol in presence of n-hexane
Amberlyst A15 gave better result than Amberlyst A36 which may mean that
the optimal working temperature of Amberlyst A15 is lower.
Table 6. Comparison of catalysts, entraining solvents and quality of raw materials
for esterification of glycerol (propionic acid/glycerol molar ratio: 6:1, 2-fold excess,
reaction temperature: 110-120°C in case of MIBK, 68-74°C in case of
n-hexane and 100-124°C in case of toluene)
Raw
material
Pure
glycerol
Pure
glycerol
Glycerol
cont. salt
Pure
glycerol
Pure
glycerol
*Glycerol
cont. salt
Glycerol
cont. salt
Catalyst
Entraining
solvent
Selectivity %
MP
DP
TP
XG %
YTP %
A15
MIBK
8.7
10,1
81,8
100.0
81.8
A15
n-Hexane
0.0
11.6
88.4
100.0
88.4
A15
n-Hexane
0.0
74.8
25.2
100.0
25.2
A36
MIBK
0.0
0.0
100.0
100.0
100.0
A36
n-Hexane
0.0
42.3
57.7
100.0
57.7
A36
n-Hexane
0.0
72.7
7.7
100.0
7.7
H2SO4
Toluene
0.0
4.0
96.0
100.0
96.0
* Significant by-product formation was observed
When partly purified glycerol is used as raw material ion-exchange
resins are not as effective as in case of pure glycerol. Reaction product
contained mainly dipropionin. This could be explained by the desactivation
of active sites of ion-exchange resin by salts, present in that raw material.
15
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
When partly purified glycerol was used as raw material the best result,
96% yield of tripropionin was achieved in presence of H2SO4 catalyst and
toluene as entraining solvent.
Distillation of tripropionin
Although, it was known that separation of mono- di- and tripropionin is
not possible by distillation. Therefore, a final product purification of tripropionin
by distillation was investigated from the point of view of color-removal.
In this case a relatively pure bottom product containing 95% tripropionin
was distilled. The distillate contained the components by almost the same
ratio as they were present in the raw material. However, the color of material
improved significantly (see Table 7).
Considering the material balance of distillation, tripropionin is
thermally stable at high temperature (up to ~200°C).
Table 7. Results of distillation of tripropionin under 0.6 kPa vacuum
Weight (g)
Raw material
Distillate
Residue
200.0
155.4
44.6
Monopropionin Dipropionin Tripropionin Color
(a%)
(a%)
(a%)
(Pt-Co)
0
3.6
95.0
423
0
2.7
96.2
62
0
4.3
93.1
n.a.
Material balance of tripropionin synthesis from crude glycerol
A sulfuric acid catalyzed reaction, starting from partly purified
glycerol, seems to be the most economical way of tripropionin synthesis.
When the reaction water was removed by an azeotropically distillation with
toluene, tripropionin yield of >96% was obtained. Considering a technical
manufacturing toluene would provide technical and commercial benefit like
low solubility in water and low price.
The most difficult problem concerning crude glycerol refining is the
removal of salt which is formed during neutralization of the catalyst (KOH,
NaOH).
Due to the fact that presence of salts is not disturbing the formation
of tripropionin using sulfuric acid, all formed salts can be removed by
simple filtration. Such an operation is supported by the facts, that these
salts are insoluble in the reaction media, but also easy filterable.
If applications of tripropionin do not require low-color material, an
expensive purification step by distillation can be ignored.
Based on the experimental results the following material balance
was calculated (see Figure 2 and Table 8).
16
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
Water
56.64 kg
Incineration
Free fatty acids
44.95 kg
Biodiesel
500 kg
Vegetable oils, animal fats,
methanol, NaOH
Propionic acid
118.70 kg
Sulfuric acid
4.14 kg
Biodiesel
plant
Crude glycerol
100 kg
Soap splitting
Water
26.70 kg
Phosphoric acid (85%)
12.30 kg
Inorganic salt+ heavies
9.60 kg
+11.55 kg
Distillation
tower
Solvent
150 kg
Reactor
Glycerol
49.14 kg
Water
27.80 kg
Salt
7.41 kg
Filtration
Tripropionin
139.10 kg
Figure 2. Potential process flow sheet for production of tripropionin from crude glycerol
The manufacture of tripropionin from crude glycerol using entraining
agents allows to remove beside the reaction water also water which is
remaining from the biodiesel process. Therefore, any earlier dewatering
step became obsolete.
Table 8. Mass balance of tripropionin synthesis from crude glycerol
Stream
Crude glycerol
Water
Phosphoric acid
Sulfuric acid
Propionic acid
Solvent (toluene)
Free fatty acids
Inorganic salt
Tripropionin
Input (kg)
100.00
26.70
12.30
4.14
118.70
150.00
-
Output (kg)
56.64
150.00
44.95
21.15
139.10
Any activated-carbon treatment of crude glycerol seems to be
unnecessary because tripropionin needs to be decolorized at the end of the
process, if the application requires low colored material.
17
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
Considering the low prices of raw materials and the severity of the
process, tripropionin produced from crude glycerol can be competitive with
commercial fuel additives.
Engine performance
Reduction on engine emissions is one major research aspect in engine
development because of an increasing concern on environmental protection
and strengthening of emission regulations [18]. Diesel engines have the
advantages in good fuel economy and low CO2 emission but may produce
high carbon monoxide (CO) and smoke.
Effect of tripropionin blending on engine performance characteristics and
environmental repercussions were studied (Table 9). VW-AUDI 1.9 TDI engine
was used for the measurements. Blended fuel contained 5 wt% tripropionin.
An increase of total unburned hydrocarbons (THC) in blended fuel
was observed which must be in connection with the inadequate burnout of
tripropionin. Due to the high oxygen content of tripropionin a decrease of
CO, smoke and exhaust temperature was observed.
Table 9. Comparison of reference fuel and blended fuel
THC [ppm]
NOX
CO (V/V%)
Smoke [FSN]
Specific fuel consumption
[g/kWh]
Texhaust [°C]
Reference fuel
35.6
767
0.0174
1.48
251
Blended fuel
37.0
768
0.0163
1.29
260
Change [%]
+3.9
+0.1
-6.3
-12.8
+3.6
524
520
-0.8
According to the engine performance characteristics and environmental
repercussions tripropionin represents a promising material, which can be
used as fuel additive. Further studies need to be done to find the optimal ratio
of tripropionin in Diesel oil.
CONCLUSIONS
Crude glycerol is a considerable by-product of biodiesel production
for which new uses are being sought. Purification of G-phase and esterification
of glycerol with propionic acid using sulfuric acid and Amberlyst type strong
acid ion-exchance resins were studied. The best result of pure glycerol
esterification by propionic acid, 100% yield of tripropionin was obtained in
presence of Amberlyst36 catalyst and MIBK entraining solvent.
18
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
However a sulfuric acid catalyzed reaction, starting from partly purified
glycerol still containing inorganic salts, seems to be the most economical
way of tripropionin synthesis. When the reaction water was removed by an
azeotropically distillation with toluene, tripropionin yield of >96% was obtained.
It has been proven that presence of inorganic salts is not disturbing the
formation of esters using the conventional acid catalyst, sulfuric acid. Since
all formed salts can be removed by simple filtration, expensive purification
of the product by distillation is not necessary.
An economical process for utilization of crude glycerol was created,
which can be applied not only for tripropionin production but preparation of
other glycerol esters like glyceryl triacetate, glyceryl tributyrate.
Tripropionin represents a promising material, which can be used as
fuel additive to improve engine performance characteristics and environmental
repercussions. Further studies need to be done to find the optimal ratio of
tripropionin in Diesel oil.
EXPERIMENTAL SECTION
Chemicals
Crude glycerol was obtained from a local biodiesel plant - Öko-Line
Hungary Ltd. This company utilized rapeseed oil for biodiesel production via
alkali (KOH) catalyzed transesterification process.
The wet ion-exchange resin Amberlyst A36 from Sigma-Aldrich was
washed with methanol and dried to remove water from the catalyst. Amberlyst
A15 strongly acidic, cation exchanger resin (dry, moisture content ~5 wt%)
from Sigma-Aldrich was used without pretreatment. Pure glycerol (99.5 wt%
purity), activated-carbon powder (Norit) and calcium-hydroxide (95 wt% purity)
were obtained from Spektrum-3D Ltd. (Hungary). Propionic acid (>99 wt%
purity), methyl isobutyl ketone (>98.5 wt% purity), n-hexane (>96 wt%
purity), toluene (>99.8 wt% purity), phosphoric acid (85 wt% purity) and
sulfuric acid (95 wt% purity) were obtained from Sigma-Aldrich.
Analytical methods
Glycerol content of samples were analyzed with a Merck LaChrom
HPLC equipped with an Ultrahydrogel column (I.D. = 7.8 mm, L= 300 mm)
and a Merck LaChrom RI detector. Water was used as eluent (flow rate: 0.8
ml/min, temperature: 30°C).
The water content was determined by volumetric Karl Fischer titration.
Ash content was analyzed by burning 1 g glycerol in muffle furnace
at 750 °C for 3 h.
19
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
For matter organic non-glycerol (MONG), it was calculated by the
difference from a hundred of the previous three compositions (100 − (%
glycerol content + % water content + % ash content)).
The samples of reaction products were analyzed with a HP 5890
Series II gas chromatograph equipped with a Restek Rtx-5MS column (30m
x 0.25 mm x 0.25 µm) and a HP 5971 MSD detector. Analyses were carried
out with temperature program from 60 to 240°C (with a slope of 10°C min-1)
and 240°C for 2 min isothermally.
The color of the samples was measured using a Lovibond Colorimeter,
model PFX190.
Effect of tripropionin blending on engine performance characteristics
and environmental repercussions were tested by a four-cylinder turbocharged
direct injection diesel engine (VW-AUDI 1.9 TDI). Blended fuel contained 5
wt% tripropionin which was prepared from partly purified glycerol, entraining
solvent was toluene and sulfuric acid was used to catalyze the reaction.
Apparatus and procedure
Procedure A: Purification of crude glycerol
The first step of our refining process was an acid treatment. To make
the handling of crude glycerol easier it was diluted by distilled water. Under
vigorous stirring phosphoric acid (85 wt%) was added slowly to crude glycerol
by pH control. The mixture was stirred at 80 °C, for 30 minutes in a 500 ml
three necked round bottomed flask equipped with a thermometer, mechanic
stirrer, heating jacket and a reflux condenser. The role of the pH on the
product mixture was investigated to check the phase separation conditions.
The reaction of an acid with the soaps will give free fatty acids (FFA).
Since FFA’s are insoluble in glycerol, these components will rise to the top
so that they can be skimmed off. Some glycerol-insoluble salts will also
precipitate out. The necessary time of the phase separation was measured.
After this treatment salts were filtered by G3 glass filter. The free fatty acids
were separated from crude glycerol by simple phase separation.
The next step was the neutralization of excess acid. For that purpose
a calcium-hydroxide slurry containing 25 wt% Ca(OH)2 was added to the
glycerol phase to reach a pH value of about 5. All precipitated calciumphosphates
was eliminated by simple filtration on G3 glass filter.
The filtrate coming from such a neutralization step is yellow or light
brown. Pigments and odor bodies were eliminated by adsorption on activated
carbon. For that purpose activated charcoal powder was added to the glycerolcontaining phase. This mixture was heated to 60°C and stirred for half an hour in
a three necked round bottomed flask equipped with a thermometer, mechanic
stirrer, heating jacket and a reflux condenser. After the adsorption step activated
carbon was filtered off by a G4 glass filter. Different quantities of activated
carbon were used to find the best adsorption conditions.
20
SYNTHESIS OF TRIPROPIONIN FROM CRUDE GLYCEROL THE BY-PRODUCT OF BIODIESEL PRODUCTION
That solution contained glycerol, water and salts, only. The removal of
all water contained was done by distillation at 62-67°C under vacuum (~ 3kPa).
Most of the reactions were carried out using pure glycerol (>99.5%) to get
reference results, but our final aim was to apply partly purified glycerol
(containing salt) to produce tripropionin.
Procedure B: Tripropionin synthesis by straight – forward distillation
In a typical run, 46 g (0.5 mol) of glycerol or 50 g partly purified glycerol
(~0.5 mol) containing inorganic salts and 222 g (3 mol) propionic acid were
used. As catalyst 2 ml H2SO4 was used.
The esterification reactions were carried out in a 500 ml glass round
bottomed flask equipped with a magnetic stirrer, heating jacket, thermometer
and a distillation bridge.
Propionic acid was always used in excess (usually 2-fold molar excess)
to shift reaction equilibrium towards the product. Reactions were carried out
by straight – forward distillation in absence of entraining solvents.
All water formed during the esterification was removed together with
some propionic acid. When temperature reached 141°C, the boiling point of
propionic acid, the reaction was stopped.
Homogenous catalyst was neutralized by 50 wt% NaOH aqueous solution.
Inorganic salts formed an easy-filterable precipitation, now. This
precipitate was filtered off and the unreacted propionic acid and remaining
water were removed by simple distillation under vacuum at 3 kPa.
For the purification of tripropionin by distillation an apparatus was
used consisting of a 500 ml glass round bottomed flask equipped with a
magnetic stirrer, heating jacket, thermometer and a 30 cm long tower packed
by Raschig rings. For fractionation the crude tripropionin was heated up to
200°C bottom temperature at a pressure of 0.6 kPa.
Procedure C: Tripropionin synthesis by azeotropic water removal
In a typical run, 46 g (0.5 mol) of glycerol or 50 g partly purified
glycerol (~0.5 mol) containing inorganic salts, 222 g (3 mol) propionic acid
were used. As catalyst 2 ml of H2SO4 was used, alternatively 10 g of Amberlyst
A15 or 12 g of Amberlyst A36 ionexchange resins.
The esterification reactions were carried out in a 500 ml glass round
bottomed flask equipped with a magnetic stirrer, heating jacket, thermometer
and a calibrated Dean-Stark trap connected to a reflux condenser.
Propionic acid was used in excess (2-fold molar excess) to shift
reaction equilibrium towards the product. For the azeotropic removal of the
reaction water different entraining solvents like MIBK, n-hexane and toluene
were used. The heterogeneous water-solvent azeotropes were phase separated
and the solvent recycled to the reaction flask. For product purifications the
same method was used as described under procedure B.
21
ZSANETT HERSECZKI, GYULA MARTON, ANDRAS DALLOS
RE F E R E N CE S
1. W. Xie, Z. Yang, H. Chun, Industrial & Engineering Chemistry Research, 2007,
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4. Y.C. Lin, International Journal of Hydrogen Energy, 2013, 38, 2678.
5. P. Anand, R.K. Saxena, New Biotechnology, 2011, 00, 1.
6. F. Yang, M.A. Hanna, R. Sun, Biotechnology for Biofuels, 2012, 5, 13.
7. B.J. Kerr, W.A. Dozier, K. Bregendahl, Nutritional value of crude glycerin for
nonruminants. In Proceedings of the 23rd Annual Carolina Swine Nutrition
Conference, Raleigh, NC, 2007, 6.
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of Oil Palm Research, 2001, 13, 16-22.
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2010, 27, 944.
13. E. Lotero, Y. Liu, D.E. Lopez, K. Suwannakarn, D.A. Bruce, J.G. Goodwin,
Industrial & Engineering Chemistry Research, 2005, 44, 5353.
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16. Z.Y. Zhang, K. Hidajat, A.K. Ray, Journal of Catalysis, 2001, 200, 209.
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18. X. Wang, C.S. Cheung, Y. Di, Z. Huang, Fuel, 2012, 94, 317.
22
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 23 – 34)
(RECOMMENDED CITATION)
REMOVAL OF ANIONIC DYE CONGO RED FROM
SYNTHETIC WASTEWATER USING IMMOBILISED FIR
SAWDUST (ABIES ALBA)
CERASELLA INDOLEANa, SILVIA BURCĂa,
ANDRADA MĂICĂNEANUa, MARIA STANCAa, DAN RĂDULESCUb
ABSTRACT. The purpose of this paper was to establish the optimum
experimental conditions for removal of Congo Red (CR) from aqueous
solutions by biosorption on alginate immobilized fir tree sawdust (Abies Alba)
beads. The studies were carried out under various experimental conditions.
Dye concentration, fir tree sawdust quantity, stirring rate and working regime
were considered in order to assess their influence on the biosorption process.
Removal efficiencies up to 97% were reached in the case of immobile phase
regime. Also, adsorption capacity increased with a decrease in the sawdust
quantity and an increase of the initial dye concentration. The results indicate
that this local immobilized material can be an attractive option for dye
removal from diluted industrial effluents.
Keywords: biosorption, Congo red, immobilized fir tree sawdust, alginate
beads, kinetics
INTRODUCTION
Wastewater effluents from many industries such as textile, rubber,
paper, leather plastics, cosmetic, painting, etc. contain several kinds of synthetic
dyes [1]. This dye-bearing wastewater exhibits high color. Thereby, a very
small amount of dye in water is highly visible and therefore, the discharge
of these effluents in the environment is worrying for both toxicological and
aesthetical reasons [2].
As we know, dyes can be classified into cationic, anionic and nonionic
dyes. Cationic dyes are basic dyes while the anionic dyes include direct, acid
and reactive dyes [3]. The main problem in treating wastewater containing dyes
is related to the high stability of these pollutant species, (they are resistant
a
b
Universitatea Babeş-Bolyai, Departamentul de Inginerie Chimică, Str. Arany Janos nr. 11,
RO-400028 Cluj-Napoca, Romania, cella@chem.ubbcluj.ro
Universitatea de Medicină şi Farmacie Iuliu Haţieganu, Departamentul de Cardiologie, str.
V. Babeş nr.8, RO-400012 Cluj-Napoca, Romania, dan_rad31@yahoo.com
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
to moderate oxidizing agents and light, and cannot be removed completely
by conventional methods of anaerobic degradation [4]).
Recently, numerous studies have been reported for the adsorption
of cationic and anionic dyes by agricultural based adsorbents, such as rice
husk [5], tea waste [6], coniferous pins bark powder [7], peanut hull [8],
almond shell [9], lemon peel [10], etc.
Adsorption is a very effective separation technique and now it is
considered to be superior to other techniques for wastewater treatment in
terms of initial cost, simplicity of design, easy of operation and insensitivity
to pollutant substances [11-14].
Congo Red (CR, chemical formula = C32H22N6Na2O6S2, FW = 696.68,
λmax = 497 nm) is a benzidine-based anionic diazo dye, i.e. a dye with two
azo groups. The structure is as illustrated in Figure 1. This anionic dye, in
general has been known to cause human allergic reactions and to be
metabolized to benzidine, a human carcinogen [15].
NH2
NH2
N N
O
S
-
O
N N
O
+
O Na
S
-
O
+
O Na
Figure 1. Structure of CR molecule
Abies Alba fir is a common tree from some forest areas in Transylvania
(Romania). These trees are the main source for the local wood industry and
their sawdust could be a good candidate as a green and economic alternative
for Congo Red (CR) removal from wastewater. Previous studies realized on
sawdust (timber, pine, Shorea dasyphylla, beech wood) showed that they
can be used successfully to remove different dyes (methylene blue, direct
brown, basic blue, acid blue) from wastewaters [16-19].
Different matrices that can be used for the immobilization of biomass
such as alginate [20], chitosan [21], or polyvinylalcohol (PVA) with kaolin
[22], etc. are available.
Predicting the rate at which adsorption takes place for a given system
is probably the most important factor in adsorption system design, with
adsorbate resistance time and the reactor dimensions controlled by the system
kinetics [23]. In order to investigate the mechanism of adsorption, various
kinetic models have been suggested. Numerous kinetic models have described
the reaction order of adsorption system based on solution concentration. These
24
REMOVAL OF ANIONIC DYE CONGO RED FROM SYNTHETIC WASTEWATER
include first-order [24] and second-order [25] reversible ones, and first-order
[26] and second-order [27] irreversible one, pseudo-first-order [28] and pseudosecond-order [29] based on the solution concentration.
The goal of this study was to realize the Congo red biosorption onto
immobilized fir tree sawdust (IFTS) from Romanian wood industry and to
offer an effective and economical alternative to more expensive adsorption
processes (commercial active carbon and resins). Therefore, biosorbent
quantity, dye concentration, optimum stirring rate and working regime influence
over the biosorption process were investigated in batch conditions. Kinetic
models of the considered biosorption process were discussed.
RESULTS AND DISCUSSION
The effect of biomass quantity
The effect of biomass quantity on the biosorption of CR was studied
using different masses of sawdust. To establish the optimal dose of adsorbent
100 mL synthetic solution of CR dye, with concentration 50 mg/L was used.
Experiments were conducted in batch conditions under magnetic stirring at 300
rpm and room temperature (T = 22°C), using different amounts of sawdust, 1,
2, 3, 4 and 5 g, respectively, immobilized in sodium alginate (IFTS).
Experiments have shown that equilibrium was reached after about
180 minutes when 1, 2 and 3 g of sawdust were used, and after about 150
minutes when 4 or 5 g sawdust were used (Figure 2).
60
C (mg CR/L)
50
40
30
20
10
1g
2g
3g
4g
5g
0
0
50
100
150
200
250
t (min)
Figure 2. CR concentration time evolution for different initial sawdust quantities
(100 mL solution, 50 mg CR/L, 300 rpm, room temperature).
25
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
The diagram from Figure 3, gives the maximum removal efficiency E (%)
as a function of the biomass quantity. As shown in Figure 3 the maximum
removal efficiency varies from 32.35 to 62.04% for 1 and 5 g of sawdust,
respectively. The best results were obtained for 4 g (57.66 %) and 5 g (62.04 %).
Taking into consideration the fact that the fir tree sawdust is a by-product,
therefore is available in large quantities and at very low cost, the experiments
were further considered using 5 g for maximum removal efficiency.
5g
4g
3g
2g
1g
0
20
40
60
80
E (%)
Figure 3. Influence of sawdust quantity over the maximum biosorption process
efficiency (100 mL solution, 50 mg CR/L, 300 rpm, room temperature).
The effect of initial CR solution concentration over the biosorption process
Experiments were conducted using volumes of 100 mL CR aqueous
solutions with the following concentrations: 50, 105, 150, 200 and 255 mg/L
dye and were realized in batch conditions, with magnetic stirring at 300 rpm, at
room temperature (T = 22°C) and 5 g of fir tree sawdust, immobilized in
sodium alginate.
As the initial concentration decreases, the quantity of dye (CR) retained
in the first 30 minutes decreases also due to the smaller difference that exist
between the concentration of dye on the adsorbent surface and in the solution.
As the initial concentration increases, biosorption process equilibrium was
reached more difficult, after about 180 minutes, by comparison with just 80
minutes for small concentrations (50 – 105 mg CR/L) (Figure 4).
26
REMOVAL OF ANIONIC DYE CONGO RED FROM SYNTHETIC WASTEWATER
The biosorption was noted to occur in two phases of fast and slow
rates. This variation could be explained by the easiness with which organic
dye gain access to the adsorption sites (favoured by the small stirring rate
and macroporosity of the lignocellulosic materials) and by the high activity
of the adsorption sites. The formation of a plateau shows a maximum
occupation of available biosorption sites, marking thus, the equilibrium
achievement of the biosorbate/biosorbent system.
300
C (mg CR/L)
250
200
150
100
50
0
0
50
100
150
200
250
t (min)
50 mg/L
105 mg/L
200 mg/L
255 mg/L
150 mg/L
Figure 4. CR concentration time evolution for different initial concentrations (100 mL
solution, 5g fir tree sawdust immobilized in alginate beads, 300 rpm, room temperature).
Experimental results showed that biosorption capacity increases
with increasing concentration of CR dye in aqueous solution, from 0.51
mg/g when a 50 mg CR/L aqueous solution was used up to 1.43 mg/g
when a 255 mg CR/L aqueous solution was used (Figure 5).
Establishing optimum stirring rate
The experiments of biosorption for 5g of fir tree sawdust immobilized in
alginate were repeated with varying stirring rate at 300, 500 and 700 rpm, at
initial dye concentration of 50 mg CR/L. The efficiency of each experiment is
presented in Figure 6. The diagram obtained showed that the biosorption
process was intensified with a decrease of stirring rate down to 300 rpm
(62.04%). Higher stirring rates, (500 and 700 rpm) will lead to a decrease in
efficiency from 45.98% (for 500 rpm) to 29.92% (for 700 rpm), showing that
after a certain stirring speed, the minimization of the thin film layer formed at
the beads surface will not lead to a further increase in the external diffusion rate.
27
qmax (mg CR/g)
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
1,6
1,4
1,2
1,0
0,8
0,6
0,4
0,2
0,0
1,43
1,27
0,92
1,09
0,51
50
105
150
200
255
C (mg CR/L)
Figure 5. Influence of CR concentration over the biosorption
capacity (100 mL solution, 5 g fir tree sawdust immobilized
in alginate beads, 300 rpm, room temperature).
v (rpm)
700
500
300
0
20
40
60
80
E (%)
Figure 6. Influence of stirring rate over the maximum biosorption
process efficiency (100 mL solution, 50 mg CR/L, 5 g fir tree
sawdust immobilized in alginate beads, room temperature).
The influence of working regime on biosorption process
In figure 7, a comparison of maximum removal efficiencies is presented
for the experiment conducted in mobile and immobile phases regime, at
different initial concentrations (Ci = 50 – 255 mg CR/L). A closer inspection of
this diagram conducts to the conclusion that for all five dye initial concentrations
28
REMOVAL OF ANIONIC DYE CONGO RED FROM SYNTHETIC WASTEWATER
the immobile phase regime is the best solution, leading to the highest removal
efficiencies 97.08% (50 mg/L), 96.92% (105 mg/L), 96.41% (150 mg/L), 95.68%
(200 mg/L) and 95.14% (255 mg/L). Equilibrium was reached in 250 hours
(10 day, approximately), for all five experiments.
In mobile phase regime, the same systems were studied and the
conclusion was that this type of regime leads to maximum biosorption
efficiency between 33.99% (for C0 = 255 mg CR /L) and 62.04% (for C0 =
50 mg CR /L), as it can be seen in Figure 7.
These results suggested that due to the size of the CR molecule,
diffusion could have an important role in biosorption process, therefore we
decided to conduct further experiments in immobile phase regime.
100
E (%)
80
60
40
20
0
50
105
150
200
255
C (mg CR/L)
Mobile phase regime
Immobile phase regime
Figure 7. Influence of working regime over the maximum biosorption
process efficiency (100 mL solution, 5 g fir tree sawdust immobilized
in alginate beads, 300 rpm, room temperature).
Adsorption kinetics
Pseudo-first-order (Lagergren) [30] and pseudo-second-order (Ho) [31]
models were used to study the adsorption kinetic of CR onto immobilized
sawdust sample. Linear regression was used to determine the best fitting
kinetic rate equation (correlation coefficients, R2) [32].
Lagergren suggested a first order equation for the adsorption of liquid/
solid system based on solid capacity, which can be expressed as follows:
dqt
= k 1 (q e − q t )
dt
(1)
29
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
Integrating equation (1) from the boundary conditions t = 0 to t = t and qt =
0 to qt = qt, gives:
ln(qe − qt ) = ln qe − k1t
(2)
where,
qe and qt are the amounts of CR adsorbed (mg/g) at equilibrium and
time t, respectively
k1 is the rate constant of first order adsorption (1/min).
In order to determine the rate constant and equilibrium of CR uptake,
the straight line plots of ln(qe-qt) against t, eq. (2), were made at five different
initial dye concentrations. Because correlation coefficients are modest
(between 0.653 and 0.739, figure not shown), CR biosorption onto fir tree
sawdust cannot be classified as first order.
The pseudo-second-order kinetic model is derived on the basis of
the adsorption capacity of the solid phase, expresses as [27]:
dqt
= k 2 (qe − qt )2
dt
(3)
Integrating eq. (3) from the boundary conditions t = 0 to t = t and qt = 0 to qt
= qt, gives:
1
1
=
+ k2t
(qe − qt ) qe
(4)
where,
qe and qt are the amounts of CR adsorbed (mg/g) at equilibrium and
time t, respectively
k2 is the rate constant of first order adsorption (g/mg·min).
Equation (4) can be rearranged in linear form, as follows:
t
1
t
=
+
2
q t k 2 qe qe
(5)
In order to determine the rate constant and equilibrium of CR uptake,
the straight line plots of t/qt against t, eq. (5), were made at five different
initial dye concentrations. Correlation coefficients between 0.921 and 0.997
were obtained (figure 8 and table 1), therefore Congo Red adsorption onto
immobilized fir sawdust can be classified as pseudo-second-order.
30
REMOVAL OF ANIONIC DYE CONGO RED FROM SYNTHETIC WASTEWATER
500
400
t/qt
300
200
100
0
0
50 mg/L
50
105 mg/L
100
150
t (min)
150 mg/L
200
250
200 mg/L
300
255 mg/L
Figure 8. Plots of the second-order model, at different initial CR
concentrations (mobile phase regime, 5 g fir tree sawdust immobilized
in alginate beads, 100 mL CR solution).
Table 1. Second order adsorption rate constants, and calculated and experimental
Qe values for CR adsorption using different initial concentrations.
Concentration
(mg CR/L)
50
105
150
200
255
qe,exp
(mg/g)
0.51
0.92
1.09
1.27
1.43
k2
(g/mg·min)
15.04 ·10-2
4.62 ·10-2
3.29 ·10-2
2.43 ·10-2
1.91 ·10-2
qe,calc
(mg/g)
0.54
1.09
1.27
1.54
1.77
R2
0.997
0.978
0.986
0.921
0.921
CONCLUSIONS
This study presented results obtained for Congo Red biosoption on
popular Romanian fir tree sawdust (Abies Alba) from Transylvanian forests, in
immobilized form as biosorbent. The biomass was subjected only to mechanical
preparation in order to obtain the final biomass (washing, drying and sieving)
which was further immobilized in alginate beads. The effects of the initial
biomass quantity, initial dye concentration, stirring rate and working regime
on biosorption process were studied. Higher biomass quantity, 50 mg CR/L
initial dye concentration, reduced stirring rate and immobile phase regime were
all favoring the biosorption process. Removal efficiencies up to around 62 %
and a maximum adsorption capacity of 0.51 mg/g dye were obtained
experimentally, in mobile phase regime, while for immobile phase regime
removal efficiencies up to 97% were obtained.
31
CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
In conclusion, for removal of this bulky anionic dye molecule with
immobilized Romanian sawdust, the optimum conditions established experimental
are high quantities of biosorbent, immobile phase regime (10 days or probably
more, for higher concentrations), solution pH and room temperature.
Kinetics (pseudo-first- and pseudo-second-order) models of the
considered biosorption process were discussed. The kinetic of the process
was best described by the pseudo-second-order model, suggesting monolayer
coverage and a chemisorption process. According to the obtained results it
can be concluded that the fir tree (Abies Alba) sawdust it is a good biosorbent
for Congo Red dye from aqueous solutions, especially in immobile phase regime.
EXPERIMENTAL SECTION
Biosorbent
The fir tree (Abies Alba) sawdust was obtained from a local sawmill in
Mărgău vilage, Cluj County, Romania. Prior to its utilization the considered
biomass was washed several times with distilled water in order to eliminate
surface impurities, was dried at 105°C for 24 h. Finally the dried biomass
was grinded and sieved (400-600 µm). The sieved sawdust was then stored in
an airtight box before its utilization. No further chemical treatments were
considered at this stage.
Preparation of Congo Red (CR) solutions
The dye stock solution (1000 mg/L) was obtained by dissolving the
necessary quantity of solid substance, CR (analytical purity reagent) in distilled
water. From this solution were further prepared solutions with known
concentration in 50-255 mg CR/L range.
Immobilization of fir sawdust.
Our technique draws inspiration from the methods described by Akar
et al., (silica-gel-immobilized waste biomass) [33], Rangsayatorn et al. (cells of
Spirulina platensis TISTR 8217 immobilized in alginate and silica gel) [35] and
Mata et al. (calcium alginate xerogels and immobilized Fucus vesiculosus)
[35]. In this work, the beads were prepared by mixing 1-5 g of fir sawdust
powder to 1 g of sodium alginate and an amount of water varying between 20
and 35 mL according to the quantity of the biosorbent and mixture viscosity.
The mixture was blended until was homogeneous and fluid. Then, the mixture
was dropped through a syringe using a 1.2 mm in diameter needle into a 0.2 M
solution of CaCl2 when beads with diameter between 1.5 and 2.0 mm were
formed. Once the beads were formed, stirring was stopped and the beads
were let at rest for at least two hours, then removed, washed with water and
then conserved in demineralised water, and spin dried before further use.
Biosorption experiments
The Congo Red (CR) biosorption studies were realized using fir tree
sawdust (Abies Alba) in alginate immobilized form (IFTS).
32
REMOVAL OF ANIONIC DYE CONGO RED FROM SYNTHETIC WASTEWATER
Biosorption process was conducted in batch conditions, under mobile
phase regime (magnetic stirring), and also in immobile phase regime (the
biosorbent was contacted with the solution and the process was realized
without further stirring), through the contact of a certain amount of biosorbent
with a volume of 100 mL dye aqueous solution of various concentrations. The
biosorbtion process was realized until equilibrium was reached.
The CR concentration in solution was determined using a Jenway
6305 UV-VIS spectrophotometer at a wavelength of 498 nm and appropriate
dilution. Samples were collected at established time intervals.
The influence of the following parameters on the efficiency of biosorbtion
process was considered: initial concentration of CR, fir tree sawdust quantity,
influence of stirring speed and working regime (with mobile and immobile phases).
All the experiments were repeated three times, the values presented
were calculated using averaged concentration values.
Biosorption process efficiency expressed as percentage was calculated
with equation (6):
C − Ct
(6)
E, (%) = 0
× 100
C0
where: E – efficiency (%);
C0 – CR initial concentration (mg/L);
Ct – CR time t concentration (mg/L).
Biosorption capacity was calculated using the equation (7):
(C − C t )
V
×
q= 0
1000
w
(7)
where: C0 – CR initial concentration (mg/L);
Ct – CR time t concentration (mg/L);
V – aqueous solution volume (mL);
m – biosorbent quantity (g).
Experimental data were used to determine the optimum working conditions
and to establish which kinetic model describes better the considered process.
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1. S. Chatterjee, L.S. Lee, M.W. Lee, S.H. Woo, Bioresource Technology, 2009,
100, 2803.
2. I.A.V. Tan, B.H. Hameed, A.L. Ahmad, Chemical Engineering Journal, 2007,
127, 111.
3. G. Mishra, M. Triphathy, Colourage, 1993, 40, 35.
4. W.J. Jr. Weber, Physiochemical Processes for Water Quality Control, 1972,
Wiley-Interscience, New York.
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CERASELLA INDOLEAN, SILVIA BURCĂ, ANDRADA MĂICĂNEANU, MARIA STANCA, DAN RĂDULESCU
5. R. Han, D. Ding, Y. Xu, W. Zou, Y. Li, L. Zou, J. Bioresource Technology, 2008,
99, 2938.
6. M.T. Uddin, M.A. Islam, S. Mahmud, M. Rukanuzzaman, Journal of Hazardous
Materials, 2009, 164, 53.
7. R. Ahmad, Journal of Hazardous Materials, 2009, 171, 767.
8. M.Ş. Tanyildizi, Chemical Engineering Journal, 2011, 168, 1234.
9. F.D. Ardejani, K. Badii, N.Y. Limaee, S.Z. Shafaei, A.R. Mirhabibi, Journal of
Hazardous Materials, 2008,151, 730.
10. K.V. Kumar, J. Dye Pig., 2007, 74, 595.
11. T.K. Sen, S. Afroze, H.M. Ang, Water Air Soil Pollution, 2011, 218, 499.
12. Z. Yao, L. Wang, J. Qi, Clean-Soil, Air, Water, 2009, 37(8), 642.
13. M.M. Abd El-Latif, A.M. Ibrahim, M.F. El-Kady, Journal of American Science,
2010, 6(6), 267.
14. M. Mohammad, S. Maitra, N. Ahmad, A. Bustam, T.K. Sen, B.K. Duta, Journal
of Hazardous Materials, 2010, 179, 363.
15. S. Dawood, T.K. Sen, Water research, 2012, 46, 1933.
16. Y. Djilali, E-H. Elandaloussi, A. Aziz, L.-C. de Menorval, Journal of Saudi Chemical
Society, 2012, http://dx.doi.org/10.1016/j.jscs.2012.10.013
17. M.A.K.M. Hanafiah, W.S.W. Ngah, S.H. Zolkafly, L.C. Teong, Z.A.A. Majid,
Journal of Environmental Sciences, 2012, 24, 261.
18. D. Politi, D. Sidiras, Procedia Engineering, 2012, 42, 1969.
19. V. Dulman, S.M. Cucu-Man, Journal of Hazardous Material, 2009, 162, 1457.
20. S.K. Papageorgiou, E.P. Kouvelos, E.P. Favvas, A.A. Sapalidis, G.E. Romanos,
F.K. Katsaros, Carbohydrates Research, 2010, 345, 469.
21. Y.H. Lin, H.F. Liang, C.K. Chung, M.C. Chen, H.W. Sung, Biomaterials, 2005,
26, 2105.
22. Y. Cheng, H.-Y Lin, Z. Chen, M. Megharaj, R. Naidu, Ecotoxicology and
Environmental Safety, 2012, 83,108.
23. Y.-S. Ho, Journal of Hazardous Materials, 2006, B136, 681.
24. J.E. Saiers, G.M. Hornberger, L. Liang, Water Resource Research, 1994, 30,
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25. M.A. McCoy, A.I. Liapis, Journal of Cromatography A, 1991, 548, 25.
26. S.V. Mohan, N.C. Rao, J. Karthikeyan, Journal of Hazardous Materials, 2002,
90, 189.
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30. S. Lagergren, Kungliga Svenska Vetenskapsakademien Handlingar, 1898, 24, 1.
31. Y.S. Ho, G. McKay, Process Biochemistry, 1999, 34, 451.
32. J. Febrianto, A.N. Kosasih, J. Sunarsao, Y. Ja, N. Indraswati, S. Ismadji, Journal of
Hazardous Materials, 2009, 162, 616.
33. F.N. Acar, Z. Eren, Journal of Hazardous Materials, 2006, 137, 909.
34. N. Rangsayatorn, P. Pokethitiyook, E.S. Upatham, G.R. Lanza, Environment
International, 2004, 30, 57.
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Hazardous Materials, 2009, 163, 555.
34
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 35 – 42)
(RECOMMENDED CITATION)
KINETIC STUDY OF CARROTS DRYING
ADINA GHIRIŞANa, SIMION DRĂGANa
ABSTRACT. The present study presents the drying of carrot slices as thinlayer of 4 mm thickness in a laboratory dryer with the drying air temperature in
the range of 40–60 0C. The effect of drying air temperature on the drying
kinetics, the drying rates, the effective diffusion coefficients and the activation
energy were determined. The effective diffusivity was found to be between
2.6·10-10 and 5.2·10-10 m2/s. The Newton, Page, modified Page and Henderson
& Pabis models available in the literature were fitted to the experimental data
using nonlinear regression analysis. The models were compared using the
coefficient of determination (R2). Henderson & Pabis model has shown a
better fit to the experimental drying data as compared to other two models.
Keywords: carrot, thin-layer drying, drying modeling, effective moisture
diffusivity.
INTRODUCTION
The drying operation is frequently used for agricultural products
preservation. It is also used for the substantial reduction in weight and
volume, minimizes packaging, storage and transportation costs [1].
The basic objective in drying agricultural products is the removal of
water or moisture from the surface and from the interior of material up to
certain level by evaporation. Thus, the operation involves simultaneous
transfer of heat to evaporate the liquid and mass transfer (moisture transfer) as
liquid or vapour within the solid and vapour from the surface, usually into a hot
carrier gas. The transfer of liquid inside the solid may occur by several
mechanisms, such as diffusion in homogeneous solids, capillary flow in
granular and porous solids, flow by shrinkage and pressure gradients, and flow
caused by a sequence of vaporisation and condensation [2].
a
Universitatea Babeş-Bolyai, Facultatea de Chimie şi Inginerie Chimică, Str. Kogălniceanu,
Nr. 1, RO-400084 Cluj-Napoca, Romania, ghirisan@chem.ubbcluj.ro
ADINA GHIRIŞAN, SIMION DRĂGAN
The evolution of drying can be characterised by the drying curve
and drying rate curve. The form of drying rate curve varies with the structure
and type of material. There are two typical drying curves: constant-rate drying
and falling-rate drying. Drying of fruits and vegetables occurs generally in
falling-rate period, the moisture transfer during drying being controlled by
internal diffusion [3].
The Fick’s second law of unsteady state diffusion (equation 1) was
used to calculate the effective moisture diffusivity, considering constant
moisture diffusivity, infinite slab geometry, and a uniform initial moisture
distribution as equation 2 [4]:
dM
= ∇(Deff ∇M )
dt
(1)
−
M − Me
MR =
= Ae
M0 − Me
π 2 D eff
4 L2
t
(2)
where: M is the moisture in kg water/kg dry material at time t, MR – the
moisture ratio, Deff – the effective moisture diffusivity in m2/s; L – the
thickness of the material layer (carrot slab), Me – the equilibrium moisture
content in kg water/kg dry material, and M0 – the initial moisture content in
kg water/kg dry material.
In the simplified form, as equilibrium moisture (Me) content has
negligible effect, the moisture ration becomes:
−
M
MR =
= Ae
M0
π 2 D eff
4 L2
t
(3)
The linear form of equation 3, obtained by plotting ln(MR) as a function
of time offers the possibility to reach the effective diffusivity from experimental
data.
The drying rate during experiments was calculated using the
following equation:
DR =
ΔM
A ⋅ Δt
(4)
The correlation between the variation of the moisture content and
time is a particular dependence for each material and drying conditions,
which can not be generalized, but can be experimentally determined.
The present study was undertaken to investigate the thin-layer
drying characteristics of carrot slices in a convective dryer and to fit the
experimental data to some mathematical models available in the literature.
Carrot was chosen as row material in our research because it is one
of the most common vegetables used natural or dried for human nutrition
due to the high vitamin and fibre content.
36
KINETIC STUDY OF CARROTS DRYING
RESULTS AND DISCUSSION
M (kg water/kg dry matter)
The initial moisture content of carrot slices was found to be 8.10 ±
0.05 (kg water/kg dry matter). The final moisture content of the carrot slices
varied with the experimental conditions from 0.25 ± 0.05 to 0.35 ± 0.03 (kg
water/kg dry matter).
The variations in the moisture content as a function of drying time at
various drying air temperatures and a constant velocity of 0.6 m/s are shown
(Figure 1). It can be seen that the moisture content decreases continually with
the drying time. The carrot slices of 4 mm will reach the final moisture content
within 870-450 min when the air temperature varied from 400C to 600C.
9.00
40 Celsius
8.00
50 Celsius
7.00
60 Celsius
6.00
5.00
4.00
3.00
2.00
1.00
0.00
0
200
400
600
800
1000
Drying time (min)
Figure 1. Effect of drying air temperature on moisture content for carrot slices.
Figure 2 show the drying rates, obtained by equation 4, as a function of
moisture content at various drying air temperatures.
5.00
Dry rate (kg water/kg dry
2
matter.m .min)
40 Celsius
4.00
50 Celsius
60 Celsius
3.00
2.00
1.00
0.00
0.000
2.000
4.000
6.000
8.000
10.000
M med (kg water/kg dry matter)
Figure 2. Effect of air temperature on drying rate.
37
ADINA GHIRIŞAN, SIMION DRĂGAN
The drying of carrot slices occur in the falling rate period, a continuously
decreasing of the drying rate with decreasing moisture content can be seen. In
the same time, the increase of drying rates is observed with the increase of
drying air temperatures. This means, at high temperatures the transfer of
heat and mass is higher and the water loss is more excessive. Similar
effects of air temperature are obtained in the drying of apple slices [5].
In order to determine the effective diffusivity the moisture content
was converted into the moisture ratio expression MR. The drying curves for
thin layer drying of carrots are shown in Figure 3.
1.2
40 Celsius
50 Celsius
60 Celsius
M R=M/M 0
1
0.8
0.6
0.4
0.2
0
0
200
400
600
800
1000
Drying time (min)
Figure 3. Variation of moisture ratio with the air temperature.
The transport of water during dehydration of carrot is described by
applying the Fick’s diffusion model. The effective diffusivity can be calculated
from the slope of the plot ln(MR) versus drying time (Fig. 4).
slope =
0.500
π 2 Deff
4L2
(5)
Drying time (s)
40 Celsius
0.000
ln(M R)
-0.500
0
20000
40000
60000
50 Celsius
y = -4E-05x + 0.0532
2
-1.000
R = 0.9982
60 Celsius
-1.500
-2.000
-2.500
y = -8E-05x + 0.0641
2
R = 0.988
y = -5E-05x + 0.0334
2
R = 0.9842
Figure 4. Determination of effective diffusivity coefficient (Deff).
38
KINETIC STUDY OF CARROTS DRYING
The values of effective diffusivity coefficient obtained by experimental
data are shown in Table 1. The values are comparable with those obtained in
literature [6]. The effective diffusion coefficient varied with the air temperature
from 2.6·10-10 at 400C to 5.2·10-10 m2/s at 600C, increasing as temperature
increase, which is accordance to the literature mentioned for drying processes
of agricultural products. The differences could be due to the differences of
drying conditions and drying equipments.
Table 1. Variation of diffusivity coefficient with temperature.
Temperature
(0C)
40
50
60
Deff (m2/s)·1010
1/T
2.60
3.245
5.20
0.0032
0.0031
0.0030
Effect of temperature on effective diffusivity is generally expressed
using an Arrhenius-type equation [1, 7]:
E
Deff = D0 exp − a
T⋅R
(6)
where: Ea is the activation energy of the moisture diffusion (kJ/mol), D0 –
the diffusivity value for a infinite moisture content, R- the universal gas
constant (kJ/mol·K, and T - the absolute drying air temperature (K).
A plot of ln(Deff) versus 1/T from equation (6) gives a straight line
with the slope of Ea/R (Fig. 5).
1/T
-21.2
ln Deff
0.0029 0.0030 0.0031 0.0032 0.0033
-21.4
-21.6
y = -3597.7x - 10.62
2
R = 0.9511
-21.8
-22
-22.2
Figure 5. Arrhenius-type representation for activation energy determination.
39
ADINA GHIRIŞAN, SIMION DRĂGAN
The obtained value of activation energy of the moisture diffusion
was 29.91 kJ/mol and the Arrhenius factor D0 was 2.44·10-5 m2/s, which are
comparable with the values found in literature [8].
The semi-theoretical models of Newton [3, 9], Page [3, 10] and
Henderson & Pabis [3, 10], widely used in thin-layer drying, are considered
in the present study to describe the drying behavior of carrots:
M R = exp(−kt)
n
M R = exp(−kt )
M R = a exp(−kt)
Newton
(7)
Page
(8)
Henderson & Pabis
(9)
where k is the drying constants, t – the drying time, a and n - the specific
drying coefficients.
From each model the drying constant k and the specific drying
coefficients determined considering the experimental data are shown in
Table 2. As it was expected, the drying coefficient k has increased with the
temperature of the drying air. In the same time the models coefficients are
affected by the change of air temperature.
Table 2. Drying constant k of model coefficients.
Temperature and
relative humidity of
drying air
40 (0C)
RH % = 17.5
Newton model
Page model
Henderson & Pabis
model
k = 0.1332 (h-1)
R2 = 0.995
50 (0C)
RH % = 11.3
k = 0.180 (h-1)
R2 = 0.983
60 (0C)
RH % = 8.7
k = 0.270 (h-1)
R2 = 0.983
k = 0.108 (h-1)
n = 1.1156
R2 = 0.999
k = 0.18 (h-1)
n = 1.188
R2 = 0.984
k = 0.252 (h-1)
n = 1.245
R2 = 0.983
k = 0.140 (h-1)
a = 1.056
R2 = 0.998
k = 0.184 (h-1)
a = 1.034
R2 = 0.984
k = 0.288 (h-1)
a = 1.063
R2 = 0.988
The models were compared considering the coefficient of determination
(R2) [3, 10]. The Henderson & Pabis model was selected as the best
mathematical model for describing the drying kinetics of the carrot slices in
our case.
40
KINETIC STUDY OF CARROTS DRYING
CONCLUSIONS
The experimental results have shown that the carrot slices of 4 mm
thick layer were dried between 870 and 450 min when the air temperature
was varied from 400C to 600C.
The moisture content and the drying rate were affected by the air
temperature.
The effective diffusion coefficient varied with the air temperature from
2.6·10-10 at 400C to 5.2·10-10 m2/s at 600C.
The obtained value of activation energy using Arrhenius type equation
was 29.91 kJ/mol and the Arrhenius factor D0 was 2.44·10-5 m2/s.
The Henderson & Pabis model was selected as the best mathematical
model for describing the drying kinetics of the carrot slices.
EXPERIMENTAL SECTION
Carrots were purchased from the local vegetable market, hand peeled
and washed in tap water. The carrots were then cut into slabs with a thickness
of 4 mm and putted into the dryer. The initial moisture content of carrot slices
of 89 % w. b. (wet basis) was determined drying the sample into a drying
stove 70 0C for 20 h.
The air was supplied by a centrifugal blower, heated to the required
temperature with an electrical wire placed inside the heating chamber and
connected with a variable transformer which can change the tension. The
temperature and the relative humidity in drying chamber were measured
with an HD2001.3 - Relative Humidity – Temperature Transmitter. The sample
tray with the carrot slices were put into the dryer on the pan of the balance.
The loss of each gram from the moisture was recorded as a function of time
in order to determine the drying behavior.
REFERENCES
1. I. Doymaz, O. Gorel, N. A. Akgun, Biosystems Engineering, 2004, 88(2), 213.
2. Geankoplis C.J., “Transport processes and unit operations”, Prentice-hall PTR,
Englewood Cliffs, New Jersey, 1993, chapter 9.
3. A. Kaya, O. Aydin, C. Demirtaş, Biosystems Engineering, 2007, 96(4), 517.
41
ADINA GHIRIŞAN, SIMION DRĂGAN
4. J. Crank, “Mathematics of Diffusion”, 2nd Edition, Oxford University Press,
London, 1975.
5. K. Sacilik, A.K. Elicin, Journal of Food Engineering, 2006, 73, 281.
6. J. Srikiatden, J.S. Roberts, Journal of Food Engineering, 2008, 84, 516.
7. M.C. Gely, S.A. Giner, Biosystems Engineering, 2007, 96(2), 213.
8. A. Mulet, Journal of Food Engineering, 1994, 22, 329.
9. S. Erenturk, M.S. Gulabloglu, S. Gultekin, Biosystems Engineering, 2004,
89(2), 159.
10. M. Aktaş, I. Ceylan, S. Yilmaz, Desalination, 2009, 239, 266.
42
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 43 – 52)
(RECOMMENDED CITATION)
THERMODYNAMIC STUDY OF HYDRANGEA ASPERA
CHLOROPHYLL CATABOLITES BY REVERSE PHASE
LIQUID CHROMATOGRAPHY
NINA DJAPICa
ABSTRACT. The Hydrangea aspera chlorophyll catabolites present in autumnal
leaves were investigated. The thermodynamic study of the Hydrangea aspera
chlorophyll catabolites was done using reversed phase liquid chromatography
on the C4 and C8 analytical columns with water (acidified):methanol mobile
phase in combination with ultraviolet detection and electrospray ionization
mass spectrometry identification. The retention behaviors of Hydrangea
aspera chlorophyll catabolites over a temperature range of 278-318 K were
investigated. The data obtained permitted the construction of the van’t Hoff
plots. The stationary phase composition influences the thermodynamic
retention of the Hydrangea aspera chlorophyll catabolites.
Keywords: Hydrangea aspera; chlorophyll catabolites; Liquid ChromatographyMass Spectrometry; van’t Hoff plot
INTRODUCTION
The chlorophyll catabolism consists of a great number of steps and, up
to know, chlorophyll catabolites that have a chromophore that can absorb
the ultraviolet-visible (UV-Vis) light are known. In the plant cell, every step is
coordinated, highly regulated and most steps are enzymatically catalyzed.
The chlorophyll catabolites found in Hydrangea aspera D. Don ssp. sargentiana
E. M. McClint autumnal leaves have been isolated from autumnal leaves of
Cercidiphyllum japonicum, Spinacia oleracea and Nicotiana rustica [1, 2, 3].
Reverse phase high pressure liquid chromatography (RP-HPLC) methods
have been used for the qualitative identification of the chlorophyll catabolites
[1]. The hyphenated techniques provided the information on the m/z of the
a
University of Novi Sad, Technical Faculty “Mihajlo Pupin”, Djure Djakovica bb, SRB-23000
Zrenjanin, Serbia, djapic@tfzr.uns.ac.rs
NINA DJAPIC
chlorophyll catabolites and allowed the structural determination of the chlorophyll
catabolites by their molecular mass [4]. The temperature plays an important
role in the chromatographic separation of the chlorophyll catabolites. The
temperature can influence the separation of compounds [5]. The role of
temperature in RP-HPLC and RP liquid chromatography (RP-LC) has been
used for the analysis of basic pharmaceuticals, water soluble vitamins,
small peptides, etc [6, 7, 8]. The retention behavior of the Hydrangea aspera
chlorophyll catabolites over the temperature range of 278K-318 K was
investigated in order to collect the data on the effects of the temperature on
the separation of the Hydrangea aspera chlorophyll catabolites on the C4 and
C8 reverse phase (RP) analytical columns. The capacity factor was calculated
for the chlorophyll catabolites present in autumnal leaves of Hydrangea aspera.
The enthalpy and entropy changes of the Hydrangea aspera chlorophyll
catabolites are reported.
RESULTS AND DISCUSSION
The Hydrangea aspera chlorophyll catabolites.
The LC – MS analysis of the Hydrangea aspera autumnal leaves
dichloromethane and ethyl acetate extracts were subjected on the RP – C4
and RP – C8 analytical columns under the same acquisition parameters and
elution solvent mixtures. The chromatograms obtained revealed the
presence of the chlorophyll catabolites depicted in Fig.1.
The Hydrangea aspera autumnal leaves dichloromethane extract
revealed the presence of nine chlorophyll catabolites when the separation
was done on the RP – C4 analytical column. The chlorophyll catabolite (4)
with the m/z 677, eluted at 48.2 min. at the 298 K, assigned as 2 in Fig.2.
Two isomers with the m/z 679, assigned 1 and 3 in the Fig.2, refers to the
structure 3 in the Fig.1. Two isomers with the m/z 805 refers to the structure 6
in the Fig. 1 and where assigned 4 and 8 in Fig. 2. Two most abundant
chlorophyll catabolites were with the m/z 807 (5) and were assigned in Fig.
2 with the numbers 5 and 6. The chlorophyll catabolites with the m/z 645
(1) and 643 (2) were also present and are assigned with the numbers 7 and
9 in the Fig. 2., respectively. The ESI-MS data of the chlorophyll catabolites
numerated 3 (3) 5 (5), 7 (1) and 9 (2) in the Fig. 2 is depicted in Fig. 4.
During the thermodynamical investigations chlorophyll catabolites
numeration refers to the numbers they were assigned in Fig. 2.
44
THERMODYNAMIC STUDY OF HYDRANGEA ASPERA CHLOROPHYLL CATABOLITES
OH
OH
OHC
OH
HO
NH
HN
N
HN
OHC
NH
HN
N
HN
NH
HN
NH
HN
MeO2C
O
COOH
MeO2C
1
m/z 645
OH
HO
O
O
O
O
5
m/z 807
OH
OHC
OH
HO
O
NH
N
OH
OH
COOH
3
m/z 679
COOH
O
O
O
MeO2C
OHC
OH
O
HO
O
OH
HN
OHC
O
O
HN
MeO2C
OHC
NH
HN
N
HN
NH
HN
NH
HN
O
MeO2C
COOH
2
m/z 643
OH
OH
MeO2C
COOH
4
m/z 677
O
COOH
O
6
m/z 805
Figure 1. Chlorophyll catabolites present in Hydrangea aspera autumnal leaves
dichloromethane and ethyl acetate extracts.
Figure 2. The chromatogram of Hydrangea aspera autumnal leaves’ dichloromethane
and ethyl acetate extract. The LC conditions: Column: Nucleosil 100-5 C4
4x250 mm. The mobile phase: 90% v/v water (0.1% TFA):methanol to 0%
v/v water (0.1%TFA):methanol in 90 minutes. Flow rate: 0.2 ml min-1. UV
detection at λ=312. The oven temperature was 298 K.
45
NINA DJAPIC
Figure 3. The chromatogram of Hydrangea aspera autumnal leaves’ dichloromethane
and ethyl acetate extract. The LC conditions: Column: Nucleosil 100-5 C8
4x250 mm. The mobile phase: 90% v/v water (0.1% TFA):methanol to 0%
v/v water (0.1%TFA):methanol in 90 minutes. Flow rate: 0.2 ml min-1. UV
detection at λ=312. The oven temperature was 298 K. The numeration of
chlorophyll catabolites is as in the Fig. 2.
Intens.
x10 7
679.3
0.8
0.6
0.4
0.2
0.0
250
500
750
Intens.
x10 7
807.3
1.5
1.0
0.5
0.0
250
500
750
Intens.
x10 7
645.2
1.5
1.0
0.5
0.0
250
500
Intens.
x10 6
750
643.3
2
1
242.3
0
250
347.2
500
750
Figure 4. The ESI-MS of the chlorophyll catabolites
numerated 3, 5, 7 and 9 in the Figure 2.
46
THERMODYNAMIC STUDY OF HYDRANGEA ASPERA CHLOROPHYLL CATABOLITES
The thermodynamic study on the separation of the Hydrangea
aspera chlorophyll catabolites on the RP – C4 and RP – C8 analytical
columns. In case, when the separation was done on the RP – C4 analytical
column, the capacity factor k’ showed a decrease, with a few exceptions at
the temperature of 298K (Table 1). The capacity factor k’ increases with the
temperature in the case of all the Hydrangea aspera chlorophyll catabolites
when the separation is done on the RP – C8 analytical column (Table 2).
Table 1. Capacity factor of Hydrangea aspera chlorophyll catabolites on the
RP-C4 analytical column at different temperatures
T [K]
278
288
298
308
318
k’ of the m/z 679 isomer-1
0.44
0.41
0.41
0.39
0.38
k’ of the m/z 677
0.45
0.42
0.43
0.41
0.40
k’ of the m/z 679 isomer-2
0.46
0.43
0.44
0.42
0.41
k’ of the m/z 805 isomer-1
0.47
0.44
0.45
0.43
0.42
k’ of the m/z 807 isomer-1
0.49
0.46
0.47
0.45
0.43
k’ of the m/z 807 isomer-2
0.51
0.49
0.50
0.48
0.47
k’ of the m/z 645
0.54
0.52
0.53
0.52
0.51
k’ of the m/z 805 isomer-2
0.55
0.53
0.54
0.53
0.52
k’ of the m/z 643
0.59
0.57
0.58
0.57
0.57
k’ – capacity factor.
Table 2. Capacity factor of Hydrangea aspera chlorophyll catabolites on the
RP-C8 analytical column at different temperatures
T [K]
278
288
298
308
318
k’ of the m/z 679 isomer-2
0.31
0.31
0.34
0.34
0.35
k’ of the m/z 805 isomer-1
0.31
0.31
0.34
0.34
0.36
k’ of the m/z 807 isomer-1
0.35
0.35
0.38
0.39
0.40
k’ of the m/z 807 isomer-2
0.37
0.38
0.41
0.41
0.43
k’ of the m/z 645
0.41
0.42
0.45
0.45
0.47
k’ of the m/z 805 isomer-2
0.42
0.43
0.46
0.46
0.48
k’ – capacity factor.
The representative graphs of the retention factor logarithm versus
the inverse temperature (van’t Hoff plots) are shown in Fig. 5 and 6.
47
NINA DJAPIC
log k'
0.6
9
0.55
0.5
8
7
6
0.45
5
4
0.4
0.35
0.003
3
2
1
0.0031
0.0032
0.0033
0.0034
0.0035
0.0036
0.0037
(1/T)[1/K]
Figure 5. The graphs of the retention factor vs. inverse temperature used to calculate
the change in molar enthalpy and entropy of the Hydrangea aspera
chlorophyll catabolites, the: m/z 679 isomer-1 (graph 1), m/z 677 (graph 2),
m/z 679 isomer-2 (graph 3), m/z 805 isomer-1 (graph 4), m/z 807 isomer-1
(graph 5), m/z 807 isomer-2 (graph 6), m/z 645 (graph 7), m/z 805 isomer2 (graph 8) and m/z 643 (graph 9) on the RP-C4 analytical column.
log k'
0.5
0.48
0.46
0.44
0.42
0.4
0.38
0.36
0.34
0.32
0.3
0.003
8
7
6
5
4
3
0.0031
0.0032
0.0033
0.0034
0.0035
0.0036
0.0037
1/T[1/K]
Figure 6. The graphs of the retention factor vs. inverse temperature used to calculate
the change in molar enthalpy and entropy of the Hydrangea aspera chlorophyll
catabolites, the: m/z 679 isomer-2 (graph 3), m/z 805 isomer-1 (graph 4), m/z
807 isomer-1 (graph 5), m/z 807 isomer-2 (graph 6), the m/z 645 (graph 7)
and the m/z 805 isomer-2 (graph 8) on the RP-C8 analytical column.
48
THERMODYNAMIC STUDY OF HYDRANGEA ASPERA CHLOROPHYLL CATABOLITES
The obtained graphs were approximated to be linear although the
square of the correlation coefficient were variable in case when the separation
was done on the RP-C4 analytical column, while when the separation was
done on the RP-C8, the square of the correlation coefficient were in the range
of R2=0.81 – 0.91 (Table 3 and 4). The linear graph would have indicated
that the change in molar enthalpy is constant and that there is no significant
change in retention mechanism over the temperature range of 278 – 318 K.
The slopes are negative for the separations on the RP – C8 analytical column
indicating a positive change in molar enthalpy suggesting that the transfer
from the mobile to the stationary phase is enthalpically unfavorable. The
changes in molar enthalpies were calculated from the slopes in Fig. 5 and 6,
according to the equation (2) and are depicted in Tables 3 and 4. The
phase ratio of the column (Φ) was assumed to be a constant.
Table 3. Capacity factor of Hydrangea aspera chlorophyll catabolites on the
RP-C4 analytical column at different temperatures
ΔH [J mol-1]
ΔS [J mol-1]
R2
k’ of the m/z 679 isomer-1
-2.02
0.97
0.91
k’ of the m/z 677
-1.60
2.69
0.81
k’ of the m/z 679 isomer-2
-1.60
2.88
0.81
k’ of the m/z 805 isomer-1
-1.60
3.07
0.81
k’ of the m/z 807 isomer-1
-1.89
2.45
0.84
k’ of the m/z 807 isomer-2
-1.33
4.88
0.84
k’ of the m/z 645
-0.87
7.11
0.68
k’ of the m/z 805 isomer-2
-0.87
7.30
0.68
k’ of the m/z 643
-0.58
9.07
0.49
ΔH – molar enthalpy, ΔS – molar entropy, R2 – the square of the correlation
coefficient.
49
NINA DJAPIC
Table 4. Capacity factor of Hydrangea aspera chlorophyll catabolites on the
RP-C8 analytical column at different temperatures
-1
ΔH [kJ mol ]
ΔS [J mol-1]
R2
k’ of the m/z 679 isomer-2
1.56
11.54
0.81
k’ of the m/z 805 isomer-1
1.85
12.55
0.85
k’ of the m/z 807 isomer-1
2.02
13.95
0.91
k’ of the m/z 807 isomer-2
2.11
14.75
0.87
k’ of the m/z 645
2.11
15.51
0.87
k’ of the m/z 805 isomer-2
2.11
15.70
0.87
ΔH – molar enthalpy, ΔS – molar entropy, R2 – the square of the correlation
coefficient.
When molar enthalpies are compared during the separation on the
RP – C4 analytical column there is an increase in molar entropy from the
first Hydrangea aspera chlorophyll catabolite, with the m/z 679 isomer-1 to
the last eluting Hydrangea aspera chlorophyll catabolite, with the m/z 643.
The only exception was the Hydrangea aspera chlorophyll catabolite, with
the m/z 807 isomer-1.
CONCLUSIONS
The extraction of Hydrangea aspera chlorophyll catabolites from the
autumnal leaves’ methanol extract with dichloromethane and ethyl acetate
differs slightly. The identification of Hydrangea aspera chlorophyll catabolites
on the RP –C4 column reveals the presence of nine chlorophyll catabolites,
while the separation on the RP –C8 reveals the presence of few less chlorophyll
catabolites. The thermodynamic investigations indicated that the retention
behaviour of Hydrangea aspera chlorophyll catabolites on RP – C4 and RP
– C8 analytical columns were slightly driven by the enthalpy difference. The van’t
Hoff curves obtained were approximated to be linear. When the investigations
were done on the RP – C4 the deviation from the linear approximation was
great in case of the Hydrangea aspera chlorophyll catabolites with the m/z 643.
The next investigations in reversed – phase liquid chromatography of chlorophyll
catabolites are desirable. The search for the optimal mobile phases, modifiers
and buffers is necessary in order to find the best separation conditions for
the separation of the chlorophyll catabolites.
50
THERMODYNAMIC STUDY OF HYDRANGEA ASPERA CHLOROPHYLL CATABOLITES
EXPERIMENTAL SECTION
Hydrangea aspera D. Don ssp. Sargentiana E. M. McClint autumnal
leaves (15g dry weight, 20g “fresh” weight) were chilled with liquid nitrogen,
grinded and homogenized in a blender with 0.2 dm3 methanol, at room
temperature, for 10 minutes. After centrifugation, the methanol extract was
filtered and partitioned between hexane and methanol. Water was added to
the methanol. The obtained volume was divided in two parts. From one part
Hydrangea aspera chlorophyll catabolites were extracted with dichloromethane
from the aqueous phase. Evaporation of dichloromethane (t<40oC) yielded
12.53 mg. From the other part Hydrangea aspera chlorophyll catabolites were
extracted with ethyl acetate from the aqueous phase. Evaporation of ethyl
acetate (t<40oC) yielded 10.84 mg. The extracts obtained were dissolved in
methanol and subjected to the LC-MS analysis. Methanol and water used
for the LC separation were HPLC grade (Acros Organics, Geel, Belgium)
and trifluoroacetic acid (TFA) was reagent grade (Fluka, Buch, Switzerland).
The LC/UV/ESI – MS analysis were performed on Waters 2695 Separations
Module (Milford, MA, USA) coupled to a Waters 2996 PDA UV-Vis detector
and connected to Bruker Daltonics esquire HCT (Bruker Daltonik, GmbH,
Bremen, Germany) equipped with an electrospray ionization (ESI) source.
Nitrogen produced by nitrogen generator (Domnick Hunter Group plc, Durham,
England) was used as nebulizer (20 psi) and drying gas (9 L min-1 at 3200C) in
ESI experiments. The ESI detection was done in positive mode. The capillary
voltage in a ramp ranged from 4.5 to 1.5 kV. Data were acquired by
HyStarTM and processed by Bruker Daltonics Data Analysis running under
Windows NTTM (Microsoft, Redmond, USA). The LC separations were carried
on the reverse phase (RP) EC 250x4 mm Nucleosil® 100-5 C8 column
together with RP CC 8x4 mm Nucleosil® 100-5 C8 precolumn and the RP
column with the stationary phase EC 250x4 mm Nucleosil® 120-5 C4 column
together with CC 8x4 mm Nucleosil® 120-5 C4 precolumn (Macherey-Nagel,
Oesingen, Switzerland). The injection volume was 10μL via autosampler
injection and in every sample 10 μL of uracil (0.01 mg mL-1) was dissolved.
For the thermodynamical investigations the temperature of the column oven
was in a range from 278 K to 318 K. The starting measurement was done
at oven temperature of 278 K with the subsequent increase of temperature
by 10 K. Mobile phase consisted of methanol and 0.1 % TFA in water. The
proportion of methanol was increased linearly from 10% to 100% in 80
minutes with a flow rate of 0.2 mL min-1. After each separation the column was
reequilibrated linearly from 100 % methanol to 90% water (0.1% TFA):10%
methanol in 10 minutes and additional 5 minutes at 90% water (0.1% TFA):10%
methanol. Data were acquired by HyStarTM and processed by Bruker Daltonics
Data Analysis running under Windows NTTM (Microsoft, Redmond, USA).
51
NINA DJAPIC
The following formulas were used for the calculation of the capacity
factor and the van’t Hoff isotherm [9].
The capacity factor (k’) was calculated with the equation (1):
k'=
tR − t0
t0
(1)
where the tR is the retention time of one of the Hydrangea aspera chlorophyll
catabolite and t0 is the retention time of the unretained compound (uracil).
The van’t Hoff equation [10]:
log k ' = (-
ΔH
ΔS
)+(
) + log Φ
2.3 RT
2.3R
(2)
where ΔH is enthalpy, ΔS is entropy, T is the absolute temperature, R is the
universal gas constant and the Φ is the phase ratio of the system. In the
van’t Hoff plot the log k’ versus 1/T is usually a linear curve with the slope of –
ΔH/2.3R and an intercept of ΔS/2.3R+log Φ. The value of Φ was assumed
to remain constant over the temperature range studied, so that the general
trends in ΔS could be analyzed [6].
The values obtained during the experimental measurements
represent the means of the triplicate measurements (n=3) ± SD.
RE F E R E N CE S
1. M. Oberhuber, J. Berghold, K. Breuker, S. Hoertensteiner, B. Kraeutler, Proceedings
of the National Academy of Sciences USA, 2003, 100, 6910.
2. M. Oberhuber, J. Berghold, W. Muehlecker, S. Hoertensteiner, B. Kraeutler, Helvetica
Chimica Acta, 2001, 84, 2615.
3. J. Berghold, C. Eichmueller, S. Hoertensteiner, B. Kraeutler, Chemistry & Biodiversity,
2004, 1, 657.
4. T. Mueller, S. Oradu, D. R. Ifa, R.G. Cooks, B. Kraeutler, Analytical Chemistry, 2011,
83, 5754.
5. C.B. Castells, P. W. Carr, Chromatographia, 2000, 52, 535.
6. R.J.M. Vervoort, E. Ruyter, A.J.J. Debets, H.A. Claessens, C.A. Cramers, G.J.
de Jong, Journal of Chromatography A, 2002, 964, 67.
7. V.A. Chirkin, S.I. Karpov, V.F. Selemenev, Russian Journal of Physical Chemistry A,
2012, 86, 1903.
8. C.-W. Tsai, C.-I. Liu, Y.-C. Chan, H.-H. Tsai, R.-C. Ruaan, Chromatographia, 2010,
114, 11620.
9. R.E. Ardrey, “Liquid chromatography – mass spectrometry: An Introduction”,
Wiley, England, 2003, chapter 2.
10. A. Tchapla, S. Heron, H. Colin, G. Guichon, Analytical Chemistry, 1988, 60, 1443.
52
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 53 – 59)
(RECOMMENDED CITATION)
CHARACTERIZATION OF BUFFALO MILK FAT GLOBULES
USING THE CONFOCAL LASER SCANNING MICROSCOPY
ALEXANDRA LǍPUŞANa*, FLAVIU TǍBǍRANa*, SORIN DANIEL DANa,
ROMOLICA MIHAIUb, CORNEL CǍTOIa, MARIAN MIHAIUa
ABSTRACT. Milk fat globules are biologically essential components due to
their functional and health properties. Milk fat composition has been thoroughly
studied in cow milk but still it remains unclear in buffalo milk. We have used
confocal laser scanning microscopy (CLSM) to investigate the structure of
the fat globules in cow and buffalo milk, using two types of fluorescentlylabelled dyes for phospholipid and triglyceride constituents. Using this
technique, we have observed heterogeneities in the distribution of these
lipids both in the membrane as on the surface relating to the specie and size
of the globules. The statistical analysis has shown that there are significant
differences (p<0.05) among the average fluorescence intensity (13.68±9.98
AU/µm2) found at buffalo milk fat globules in comparison to cow ones (16.88 ±
4.3 AU/µm2). The statistical comparison of the phospholipids quantification
values in both species revealed the fact that there are no significant
differences (p>0.05), the average found at cow milk being 31.07 AU/µm2
and at buffalo 34.85 AU/µm2. The use of specific dyes may be essential in
the evaluation of the unsaturated lipid milk fraction, the buffalo milk fat
globules being easily differentiated from cow milk by OilRed quantification.
Keywords: milk, buffalo, confocal laser scanning microscopy, fluorescence,
dye
INTRODUCTION
Milk fat globules play an essential role in the processing and
technology characteristics of dairy products, leading to different particularities
according to the specie. The size of these fat globules is essential in milk
a
University of Agricultural Sciences and Veterinary Medicine, Faculty of Veterinary Medicine, 3-5
Mănăştur street, 400372, Cluj-Napoca, Romania, email: lapusan_alexandra@yahoo.com
a* authors with equal contribution
b
Babes – Bolyai University, Faculty of Economics and Business Administration, Cluj-Napoca,
Romania
A. LǍPUŞAN, F. TǍBǍRAN, S. D. DAN, R. MIHAIU, C. CǍTOI, M. MIHAIU
separation, cheese technology and their further processing [1-3]. The protein
quantity absorbed per surface unit, the emulsion stability as well as their
optical, rheological (colour and viscosity) [4] and conductibility features [5] are
influenced by fat globules. On the other hand, the variation in size, distribution,
microstructure and rheological properties according to the animal species
[6,7] leads to the characteristic of each dairy product.
The distribution of the fat globules’ sizes was previously evaluated
using various methods such as classical microscopy, turbidity measurements,
and electronic impulses [8]. The classical microscopy was mainly used to
establish the quality damage degree of milk fat globules. Until now, the heat
treated milk or cream was investigated by using the classical [9], electronic
[10] and confocal microscopy [11,12,13]. Recently, Evers et al. (2008) [14]
have introduced the laser confocal microscopy method (CLSM) as a noninvasive technique for studying the cow fat globule’ membrane using lipophilic
and lectin colorants. Lopez et al. (2011) [15] has used a fluorescent staining for
phospholipids analogue with lectines in order to visualize their distribution in
the milk fat globule membrane. In Romania this is the first study performed
on buffalo milk that characterizes the biochemical aspects of fat globules
through confocal laser microscopy in comparison to cow milk.
RESULTS AND DISCUSSION
The unsaturated lipid fractions evaluation found in the fat globules
of buffalo and cow milk was performed by using the lipid fluorescent dye
OilRed.
The images presented in figure1 reveal the fluorescence emission
of the dispersed dye in the spherical areas of cow milk. The use of this dye
with affinity for unsaturated lipid fractions has confirmed the fact that in both
species these molecules are found exclusively in the fat globules. This is
not very surprising given the fact that the class they belong to, triglycerides,
are hydrophobic molecules. This method has allowed the making of 2D and
3D images of these fat globules.
The distribution of fat globules in cow milk was measured also,
varying from a 0.10 µm in diameter to 10 µm, with a final average of 4,33 µm.
The distribution was revealed in three peaks, corresponding to the diameters:
small sized (0,13 – 2,84 µm); average sized (3,5 – 7,87 µm) and large sized
globules (much lower in number) with values in between 8 and 10,2 µm.
The fat globules’ sizes evaluated in buffalo milk have varied considerably
in diameter, registering a minimal value of 0.45 µm and a maximal value of
18.2 µm. The average registered was of 9.41 µm. Our study has revealed a
higher value than the one found by El-Zeini (2006) [16] (8,7 µm).
54
CHARACTERIZATION OF BUFFALO MILK FAT GLOBULES USING THE CONFOCAL LASER
Figure 1. CLSM representing buffalo milk fat globules, colored with selective staining
for fats Oil Red (Obx63, Apocromat immersion); A - tridimensional
reconstruction; B – section analysis; C- fluorescence peak compared to
the minimal background fluorescence; D – 2,5 D triglyceride fluorescence
The use of OilRed dye for these lipid fractions has allowed the statistical
evaluation of fluorescence values measured in these stained fat globules and
the interpretation of their fluorescence degrees. Their distribution is structurally
and chemically heterogeneous in cow and also buffalo milk. Some of the results
at the triglycerides’ quantification from buffalo milk are shown in table 1.
55
A. LǍPUŞAN, F. TǍBǍRAN, S. D. DAN, R. MIHAIU, C. CǍTOI, M. MIHAIU
Table 1. Triglycerides’ fluorescence quantification in fat globules of buffalo milk
No.
Mean intensity
(AU/Arbitrary units)
1.
4,67
2.
3,4
3.
4,28
4.
2,14
5.
1,78
6.
2,18
7.
3,56
8.
2,85
9.
6,56
10.
50,72
11.
77,03
12.
8,17
13.
10,25
*SD – standard deviation
SD*
Pixels
Area
3,95
3,57
2,1
3,62
2,72
2,31
7,12
3,97
5,82
9,53
13,83
3,67
1,04
1188
331
251
502
483
461
335
326
491
861
343
494
208
82,53
23
17,44
34,88
33,56
32,03
23,27
22,65
34,11
59,82
23,83
34,32
14,45
As shown also in table 1, buffalo milk fat globules have revealed a
much lower intensity in the triglycerides’ fluorescence. The statistical analysis
has shown the fact that there are significant differences (p<0.05) among the
average fluorescence intensity found at buffalo milk fat globules in comparison
to cow ones. The average value of the fluorescence obtained in cow milk
samples was 16.88 ± 4.3 AU/µm2, with a minimum registered of 9.3 AU/µm2
and a maximum of 32.57 AU/µm2. In case of buffalo milk, the intensity was
lower revealing an average of 13.68±9.98 AU/µm2 with a minimum of 1.78
AU/μm2 and a maximum of 77.03 AU/ µm2. At the comparison of the fat
globules’ surface area, a significant difference (p<0.05) was noticed among
the two species. This time, the surface area was higher in the case of
buffalo milk (435,89 μm) and lower in the case of cow milk (182.98 μm).
These results are in accordance with other studies made on cow
milk fat globules evaluated through the same technique [17,14]. Although there
are innovative studies that characterize these fat globules lipid constituents,
there aren’t any that show a fully detailed comparison among different species.
The correlation found in this experiment show that the fat globules’ higher
degree of fluorescence (OilRed) in the unsaturated lipid fraction at cow milk
is due to the higher proportion of unsaturated fatty acids proved previously
in our studies [18]. Although at the statistical analysis of the percentages of
unsaturated fatty acids in cow milk compared to buffalo milk there were no
significant changes revealed, we proved that based on their fluorescence
degree quantification there are (p<0.05).
56
CHARACTERIZATION OF BUFFALO MILK FAT GLOBULES USING THE CONFOCAL LASER
Milk fat globules were stained also with Rhodamine, an exogenous dye.
This substance is a headgroup labelled phospholipid probe which can be
incorporated with minimal perturbation into the phospholipids layer of the
milk fat globule membrane.
We observed that the staining of the milk fat globule membrane was
heterogeneous. In figure 2 it is also shown that two phases coexist within
the buffalo milk fat globule membrane, a phase stained with rhodamine (reddish)
and a phase where rhodamine is absent (green) (Figure 2). This fact was
also observed in the case of cow milk fat globule, where the structure of the
membrane formed by phospholipids were revealed in a disorganized liquid
phase coexistent with the organized one. When comparing the intensities of
fluorescence at the two species it was revealed the fact that there were no
significant differences (p>0.05), the average found at cow milk being 31.07
AU/µm2 and at buffalo 34.85 AU/µm2. No matter the size of the fat globules,
the rhodamine fluorescence dependant on the phospholipids substrate
remains in the range at both species (28.05 – 36.9 AU/µm2 ).
Figure 2. CLSM representing buffalo milk fat globules, stained with selective staining
for triglycerides and phospholipids (Obx63, Apocromat immersion); A – plane
image; B – fluorescence intensity profile on axis 1; C- Graphical representation
of the fluorescence; Ch2 Rhodamine
57
A. LǍPUŞAN, F. TǍBǍRAN, S. D. DAN, R. MIHAIU, C. CǍTOI, M. MIHAIU
CONCLUSIONS
The use of specific dyes in the evaluation of the unsaturated lipid
fractions has revealed particularities at buffalo milk fat globules. The intensity
of tryglicerides’ fluorescence found in milk fat globule can be used as a
particular marker in assessing the specie. Given the fact that the intensity
of fluorescence is dependent on the amount of tryglicerides found in the fat
globules we can conclude that in buffalo milk the tryglicerides quantity is
lower than in cow milk. Regarding the phospholipids evaluation, the intensity of
the fluorescence was not statistically different, being able to affirm that buffalo
milk fat globules have similar phospholipids values as cow milk fat globules,
not being able to use this method for possible differentiations.
EXPERIMENTAL SECTION
The study was conducted on 84 samples of buffalo milk and 87 cow
milk samples, respectively. The samples were collected in sterile recipients
and kept at refrigerating temperatures until their further analysis. No samples
were kept longer than 6 hours until their analysis.
The confocal laser scanning microscopy analysis
The samples were analysed with the Confocal Laser Zeiss LSM 710
microscope, adjusted to an inversed microscope Acio Observer Z1. The specific
visualization of the emitted fluorescence by the complex lipid-Oil red O was
made by the laser exciting of the samples at a wave length of 596 nm and
the use of an absorption filter between 578 and 637 nm (wave length for
exciting/emission of the Texas Red fluorochrome). In order to visualize the
Rhodamine 123 fluorescence a fluorochrome excitation of 511 wave length
was used and the emission filters were in between 535-623. In order to visualize
the entire image spectrum a Zeiss Plan-Apochromat objective (63x/1.40) was
used. The images were processed and analysed by using the ZEN software,
standard version.
The calibration at the beginning of the experiment was made according
to the standard curve provided by the producers of the confocal system.
The quantification of the Oil Red and Rhodamine fluorescent signal
The quantitative assessment of triglycerides and phospholipid was performed
with the mentioned dyes: Oil Red and Rhodamine, using the previously
published protocol by Bhirde (2009) [19].
58
CHARACTERIZATION OF BUFFALO MILK FAT GLOBULES USING THE CONFOCAL LASER
RE F E R E N CE S
1. M.K. Rowney, M.W. Hickey, P. Roupas, D.W. Everett, Journal of Dairy Science,
2003,86, 712.
2. D.W. Everett and N.F. Olson, Journal of Dairy Science, 2003, 86, 755.
3. Y. Ma and D.M. Barbano, Journal of Dairy Science, 2000, 83, 1719.
4. P. Walstra, “Advanced Dairy Chemistry, Lipids”, Chapman & Hall, Inc., London,
1995, chapter 2.
5. M. Clausse, “Encyclopedia of Emulsion Technology”, Marcel Dekker, Inc., New
York, 1983, chapter 6.
6. M.A. Mehaia, Milchwessenschaft, 1995, 50, 260.
7. L.B. Abd El-Hamid and A.E. Khader, Journal of Dairy Science, 1982, 10, 43.
8. M.C Michalski, M. Ollivon, V. Briard, N. Leconte, C. Lopez, Chemistry and Physics
of Lipids, 2004, 132: 2, 247.
9. J. Hinrichs and H.G. Kessler, Cork Ireland: International Dairy Federation 1995, 9,
21.
10. W. Buchheim, G. Falk, A. Hinz, Food Microstructure, 1986, 5, 181.
11. L. Fang, The effect of milk fat globule membrane damage in the absence of air on
foulding in heat exchangers. MTech Thesis, Palmerston North: Massey University,
1998.
12. S. Herbert, B. Bouchet, A. Riaublanc, E. Dufour, D.J. Gallant, Lait, 1999, 79:6, 567.
13. J.M Evers, International Dairy Journal, 2004,14:8, 661.
14. J.M. Evers, R.G. Haverkamp, S.E. Holroyd, G.B. Jameson, D.D.S. Mackenzie,
O.J. McCarthy, International Dairy Journal, 2008,18, 1081.
15. C. Lopez and O. Ménard, Colloids and Surfaces B: Biointerfaces, 2011, 83:1, 29.
16. H.M. El-Zeini, Polish Journal Food Nutrition, 2006, 15/56:2, 147.
17. C. Lopez, B. Camier, J.Y. Gassi, International Dairy Journal, 2007,17, 235.
18. M. Mihaiu, A. Lǎpuşan, C. Bele, R. Mihaiu, S. D. Dan, Carmen Taulescu, C.
Matea, Roumanian Biotechnological Letters, 2011,16, 123.
19. A.A. Bhirde, V. Patel, J. Gavard, G. Zhang, A.A. Sousa, A. Masedunskas, R.D.
Leapman, R. Weigert, J.S. Gutkind, J.F. Rusling, ACS Nano, 2009, 3(2): 307.
59
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 61 – 69)
(RECOMMENDED CITATION)
SITE DIRECTED SPIN LABELING OF HEMERYTHRIN AND
HEMOGLOBIN
ISTVÁN MIHÁLY TAKÁCSa, AUGUSTIN MOTb,
RADU SILAGHI-DUMITRESCUb, GRIGORE DAMIANa*
ABSTRACT. Site directed spin labeling in combination with electron
paramagnetic resonance spectroscopy has become a very effective tool for
studying the dynamics and structure of biomolecules in their native
environment. This work presents the basics of site directed spin labeling
and provides our results obtained in spin labeling hemerythrin and hemoglobin
using methanethiosulfonate spin label. Best fit magnetic and libration
parameters are obtained by simulation of EPR spectra.
Keywords: site-directed spin labeling, EPR, proteins, nitroxides
INTRODUCTION
The concept of site-directed spin labeling (SDSL) in combination
with electron paramagnetic resonance (EPR) spectroscopy was developed by
Wayne L. Hubbell and coworkers [1, 2]. Often conventional spectroscopic
techniques are insufficient for studying structural properties of biomolecules,
and EPR spectroscopy has distinguished itself by offering the possibility of
studying the behavior of proteins in their native-like environment. The technique
is available for studying soluble biomolecules such as proteins and nucleic
acids, regardless of the size or complexity of the system [3, 4, 5, 6].
Although the majority of proteins are EPR-silent, SDSL and EPR can be used
together, often in conjunction with site directed mutagenesis for creating a
specific attachment point for the attachment of a nitroxide spin label, or, in
cases where multiple such points already exist, for selecting only one of
those for SDSL. Cysteine is a convenient aminoacid to use as target for SDSL,
as its thiol group will react with the functional groups of the spin label;
methanethiosulfonate, maleimide and iodoacetamide, creating a covalent bond.
a
“Babeş-Bolyai” University, Faculty of Physics, Str. Kogalniceanu, No. 1, RO-400084 ClujNapoca, Romania
*corresponding author: grigore.damian@phys.ubbcluj.ro
b
“Babeş-Bolyai” University, Faculty of Chemistry and Chemical Engineering, Str. Arany János,
No. 11, RO-400028, Cluj-Napoca, Romania
ISTVÁN MIHÁLY TAKÁCS, AUGUSTIN MOT, RADU SILAGHI-DUMITRESCU, GRIGORE DAMIAN
The nitroxide spin labels contain the nitroxyl radical (N-O) incorporated
in a heterocyclic ring and the unpaired electron localized mostly on the N-O
bond. Once attached to the protein their motion is dominated by their
environment and the proteins backbone motion. The nitroxide spin label is
influenced by his environment, surrounding structures and the motion of the
protein, which is reflected in the EPR spectra of the spin label [7, 8].
Among the long list of available spin labels the (1-oxyl-2,2,5,5tetramethylpyroline-3methyl) methanethiosulfonate spin label (MTSSL) [9]
is the most often used, because its small molecular volume and flexibility,
due to the link between the piperidine-oxyl group and the protein backbone,
minimizing the disturbance of protein folding. After labeling the attached side
chain is abbreviated as R1. Although their length, 5-8Å depending on the
conformation, MTSSL side chains don’t influence or disrupt the structural and
functional properties of the protein [10].
The free electron situated on the nitroxyl radical has a strong dipolar
interaction with the nitrogen nucleus, due to the nitrogen’s nuclear spin
state of I=1, the EPR spectral line shape will be formed by three lines each
arising from one of the three quantum states of the nitrogen nucleus. The
electron is also sensible to the anisotropic environment of the chemical bond.
These anisotropies of the surrounding interactions make the label sensitive
to its motion.
Continuous wave (cw) EPR spectroscopy of the spin labeled systems
gives information about side chain mobility, solvent accessibility, polarity of the
spin labels environment and distance between two paramagnetic centers [11].
Side chain mobility is a term used to describe the effect of motional
rate, anisotropy and reorientational motion of the spin label on the EPR
spectra [12]. At room temperature the EPR spectrum is particularly sensitive
to the reorientational motion of the side chain because of the partial motional
averaging of the anisotropic components of the g- and hyperfine tensors
[10, 13, 14]. When exposed to a motionally less restrictive environment (e.g.,
water), the nitroxide will gain a faster rotational correlation time, in the ns
range. In this case the three-peaked EPR spectra will look sharper, with a
small central line width (ΔH0) and small hyperfine splitting. In case of
mobility restriction of the spin label (e.g., due to higher viscosity solvents or
buried location of the side chain), the central line width and also the
hyperfine splitting will increase and the first and last peaks intensity will also
decrease [4, 15].
This paper reports the procedure and our results obtained in site
directed spin labeling of Phascolopsis gouldii (Peanut worm) hemerythrin
(Hr) and Bos Taurus (Bovine) hemoglobin (Hb).
62
SITE DIRECTED SPIN LABELING OF HEMERYTHRIN AND HEMOGLOBIN
RESULTS AND DISCUSSION
In Figure 1 the EPR spectrum of the MTS spin label free in water is
presented, where the spin label moves faster and has a fast rotational
correlation time of 0.79 ns. The second EPR spectrum represents also unbound
MTS spin label, but now in a more viscous environment - 85% glycerol in
water. The high viscosity of the glycerol determines the spin label to move
slower obtaining a rotational correlation time of 2.12 ns. The difference is
noticeable on the spectral lines, and the first and third peak have decreased in
the case of 85% glycerol, when the label became more immobile; also, the
central line width changes from ΔH0=1.17 G in water, to 2.05 G in the
glycerol/water mixture.
MTSSL - in water - 0.79ns
MTSSL - 85% Glycerol - 2.12ns
3300
3320
3340
3360
3380
3400
3420
Field / G
Figure 1. EPR spectra of MTSSL in water and glycerol-water solution.
Hemerythrin is a respiratory protein extracted from the blood of the
Peanut worm; the protein is responsible for the oxygen transport in the
organism by using a non-heme di-iron site [16, 17, 18]. Hr is a relatively large
protein with a homooctameric structure and 108 kDa mass. The subunits
are consistent of a four-helix bundle protein backbone, with 114 aminoacids.
Every subunit is identical and contains a native cysteine at the 51st position,
allowing one to spin label the protein at this selected site; Figure 2 illustrates
the position of this cysteine within the monomer.
63
ISTVÁN MIHÁLY TAKÁCS, AUGUSTIN MOT, RADU SILAGHI-DUMITRESCU, GRIGORE DAMIAN
Figure 2. Hemerythrin subunit A with native cysteine at the 51stposition (black)
For a next step the labeling protocol was also applied to bovine
hemoglobin. This type of hemoglobin is slightly different from the human
one, in that it has only native cysteine in the beta (β) subunit at the 92nd
position, the protein is composed from two alpha subunits and two beta
subunits, containing in total 2 cysteines available for labeling. After labeling
we abbreviated the sample Hb92R1. Figure 3 illustrates the beta subunit of
the Hb containing the native cysteine in blacked.
Figure 3. Representation of the Hb beta subunit with
native cysteine colored in black.
64
SITE DIRECTED SPIN LABELING OF HEMERYTHRIN AND HEMOGLOBIN
For a quantification of the successfully bonded spin label to the protein,
spin labeling efficiency, the EPR spectra of precisely prepared 100µM MTSSL
sample were recorded as control. The double integral area of the EPR
spectra of the MTSSL control sample can be used as a reference for the spin
quantity corresponding to 100 µM spin units. The concentration of the protein
was determined by UV-vis spectroscopy, via the absorption at 330 nm in
the case of the Hr and at 430 in case of Hb.
From the double integral area of the EPR spectra of the samples the
concentration of spins in the samples could then be determined – which,
reported to the protein concentration and taking into account the number of
cysteines available per monomer allows one to calculate the spin labeling
efficiency.
For the hemerythrin sample prepared without reducing with DTT the
labeling efficiency was 82%, whereas for the other sample, in which preparation
included the DTT reducing step, a 91% labeling efficiency was attained. The
nearly 10% difference observed by using DTT is a considerable advantage
and improvement to the procedure. In the case of the hemoglobin the obtained
spin labeling efficiency was 97%. Overall, these are very good yields. Indeed,
both of the proteins have their native cysteine in a location easily accessible
for the spin label; this is known to be one of the major influencing factor in
spin labeling.
Upon analysis of the EPR spectra, the g- and hyperfine tensor values
for the samples and the rotational correlation time of the spin label along
with the component fraction were calculated. Using the simulation software
for nitroxide spin labels Multicomponent EPR 495 developed by Christian
Altenbach, we simulated the EPR spectra of the Hr with 3 components. The
idea in a simulation is to use the minimum number of components possible
in a simulation and obtain the best result. In the case of the Hb the simulation
was done with 2 components.
Table 1. Best fit simulation parameters for spin labeled hemerythrin EPR spectra
Comp Fraction (%) Axx
(G)
Ayy
(G)
Azz
gxx
gyy
gzz
Corr.
Time ns
(G)
I
68.34
7.35
7.65
33.02
2.0087
2.0067
2.0032
4.26
II
22.57
8.25
8.55
32.05
2.0085
2.0065
2.0045
3.5
III
9.09
8.55
8.85
31.56
2.0085
2.0065
2.0041
1.16
65
ISTVÁN MIHÁLY TAKÁCS, AUGUSTIN MOT, RADU SILAGHI-DUMITRESCU, GRIGORE DAMIAN
A possible practical explanation for the three Hr components would
be that the largest fraction represents the Hr octameric structure, the
smallest fraction would represent the monomeric state of the protein and
the third component would represent a multimeric structure of the protein.
As seen in Table 1 the small fractioned component is the fastest one;
the explanation that this component represents the monomeric state in the
protein fits perfectly, because of the large possible mobility of the spin label
on the single subunit, due to his outer side position on the helix of the
subunit. This mobility is limited when we talk about the octameric form since in
that case the spin label is not at the surface anymore - it is between two
subunits, and this fact is observed also in the rotational correlation time.
Table 2 contains the data obtained from simulations on the hemoglobin
spectra. The mobility of this protein is quite different from the Hr; the protein
is tighter, smaller and more restrictive for the spin label movement as the
Hr. In this case the label is not pointing towards the outside as in the case
of the Hr subunits, but is rather trapped inside the beta unit; this explains
the slower rotational correlation times.
Table 2. Best fit simulation parameters for spin labeled hemoglobin EPR spectra
Comp Fraction (%) Axx
Ayy
Azz
(G)
(G)
(G)
gxx
gyy
gzz
Corr.
Time ns
I
21.21
9.83
10.13
33.68
2.0070
2.0050
2.0039
3
II
78.79
5.9
6.2
34.76
2.0080
2.0060
2.0022
4.73
By looking at the spectra of the two proteins on the Figure 4 one can
clearly see the differences in the shape. The simulation data shows that the Hr
is more mobile, and this is noticeable in the EPR spectra as well, with the first
peak more intense and sharp. In the Hb spectra, this component is shifted to
the left and has less sharpness and intensity. In the case of Hb, due to the
tightness of the system, the label is not as mobile as in the case of the Hr, this
is reflected in the spectra as well as in the correlation times.
66
SITE DIRECTED SPIN LABELING OF HEMERYTHRIN AND HEMOGLOBIN
Hr51R1
Hb92R1
3300
3320
3340
3360
3380
3400
3420
Field / G
Figure 4. EPR spectra of the spin labeled hemerythrin (top)
and spin labeled Hemoglobin (bottom).
CONCLUSIONS
By analysis of EPR spectra of nitroxide radical motion within a
labelled protein one can obtain the main dynamic parameters of protein
domains and characterizes protein conformation and any changes that may
occur in different environments, too. Proof of concept data are shown here
for hemerythrin for the first time, in comparison with the more often-studied
hemoglobin.
EXPERIMENTAL SECTION
The EPR measurements were carried out on a Bruker EMX EPR
spectrometer with continuous wave at X-band (9 GHz), equipped with a
Bruker liquid nitrogen temperature controller. The spectra were recorded at
room temperature with a microwave frequency of 9.45 GHz, microwave
power of 4 mW, modulation frequency of 100 kHz, modulation amplitude of 1
G and microwave attenuation of 17 dB. The samples were measured in quartz
capillary tubes containing 15 µL of sample.
The MTS spin label was inquired from Enzo Life Sciences and was
dissolved in DMSO (100 mM, stock solution).
67
ISTVÁN MIHÁLY TAKÁCS, AUGUSTIN MOT, RADU SILAGHI-DUMITRESCU, GRIGORE DAMIAN
Simulation of the EPR spectra of labelled proteins, was performed
by Multi-Component EPR Fitting v2 version 495 program, a LabVIEW
software, developed by Dr. Christian Altenbach (University of California, Los
Angeles, California, https://sites.google.com/site/altenbach/labview-programs/eprprograms/multicomponent)
For the purpose of spin labeling, Phascolopsis gouldii Hr, purified as
previously described [19], was first suspended in PBS buffer and a final
concentration of 10 mM DTT was added to the solution. The mixture was
incubated and constantly shaken at 4oC for 2 hours. To obtain a good spin
labeling efficiency, by preventing the reduction of the disulfide bridge between
the cysteine and the side chain, the DTT was removed by washing from the
system using a 10kDa Millipore filter in a Beckman J21B centrifuge. The sample
was centrifuged 6 times at 4oC, 5000 rpm for 30 minutes. After each step
the flow-trough was checked by UV-vis spectroscopy for traces of DTT.
After the complete removal of DTT from the system the MTSSL spin label
was introduced into the sample with a 10 times excess to each monomer. A
second sample of Hr was also prepared, where the DTT part was altogether
omitted, on the grounds that Hr does not contain disulfide bonds – and the
role of DTT in principle would be precisely to cleave disulfide bonds in order
to liberate the thiols for labeling. The two samples were incubated overnight
at 4oC.
The next step was to remove the unbound excess spin label from
the sample and to determine the efficiency of the spin labeling. The two
samples were washed out of the excess spin label by using 10 kDa
Millipore filters and were centrifuged at 5000 rpm and 4oC for 5 times. After
each step of washing the flow-trough was checked for remnant spin labels
by EPR spectroscopy. After the 4th step the flow-through EPR spectra showed
no traces of spin label. This was done to both of the samples in the same
conditions. The obtained sample after labeling is abbreviated as Hr51R1, 51
representing the 51st position of the subunit where the spin label is bound
and R1 is the name of the side chain after labeling, as mentioned before.
ACKNOWLEDGMENTS
IMT acknowledges the financial support of the Sectorial Operational
Programme for Human Resources Development 2007-2013, co-financed
by the European Social Fund, under the project number POSDRU/107/
1.5/S/76841 with the title „Modern Doctoral Studies: Internationalization and
Interdisciplinarity”.
68
SITE DIRECTED SPIN LABELING OF HEMERYTHRIN AND HEMOGLOBIN
RE F E R E N CE S
1. C. Altenbach, S.L. Flitsch, H.G. Khorana, W.L. Hubbell, Biochemistry, 1989,
28:7806-7812.
2. C. Altenbach, T. Marti, H.G. Khorana, W.L. Hubbell, Science, 1990, 248:10881092.
3. E. Bordignon, H-J.Steinhoff, Membrane protein structure and dynamics studied
by site-directed spin labelling ESR. In: M.A. Hemminga, L.J. Berliner (eds) ESR
spectroscopy in membrane biophysics, 2007, Springer Science and Business
Media, New York, pp 129-164.
4. W.L. Hubbell, H.S. Mchaourab, C. Altenbach, M.A. Lietzow, Structure, 1996,
4:779-783.
5. W.L. Hubbell, A. Gross, R. Langen, M.A. Lietzow, Curr. Opin. Struct. Biol. 1998,
8:649-656.
6. C.S. Klug, J.B. Feix, Methods and applications of site-directed spin labelling
EPR spectroscopy, In: J.J. Correia, H.W. Detrich (eds), Methods in cell biology.
Biophysical tools for biologists, Volume one: in vitro techniques, 2008, New
York, Academic Press, pp 617-658.
7. S.Cavalu, G.Damian, Biomacromolecules, 2003, 4(6);1630-1635.
8. S.Cavalu, G.Damian, M.Dansoreanu, Biophysical Chemistry, 2002, 99(2):181-188.
9. L.J. Berliner, J. Grunwald, H.O. Hankovszky, K. Hideg, Anal. Biochem. 1982,
119:450-455.
10. J.P.Klare, H-J. Steinhoff, Spin labelling EPR, Photosynth. Res., 2009, Volume
102, 2-3:377-390.
11. G.F. White, L. Ottingnon, T. Georgiu, C. Kleanthous, G.R. Moore, A.J. Thomson,
V.S. Oganesyan, Journal of magnetic Resonance, 2007, 185:191-203.
12. L.J. Berliner, Spin labeling: theory and applications, 1976, Academic Press,
New York.
13. L.J. Berliner, Spin labeling II: theory and applications, 1979, Academic Press,
New York.
14. L.J. Berliner, J. Reuben, Spin labeling theory and applications, 1989, Plenum
Press, New York.
15. H.S. Mchaourab, M.A. Lietzow, K. Hideg, W.L. Hubbell, Biochemistry, 1996,
35:7692-7704.
16. C.S. Farmer, D.M. Kurtz Jr, R.S. Phillips, J. Ai, J. Sanders-loeher, J. Biol. Chem.,
2000, 275:17043-17050.
17. S. Jin, D.M. Kurtz Jr, Z.J. Liu, J. Rose, B.C. Wang, J. Am. Chem. Soc., 2002,
124:9845-9855.
18. S.V. Kryatov, E.V. Rybak-Akimova, S. Schindler, Chem. Rev. 2005, 105:21752226.
19. A.C. Mot, A. Roman, I. Lupan, D.M. Kurtz Jr, R. Silaghi-Dumitrescu, , Protein J,
2010, 29:387-393.
69
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 71 – 86)
(RECOMMENDED CITATION)
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS
WITH A GIVEN MATCHING NUMBER
KEXIANG XUa*, KINKAR CH. DASb, HONGBO HUAc,
MIRCEA V. DIUDEAd
ABSTRACT. The Harary index is defined as the sum of reciprocals of distances
between all the vertex pairs of a connected graph. In this paper we present
upper bounds on Harary index of unicyclic graphs with a given matching
number and characterize the extremal graphs for which the upper bounds
on Harary index are attained.
Key Words: Graph, Reciprocal distance, Harary Index, upper bound
INTRODUCTION
The Harary index of a graph, denoted by H(G), has been introduced
in 1993, independently by Ivanciuc et al.[1] and by Plavšić et al.[2] Even
earlier, the QSAR group in Timisoara, Romania, particularly Ciubotariu [3],
have used this index to express the decay of interactions between atoms in
molecules as the distances between them increased. It has been so named
in the honor of Professor Frank Harary, on the occasion of his 70th birthday.
The Harary index is defined as
H (G ) =
1
u , v∈V ( G ) d G (u , v )
where the summation runs over all unordered pairs of vertices of the graph
G and d G (u , v) denotes the topological distance between any two vertices
u and v of G (i.e., the number of edges in a shortest path connecting u and v).
Mathematical properties and applications of H are reported in refs. [4-14].
a
College of Science, Nanjing University of Aeronautics & Astronautics, Nanjing, China
* xukexiang1211@gmail.com (K. Xu)
b
Department of Mathematics, Sungyunkwan University, Suwon 440-746, Republic of Korea
c
Faculty of Mathematics and Physics, Huaiyin Institute of Technology,Huai'an, Jiangsu, China
d
Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, Cluj, 400084, Romania
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
Chemical applications of this index, in correlating with thermodynamic
properties or octane number of alkanes, or in discriminating alkane isomers,
are presented in refs. [5,15-18]. Some new interesting properties of other
distance-based graph invariants can be seen in refs. [19-21].
Let γ (G, k ) be the number of vertex pairs of G lying to each other at
the distance k. Then, from refs.[8,12] we have:
1
H (G ) = γ (G, k ).
k ≥1 k
(1)
All graphs herein considered are finite and simple ones. Let G = (V;E)
be a graph with the vertex set V (G) and edge set E(G). A connected graph
G is called a unicyclic graph if V (G ) = E (G ) . Two edges e1 and e2 are called
independent if they do not have a common vertex. A matching of G is a
subset of E(G) with some pairwise independent edges. For a graph G, the
matching number β (G ) is the maximum cardinality among the independent
sets of edges in G. For a matching M of a graph G, if a vertex v ∈ V (G ) is
incident to an edge of M, then v is said M-saturated. For a graph G, D(G)
denotes the diameter of G, or the maximum topological distance between
any two vertices in G. In the following, we denote by Pn , Cn and S n the path
graph, the cycle graph and the star graph with n vertices, respectively. For
other notations and terminology in the Graph Theory, the readers may
consult refs. [22,23].
Let
(n, m) be the set of connected unicyclic graphs, of order n and
having the matching number m. Recently, Ilić et al. [24] have determined
the tree with the maximal Harary index among all the trees of order n and
having the matching number m. Du and Zhou [25] determined the extremal
graph of
(n, m) with the minimal Wiener index. Inspired by the above
results, the graphs of
(n, m) , having the maximal Harary index and their
characterization, will be presented in the following.
SOME LEMMAS
As preliminaries, let us introduce some basic lemmas. For a graph G, with
v ∈ V (G ) , one defines [12]
QG (v) =
72
d G (u, v)
.
u∈V ( G ) d G (u , v ) + 1
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
For convenience, we will write QG (v ) as QV ( G ) (v) . Note that the
function f ( x) =
x
is strictly increasing for x > 1 .
x +1
Let U n , m be a unicyclic graph obtained by attaching n − 2m + 1 pendent
edges and m − 2 pendent paths, of length 2, to one vertex of the triangle
C3 , as shown in Figure 1. By equality (1), we can obtain
1 n − m + 1
1
1 m − 2
H (U n , m ) = n + [
− 1 + m − 2] + [( n − 2m + 3)( m − 2) + ( m − 2)( m − 3)] +
2
2
3
4 2
= n+
=
1 ( n − m )2 + n + m − 6 1
1 m − 2
+ ( n − m )( m − 2) +
2
2
3
4 2
1
(6n2 − 4mn + m 2 + 14n + 7 m − 18).
24
(*)
For a vertex v of G, the eccentricity ecc(v) is defined as the maximum
distance from v to any other vertex in G.
Lemma 2.1. Let G be a connected graph of order n > 4, with a
pendent vertex v adjacent to the vertex u, and let w be a neighbor of u
different from v. Then
H (G ) − H (G − v) ≤
n 1 1
+ + d G (v )
3 6 6
(2)
with the equality holding if and only if ecc(u) = 2. Moreover, if d G (u ) = 2 , then
H (G ) − H (G − {u, v}) ≤
7n 1 1
+ + dG ( w)
12 2 4
(3)
with the equality holding if and only if ecc(w) = 2.
73
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
Proof. Considering that v is a pendent vertex of G, we have
H (G ) − H (G − v) = n − 1 − QG − v (u )
1
2
≤ n − 1 − [ (d G (u ) − 1) + (n − 1 − d G (u ))]
2
3
n 1 1
= + + d G (u )
3 6 6
with the equality holding if and only if ecc(u) = 2.
When d G (u ) = 2 , we have
H (G ) − H (G − {u , v}) = H (G ) − H (G − v) + H (G − v) − H (G − {u , v})
= n − 1 − QG − v (u ) + n − 2 − QG −{u , v} ( w)
1 2
3
≤ n − 1 − [ + (d G ( w) − 1) + (n − 2 − d G ( w))]
2 3
4
1
2
+ n − 2 − [ (d G ( w) − 1) + (n − 2 − d G ( w))]
2
3
7n 1 1
=
+ + d G ( w)
12 2 4
with the equality holding if and only if ecc(w) = 2.
Lemma 2.2. [26] Let G ∈
(2m, m) ,
m ≥ 3 and T be a branch of G
with the root r. If u ∈ V (T ) is a pendent vertex closest to the root r, with
d G (u , r ) ≥ 2 ¸ then u is adjacent to a vertex of degree two.
Lemma 2.3. [27] Let G ∈
(n, m) , with n > 2m and G ≠ C
n
. Then,
there is a maximum matching M and a pendent vertex v of G such that v is
not M-saturated.
74
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
Lemma 2.4. [10,13] Let A, X and Y be three connected graphs with
disjoint vertex sets. Suppose that u, v are two vertices of A, v0 is a vertex of X
and u0 is a vertex of Y . Let G be the graph obtained from A, X and Y by
identifying v with v0 and u with u0 , respectively. Let G1* be the graph obtained
from A, X and Y by identifying three vertices v, v0 and u0 , and let G2* be the
graph obtained from A, X and Y by identifying three vertices u, v0 and u0
(Figure 2). Then we have:
H (G1* ) > H (G ) or H (G2* ) > H (G ).
From Lemma 2.4, the following corollary is immediate.
Corollary 2.1. Let G be a connected graph with u , v ∈ V (G ) . Denote
by G(s;t) the graph obtained by attaching s > 1 pendent vertices to vertex u
and t > 1 pendent vertices to vertex v. Then, we have
H (G (1, s + t − 1)) > H (G ) or H (G ( s + t − 1,1)) > H (G ).
Lemma 2.5. [13] Let G be a (connected) graph with a cut vertex w
such that G1 and G2 are two connected subgraphs of G having w as the only
common vertex and G1 ∪ G2 = G . Let V (Gi ) = ni for i = 1,2 . Then
H (G ) = H (G1 ) + H (G2 ) +
1
.
u∈V ( G1 ) \{ w}v∈V ( G 2 ) \{ w} d G1 (u , w) + d G 2 ( w, v )
Let Ck (1n − k ) be a graph obtained by attaching n − k pendent edges to
a vertex of Ck . Based on equality (1), we can claim that H (Ck (11 )) > H (Ck +1 ) ,
for k ≥ 5 . Denote by Ck* (n − k − 1,1) a unicyclic graph obtained by attaching
one pendent vertex and n − k − 1 pendent vertices, respectively, to two
adjacent vertices of a cycle Ck .
Lemma 2.6. Let k ≥ 5 and Ck* (n − k − 1,1) be a unicyclic graph
defined as above. Then
H (Ck* (n − k − 1,1)) > H (Ck*+1 (n − k − 2,1)).
Proof. To prove this lemma, we first prove that
H (Ck (1n − k )) > H (Ck +1 (1n − k − 2 )) .
Note that Ck (1n − k ) is obtained by identifying the unique vertex of degree 3 in
Ck (11 ) with the center of star S n − k −1 , where the new vertex is labeled as w1
75
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
and Ck +1 (1n − k − 2 ) is obtained by identifying one vertex Ck +1 with the center
of
the
star
S n − k −1 , where the new vertex is labeled as
w2 .
Set A = H (Ck (1n − k )) − H (Ck +1 (1n − k − 2 )) . So, by Lemma 2.5, we have
H (Ck (1n − k −1 )) = H (Sn − k −1 ) + H (Ck (11 )) + (n − k − 2)
1
v∈V ( Ck (11 )) \{w1 }
H (Ck +1 (1n − k − 2 )) = H ( S n − k −1 ) + H (Ck +1 ) + (n − k − 2)
1 + dC
k
1
v∈V ( C k +1 ) \{ w2 }
,
(w1, v)
(1 )
1
1 + dC k +1 ( w2 , v)
.
Thus, considering that H (Ck (11 )) > H (Ck +1 ) , for k ≥ 5 , from above we get
1
A > (n − k − 2)(
v∈V ( C k (11 )) \{ w1 }
1
= (n − k − 2)( −
2
1 + dC
k
( w1 , v)
(1 )
−
1
v∈V ( C k +1 ) \{ w2 }
1
1 + d C k +1 ( w2 , v)
)
1
)>0
k
1+
2
as expected.
Assume that the unique vertex of degree 3 in Ck* (n − k − 1,1) is u1
and the unique vertex of degree 3 in Ck*+1 (n − k − 2,1) is u2 . Suppose that
V (Ck (1n − k −1 )) = V (Ck* (n − k − 1,1)) \ {v1} and
V (Ck (1n − k −1 )) = V (Ck* (n − k − 1,1)) \ {v1} , where v1 is adjacent to u1 in
Ck* (n − k − 1,1) and v2 is adjacent to u2 in Ck*+1 (n − k − 2,1) . Let
B = H (Ck* (n − k − 1,1)) − H (Ck*+1 (n − k − 2,1)) . Similarly, by Lemma 2.5, we
arrive at
H (Ck* (n − k − 1,1)) = 1 + H (Ck (1n − k −1 )) +
1
v∈V ( C k (1n − k −1 )) \{u1 }
H (Ck*+1 (n − k − 2,1)) = 1 + H (Ck +1 (1n − k − 2 )) +
n −k −2
v∈V ( C k +1 (1
1 + dC
k
(1
n − k −1
(u1 , v)
)
,
1
)) \{u 2 } 1 + dC
n − k −2
k +1 (1
(u2 , v)
)
.
From above, we get
B>
v∈V ( C k (1n − k −1 )) \{u1 }
1
1 + dC
k
(1n − k −1 )
(u1 , v)
−
v∈V ( C k +1 (1n − k − 2 )) \{u 2 }
as H (Ck +1 (1n − k − 2 )) > H (Ck +1 (1n − k − 2 ))
76
1
1 + dC
k +1 (1
n−k −2
) \{u 2 }
(u2 , v)
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
=
1
−
3
1
> 0 , thus ending the proof of this lemma.
k
1+
2
MAIN RESULTS
In this section, the graph of
(n, m) , with the maximal Harary index,
will be determined. Before presenting the main results, we first will deal with
some special cases of this problem.
When n = 3, there is only one unicyclic graph, which is just the triangle
C_3, with the matching number 1. There is nothing to prove, in this case.
(n,1) . Next, we only need to consider the set
Clearly, only C3 belongs to
(n, m) , with
n ≥ 4 and m ≥ 2 . If n = 4, there are exactly two unicyclic
graphs, C4 and C3 (11 ) , which belong to
(4,2) , with
H (C4 ) = H (C3 (11 )) .
When n = 5, we can easily check that (see ref.[11]) only two graphs Cn and
C3 (12 ) have the maximal Harary index in
the unique graph C3 (1n − 3
(5,2) . From ref. [17] we find that
) has the maximal Harary index in (n,2) , with n ≥ 6 .
Now we consider the case n = 6. Two graphs, G6(1) and G6( 2 ) are
shown in Fig. 2. It is not difficult to check that there are only five graphs:
U 6,3 , C5 (11 ) , G6(1) , G6( 2 ) and C6 , in (6,3) , and
1
1
1
× 7 + × 2 = 10
6
3
2
> H (U 6,3 ) = H (C6 ) = H (G6(1) ) = H (G6( 2 ) )
H (C5 (11 )) = 6 +
=6+
1
1
× 6 + × 3 = 10.
3
2
Thus C5 (11 ) has the maximal Harary index in
we assume that n ≥ 7 and m ≥ 3 .
(6,3) . In the following
77
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
Let
(1)
(m) be the set of graphs from
vertex whose neighbor is of degree two. Also, let
(6,3)
( 2)
having a pendent
( m) = ( m) \
(1)
( m) .
Denote by C5 (1,1,1) the graph obtained by attaching three pendent vertices
to three consecutive vertices in C5 .
Lemma 3.1. Let G ∈
( 2)
(m) , with m ≥ 4 . Then, we have
1
(17m 2 + 35m − 18)
24
with the equality holding if and only if G ≅ C5 (1,1,1) .
H (G ) ≤
Proof. If G ≅ C5 (1,1,1) , the equality holds immediately. So it suffices
to prove that
1
(17m 2 + 35m − 18) , when G ≠ C5 (1,1,1) .
24
For any graph G ∈ ( 2 ) (m) \ {C5 (1,1,1)} , by Lemma 2.2, we find that
H (G ) <
G is the cycle C2 m or a graph obtained by attaching some pendent vertices
to some vertices of Ck with m ≤ k ≤ 2m − 1 . Combining the structure of
U n , m with n = 2m and formula (*), we can easily find
17 m 2 + 35m − 18
1 m 2 + 3m − 6 1
1 m − 2
= 2m +
+ m(m − 2) +
24
2
2
3
4 2
Moreover, for m ≥ 4 ,
m 2 + 3m − 6
γ (C2 m ,2) = 2m <
, γ (C2 m ,3) = 2m < m(m − 2) and
2
γ (C2 m ,4) ≥ m , , γ (C2 m , m) = m .
Therefore, from (1), we have H (C2 m ) <
17 m 2 + 35m − 18
.
24
Now, let us consider the case when G is a graph obtained by
attaching some pendent vertices to some vertices of Ck , with m ≤ k ≤ 2m − 1 .
To prove this lemma, we need to look at the following three cases.
Case 1: k = m. In this case, we can easily find that G is a graph
obtained by attaching
78
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
a pendent vertex to each vertex of Cm . If m = 4, we can easily check that
H (G ) < H (C5 (1,11)). When m ≥ 5 , we have γ (G,2) = 3m <
m 2 + 3m − 6
,
2
γ (G,3) = 3m + γ (Cm ,3) ≤ m(m − 2) , γ (G,4) = m + 2γ (Cm ,4),,
m
m
m
γ (G, + 2) = γ (Cm , ) = > 1.
2
2 2
Therefore, according to (1), we have H (G ) <
17 m 2 + 35m − 18
.
24
Case 2. m + 1 ≤ k ≤ 2m − 2 . For this case, by Corollary 2.1, we
claim that any graph G of this type can be changed into a
graph Ck (n − k − 1,1) = Ck (1, n − k − 1).
Considering the equality (1), H (Ck (2m − k − 1,1)) reaches its maximum
value when the two vertices of degrees 3 and 2m − k + 1 are adjacent. We
denote by Ck* the type of graph with the maximal Harary index. When m = 4,
since G ≠ C5 (1,1,1) , we have G ≅ C6* . A simple calculation shows that
97 197
<
= H (C5 (1,1,1)) . In the following, we assume that m ≥ 5 .
6
12
By Lemma 2.6, we claim that the maximum value of H (Ck* ) is attained at k
H (C6* ) =
= m + 1. Moreover,
m − 2
2
γ (Cm* +1 ,2) = m + 1 + 2(m − 1) +
(m − 2)(m − 3)
2
2
m + 3m − 6
≤
,
2
γ (Cm* +1 ,3) = γ (Cm +1 ,3) + 2(m − 1) + (m − 2)
= 3m − 1 +
3m − 1 if m = 5
=
4m − 3 if m ≥ 6
< m 2 − 2m,
m + 1
D(Cm* +1 ) =
+ 1 ≥ 4.
2
79
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
Combining the above arguments with the equality (1), we have
17 m 2 + 35m − 18
.
24
Case 3. k = 2m − 1 . In this case, we claim that G ≅ C2 m −1 (11 ) . If m = 4,
197
it is easy to see that H (C7 (11 )) = 16 <
= H (C5 (1,1,1)) . For k ≥ 5 , we
12
m 2 + 3m − 6
,
can find that γ (C2 m −1 (11 ), 2) = 2m + 1 <
2
γ (C2 m −1 (11 ),3) = 2m + 1 < m(m − 2) and D (C2 m −1 (11 )) = m ≥ 5 .
H (G ) < H (Cm* +1 ) <
Similarly to the above two cases, we have H (C2 m −1 (11 )) <
17 m 2 + 35m − 18
.
24
Thus we completed the proof of this lemma.
Lemma 3.2. Let G ∈
d G (v ) ≤ m + 1 .
(2m, m)
and v be any vertex in V (G). Then
Proof. There exists a graph G ∈
(2m, m) with a vertex v ∈V (G) ,
of degree s ≥ m + 2 . Assume that v1 , v2 , , vs are all the neighbors of v in G.
Now there are 2m − s ≤ m − 2 edges remained in G ∈
(2m, m) .
Therefore, β (G ) ≤ m − 2 + 1 = m − 1 . This is a contradiction to the fact
(2m, m) , thus proving this lemma.
197
, with the equality
Lemma 3.3. Let G ∈ (8, 4) . Then H (G ) ≤
12
that G ∈
holding if G ≅ U 8,4 or G ≅ C5 (1,1,1) .
197
with
12
the equality holding if and only if G = C5(1; 1; 1). If G ∈ (1) (4) , with a
Proof. If G ∈
(2)
(4) , by Lemma 3.1, we have H (G ) ≤
pendent vertex v ∈ V (G ) and u as the neighbor of v, of degree two, then
G − {u , v} ∈ (6,3) . By Lemmas 2.1 and 3.2, we have
31 1
+ dG ( w)
6 4
31 5
≤ H (G − {u , v}) + +
6 4
H (G ) ≤ H (G − {u , v}) +
80
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
with the equality holding if and only if ecc(w) = 2 and dG ( w) = 5 .
Considering the structures of U 6,3 , C5 (11 ) , G6(1) , G6( 2 ) and C6 (there
is only U 6,3 with the maximum degree 4), we claim that the above equality
holds if and only if G ≅ U 8,4 . The lemma follows immediately.
In the following, we give a lemma as a starting point for our main
(10,5) , with the maximum Harary
results. In this lemma, the graph of
index, will be completely characterized.
Lemma 3.4. Let G ∈
(10,5) .
Then, H (G ) ≤
97
with the equality
4
holding if and only if G ≅ U10,5 .
Proof. By Lemma 3.1, we have H (G ) ≤
97
if G ∈ (2) (5) . For any
4
graph
G ∈ (1) (5) , from Lemmas 2.1, 3.2 and 3.3, we have
38 1
+ dG ( w)
6 4
197 38 3 97
≤
+ + =
12
6 2 4
with the equality holding if and only G − {u , v} ≅ U 8,4 or G ≅ C5 (1,1,1) , ecc(w)
H (G ) ≤ H (G − {u , v}) +
= 2 and d G ( w) = 6 , that is, G ≅ U10,5 .
Theorem 3.1. Let G ∈
(2m, m) with m ≥ 5 . Then we have
17 m 2 + 35m − 18
24
with the equality holding in (4) if and only if G ≅ U 2 m , m .
H (G ) <
(4)
Proof. We prove this theorem by induction on m. For m = 5, from
Lemma 3.4, this lemma follows immediately.
Assume that the result is true for any graphs in
(2m − 2, m − 1) , with
m ≥ 6.
81
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
17 m 2 + 35m − 18
. If
If G ∈ (m) , then by Lemma 3.1, we have H (G ) <
24
G ∈ (1) (m) , with a pendent vertex v ∈ V (G ) and u as the neighbor of v,
(2)
of degree two, we can conclude that G − {u , v} ∈
(2m − 2, m − 1) .
By
Lemma 2.1 and the induction hypothesis, it follows that
7m + 3 1
+ dG ( w)
6
4
2
17(m − 1) + 35(m − 1) − 18 7 m + 3 m + 1 17m 2 + 35m − 18
≤
+
+
=
24
6
4
24
with the equalities holding if and only if G − {u , v} ≅ U 2 m − 2,m −1 , ecc(w) = 2 and
H (G ) ≤ H (G − {u , v}) +
d G ( w) = m + 1 ; thus, G is just U 2 m ,m and the theorem is completely proved.
Theorem 3.2. Let G ∈
n
(n, m) with 3 ≤ m ≤ 2 and n ≥ 7 .
Then we have
6n 2 − 4mn + m 2 + 14n + 7 m − 18
(5)
24
with the equality holding in (5) if and only if G ≅ U 7,3 or C5 (12 ) for
H (G ) <
(n, m) = (7,3) ; G ≅ U 8,4 or C5 (1,1,1) for (n, m) = (8, 4) ; G ≅ U n , m otherwise.
Proof. First we define a function
6n 2 − 4mn + m 2 + 14n + 7 m − 18
,
24
where n, m are all positive integers. In view of formula (*) we obtain
1 ( n − m) 2 + n + m − 6 1
1 m − 2
+ (n − m)(m − 2) +
f ( n, m ) = n +
.
2
2
3
4 2
For the cycle Cn , we have n = 2m + 1 or n = 2m . Based on equality
f ( n, m ) =
(1), using a procedure as that followed in the proof of Lemma 3.1, we can
get H (Cn ) < f (n, m).
For any graph G ∈
( n, m ) ,
with n > 2m different from Cn , by
Lemma 2.3, there must be a pendent vertex v of G and a maximum matching
M such that v is not M-saturated in G. Clearly, G − v ∈ (n − 1, m) . Let u be
the unique neighbor of v in G. As proved in ref. [25] d G (u ) ≤ n − m + 1 .
82
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
Now we prove this result by induction on n. According to the value
of m, we divide the discussion into the following three cases.
Case 1: m = 3. For n = 7, G − v ∈
(6,3) . If
G − v ≅ C5 (11 ) , we
have d G (u ) ≤ 4 . Then, by Lemma 2.1, it follows that
5 1
61 5 2 40
+ d G (u ) ≤ + + =
2 6
6 2 3 3
with the equalities holding if and only if d G (u ) = 4 and ecc(u) = 2, that is,
H (G ) ≤ H (C5 (11 )) +
G ≅ C5 (12 ) . If G − v ≠ C5 (11 ) , by Lemma 2.1, we have
5 1
5 5 40
H (G ) ≤ H (G − v) + + dG (u ) ≤ 10 + + =
2 6
2 6 3
with the equalities holding if and only if G ≅ U 6,3 , C6 , G6(1) , or G6( 2 ) (Fig. 2),
d G (u ) = 5 and ecc(u) = 2, which implies G ≅ U 7 ,3 . Thus, we claim that
40
. When G ∈ (n, m) , with (n, m) = (7,3) , the equality is holding
3
if and only if G ≅ C5 (12 ) ; or U 7 ,3 .
H (G ) ≤
When n = 8, we get G − v ∈
(7,3) . By Lemma 2.1,
17 1
40 17
+ dG (u ) ≤
+ + 1 = f (8,3)
6 6
3
6
with the equalities holding if and only if G − v ≅ U 7 ,3 , d G (u ) = 6 and ecc(u) = 2,
H (G ) ≤ H (G − v) +
i.e., G ≅ U 8,3 . Assume that the result holds for all graph G ∈
with n ≥ 9 . By Lemma 2.1 and induction hypothesis, we have
(n − 1,3)
2n + 1 1
2n + 1 n − 2
+ dG (u ) ≤ f (n − 1, m) +
+
= f (n,3)
6
6
6
6
with the equalities holding if and only if G − v ≅ U n −1,3 , d G (u ) = n − 2 and
H (G ) ≤ H (G − v) +
ecc(u) = 2, equivalently, G ≅ U n ,3 .
Case 2: m = 4. For n = 8, the result follows from Lemma 3.3. In case
n = 9 , G − v ∈ (8,4) . Based on Lemma 2.1, by analogy to the Case 1, we
have H (G ) ≤
197 19
+ + 1 = f (9,4)
12
6
83
KEXIANG XU, KINKAR CH. DAS, HONGBO HUA, MIRCEA V. DIUDEA
with the equality holding if and only if G ≅ U 9, 4 . Suppose that the result
holds for any graph G − v ∈
(n − 1,4) , with
n ≥ 10 ; from Lemma 2.1 and
induction hypothesis, we have
2n + 1 n − 3
2n + 1 1
+ dG (u ) ≤ f (n − 1,4) +
+
= f (n,4)
6
6
6
6
with the equalities holding if and only if G − v ≅ U n −1, 4 , d G (u ) = n − 3 and
H (G ) ≤ H (G − v) +
ecc(u) = 2, equivalently, G ≅ U n, 4 .
Case 3: m ≥ 5 . When n = 2m , the result holds from Lemma 3.4.
Assume the result is true for any graph G ∈ (n − 1,4) with ≥ 2m . By a
similar procedure, we obtain
H (G ) ≤ H (G − v) +
2n + 1 1
2n + 1 n − m + 1
+ d G (u ) ≤ f (n − 1,4) +
+
= f (n, m)
6
6
6
6
with the equalities holding if and only if
G − v ≅ U n −1, m , d G (u ) = n − m + 1
and ecc(u) = 2, that is, G ≅ U n , m . Thus, the proof of this theorem is completed.
The cyclomatic number η of G is defined as η (G ) = E (G ) − V (G )
+ ω (G ) , where ω (G ) is the number of connected components of G. Denote
by G (n,η , m) the set of connected graphs of order n and by m the
matching number. Clearly, when η = 0 , G (n,η , m) denotes the set of trees
of order n, of the matching number m; if η = 1 , then G ( n,η , m) = (n, m) .
Considering the main results in this paper (for η = 1 ) and those in ref. [24]
(for η = 0 ), we naturally ask the following problem:
Problem 3.1. Can we determine the graph of G (n,η , m) with the
maximal Harary index being an integer η ≥ 2 ?
Even more difficult is to determine the graph of G (n,η , m) with the
minimal Harary index, even for the caseη = 0 . Therefore, we will end this
paper with the following interesting problem:
Problem 3.2. Which graph of G (n,η , m) has the minimal Harary
index for a given integer η ≥ 0 ?
84
MAXIMAL HARARY INDEX OF UNICYCLIC GRAPHS WITH A GIVEN MATCHING NUMBER
ACKNOWLEDGEMENT
K. X. is supported by NUAA Research Funding, No. NN2012080 and
NNSF of China (No. 11201227). K. Ch. D. and H. H. acknowledge, respectively,
for the support of Sungkyunkwan University BK21 Project, BK21 Math
Modeling HRD Div. Sungkyunkwan University, Suwon, Republic of Korea
and Qing Lan Project of Jiangsu Province, PR China.
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14. B. Zhou, X. Cai, and N. Trinajstić, J. Math. Chem. 2008, 44, 611.
15. M.V. Diudea, MATCH Commun. Math. Comput. Chem. 1995, 32, 85.
16. M.V. Diudea and C. M. Pop, Indian J. Chem. 1996, 35A, 257.
17. M.V. Diudea, O. Ivanciuc, S. Nikolić, and N. Trinajstić, MATCH Commun. Math.
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20. M.H. Khalifeh, H. Yousefi-Azari, and A.R. Ashrafi, Comput. Math. Appl. 2008, 56,
1402.
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22. J.A. Bondy and U.S.R. Murty, Graph Theory with Applications, Macillan Press,
New York, 1976.
23. M.V. Diudea, I. Gutman, and L. Jäntschi, Molecular Topology, NOVA, New
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24. A. Ilić, G. Yu, and L. Feng, Utilitas Math., in press.
25. Z. Du and B. Zhou, MATCH Commun. Math. Comput. Chem. 2010, 63, 101.
26. A. Chang and F. Tian, Lin. Algebra Appl. 2003, 370, 237.
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86
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 87 – 92)
(RECOMMENDED CITATION)
FAST GC-MS METHOD FOR QUANTIFICATION OF GAMMABUTYROLACTONE IN BIOLOGICAL MATRICES
ANIKÓ PÉTERa, TÍMEA DERGEZa, IBOLYA KISSb, FERENC KILÁRa,b
ABSTRACT. A sensitive and specific gas chromatography-mass spectrometry
analysis using selective ion monitoring for the quantification of γ-butyrolactone
in biological matrices was developed. The method includes a simple liquidliquid extraction and no derivatization procedure before the GC-MS analysis. An
internal standard, α-methylene-γ-butyrolactone was applied for the quantitative
determination. The method was linear between 0.34 µg/ml (LOD) and 500
µg/ml. The limit of quantification (LOQ) was obtained to be 0.798 µg/ml using
100 µl blood, urine or plasma.
Keywords: gamma-butyrolactone, gamma-hydroxybutyric acid, GC-MS,
blood, urine, plasma
INTRODUCTION
Gamma-butyrolactone (γ-butyrolactone, GBL) is the chemical precursor
of gamma-hydroxybutiric acid (γ-hydroxybutiric acid, GHB). Both are components
of the normal mammalian metabolism, as endogenous constituents of the
mammalian brain and they have been hypothesized to have a role as
neurotransmitters [1]. Gamma-hydroxybutiric acid has been gaining popularity
amongst club-goers as a recreational drug [2] . It is a component of “date
rape drugs”, due to its euphoric effects [3] and ability to reduce inhibitions [4]
or as doping agent (enhancer of muscle growth) [5]. Gamma-butyrolactone,
on the other hand, has a hypothetical effect in the fungal metabolism, in
filamentous fungi as a signalling molecule [6]. GBL has therapeutic importance,
because of its pharmacokinetic and anti-angiogenic activity. Several quantitative
analytical methods have been developed for measuring GHB and/or GBL in
biological matrices [7-10]. Most of the papers report methods with gas
chromatography-mass spectrometry, high performance liquid chromatography
a
b
Institute of Bioanalysis, University of Pécs, Faculty of Medicine, University of Pécs, Szigeti
út. 12, H-7624 Pécs, Hungary, ferenc.kilar@aok.pte.hu
Department of Analytical and Environmental Chemistry, Faculty of Science, University of
Pécs, Ifjúság útja 6., H-7624 Pécs, Hungary
ANIKÓ PÉTER, TÍMEA DERGEZ, IBOLYA KISS, FERENC KILÁR
or capillary electrophoresis procedures. The physiological level of gammahydroxybutiric acid is approximately 2 µg/ml in blood, and the normal endogenous
concentration in urine is typically less than 10 µg/ml [11, 12]. Studies on the
serum level of γ-butyrolactone, however, could not demonstrate its normal
presence in significant amount, presumably due to its rapid conversion to γbutyrolactone by γ-lactonase [13]. The determination of GHB was possible in
the form of GBL after its acidic conversion [14]. The expected concentration
of GBL in culture media of fungi is between 50-300 µg/ml [15, 16].
The aim of this study was to develop a rapid and simple method, for
the quantitative determination of γ-butyrolactone in culture media of fungi,
which will be applicable for the investigation of GBL in human blood and urine,
as well. No method has previously been published for the determination of
gamma-butyrolactone in culture medium.
RESULTS AND DISCUSSION
The gas-chromatography-mass-spectrometry analysis of γ-butyrolactone
extracted by organic solvents from different biological matrices was studied. For
the quantification of GBL an internal standard, α-methylene-γ-butyrolactone (MGBL) was applied. Five solvents, chloroform, cyclohexane, dichloromethane,
ethyl-acetate and methyl tert-butyl ether were examined in the extraction
procedure. Care was taken to find the most suitable conditions for concentrating
the extracts. A typical chromatogram of the two components after an extraction
procedure with methyl tert-butyl ether (MTBE) using single ion monitoring is
presented in Figure 1. The base peak of GBL at 42 m/z, and the base peak of
M-GBL at 68 m/z can be clearly differentiated in the chromatogram, and besides
these a fragment of GBL at 68 m/z can also be detected. The suggested
fragmentation structure for the 42 m/z fragment is [O=C=CH2]+., while the MGBL looses one carbon, one oxygen, and two hydrogens to form the 68 m/z
fragment, it means most likely the elimination of CH2=O neutral molecule.
The quantification of γ-butyrolactone was obtained by using a calibration.
The calibration curve for the standard was linear in the 0.34 - 500 µg/ml
concentration range. Each correlation coefficient for three independent calibrations
was R=0.999. The recovery experiments were carried out with a 500 µg/ml
GBL concentration in blood, urine, or fungal culture. Cyclohexane and ethylacetate provided a recovery of γ-butyrolactone less than 20 % and 45 %,
respectively. Although, the extraction with dichloromethane and chloroform
resulted in a recovery higher than 90 %, due to the background noise, the
LOD was higher than 200 µg/ml. The best recovery (95 %) was obtained
with extraction using MTBE. The limit of quantitation was found to be 0.798
µg/ml (RSD: 20 %), and the limit of detection was obtained to be 0.34 µg/ml
(RSD: 33 %).
88
FAST GC-MS METHOD FOR QUANTIFICATION OF GAMMA-BUTYROLACTONE IN BIOLOGICAL MATRICES
Abundance
110000
Ion 42.00 (41.70 to 42.70)
Ion 68.00 (67.70 to 68.70)
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4
Time (min)
Figure 1. GC-MS chromatogram of a sample containing γ-butyrolactone and
α-methylene-γ-butyrolactone. Single ion monitoring (SIM) detection of two
fragment ions, 42 m/z (solid line) and 68 m/z (dashed line) was applied. The
culture medium spiked with γ-butyrolactone (500 µg/ml) and α-methylene-γbutyrolactone (500 µg/ml) was extracted with methyl tert-butyl ether. Other
experimental conditions are given in the Experimental session.
The within-batch precision, using culture medium in the extraction,
was between 1.1 to 3.9 %, the between-batch precision was between 1.7 to
7.3 % (experiments with three replicates). In the case of plasma, the withinbatch precision was 4.9-8.1 %; in the case of blood cell suspension 10.1-13.4 %;
and using urine the precision was between 0.8-5 %. The limit of detection was
0.34 µg/ml in culture medium and urine, and 0.5 µg/ml in blood. The limit of
quantitation was 0.798 µg/ml in culture medium and urine, and 1.6 µg/ml in
blood. The ratio of γ-butyrolactone present in the plasma and blood cells
after centrifugation was ca. 45/55.
It was not possible to detect γ-butyrolactone in blank plasma or in
blood cell suspension, which is in accordance to previous results, showing
that the concentration of GBL in blank plasma is about 0.1 µg/ml [17].
89
ANIKÓ PÉTER, TÍMEA DERGEZ, IBOLYA KISS, FERENC KILÁR
The most efficient extraction was obtained with methyl tert-butyl
ether (a low-boiling point solvent), but valid result could be obtained only
after satisfactory sample preparation and within 40 min after sampling. The
pretreatment procedure has been investigated with different solvents mainly
with chloroform [7], but solid-phase extraction methods were also developed
for the extraction of GBL [12]. Some publications applies salting-out approach
[18], but those techniques are more complicated compared to the one
described here.
CONCLUSIONS
The analytical gas-chromatography-mass-spectrometry method developed
in this study is sensitive, accurate and precise for the determination of γbutyrolactone, which participates in signal processes of fungi [15], but possibly
occurent in human blood and urine. Only a simple pretreatment of the sample
is necessary. The method provides a low LOD for the determination, although,
applying special analytical conditions and instrumentation results with lower
LOD values can be found in the literature [19]. In the case of following drug
administration in human material a cautious interpretation of the data is
necessary to avoid false positive results, therefore, it is mandatory to collect
blood with EDTA, because the drug is cleared from the blood within 6 h [20].
EXPERIMENTAL SECTION
Reagents
Gamma-butyrolactone (GBL) and α-methylene-γ-butyrolactone (MGBL) were purchased from Sigma-Aldrich (Darmstadt, Germany). Chloroform,
cyclohexane, dichloromethane, ethyl-acetate and methyl tert-butyl ether
(MTBE) were of GC grade. Stock solutions of GBL (10 mg/ml) were prepared
in the organic solvents; M-GBL (10 mg/ml) was dissolved in MTBE. The Difco
Potato Dextrose Broth (Difco Laboratories, Le Pont de Claix, France) was
used (24 mg/ml) as culture medium. Drug-free human urine and blood were
collected from healthy individuals. The blood samples were taken in EDTA
tubes, and the biological samples were stored at 4°C.
Extraction
Extraction of GBL was made from aqueous solution, culture medium and
from biological matrices containing different amounts of gamma-butyrolactone
and 500 µg/ml α-methylene-gamma-butyrolactone, as internal standard. The
concentration of GBL in the different solutions were as follows: aqueous
solutions: 10 µg/ml or 50 µg/ml GBL; culture medium: 0, 0.4, 0.8, 1, 2.5, 5, 50,
100 and 500 µg/ml; blood or urine: 0, 0.5, 1, 2, 5, 10, 20 and 50 µg/ml.
90
FAST GC-MS METHOD FOR QUANTIFICATION OF GAMMA-BUTYROLACTONE IN BIOLOGICAL MATRICES
The extraction procedure of the biological samples was preceded with a
purification step, the samples in the culture medium were filtered through a
Whatman Syringe Filter (0.45 µm), the urine was filtered with Millipore-Millex
filter (0.45 µm), and the blood plasma was separated from the blood cells by
centrifugation (3000 rpm, 30 min). The extraction was made applying 100 µl
samples and 1 ml organic solvents (chloroform, cyclohexane, dichloromethane,
ethyl-acetate or methyl tert-butyl ether). A suspension of the blood cells (100 µl)
was also used for extraction. After vortexing (1 min. two times) and
centrifugation (3000 rpm, 10 min) the organic part was collected and evaporated
to ca. 100 µl final volume.
Gas chromatography-mass spectrometry
Gas chromatography-mass spectrometry (GC-MS) analyses were
performed on an Agilent 6890N GC equipped with a 5975 Inert Mass Selective
detector (Agilent Technologies, Waldbronn, Germany). A HP-1 column (25
m x 0.2 mm I.D., 0.33 µm film thickness of polydimethylsiloxane) (Agilent
Technologies, Waldbronn, Germany) was used for the separations applying
helium as carrier gas at a flow rate of 1.5 ml/min. An HP 7683B automatic
sampler was used for the injection. Split injection (20:1) was used with the
valve closed for 2.7 min, and 1 µl samples being injected. The operating
conditions for the analyses were: inlet temperature 250°C; the detector
temperature 300°C; initial oven temperature was 50°C with a hold time of 0.6
minute and with a temperature ramp of 15°C min-1 up to 300°C. The mass
spectrometer was operated in the selective ion monitoring (SIM) mode,
monitoring GBL and M-GBL (the internal standard) by the 42 m/z and 68
m/z major fragment ions, respectively.
Method validation
The extraction was tested with γ-butyrolactone spiked distilled water
(100 µg/ml). A calibration curve was constructed by preparing solutions in MTBE
containing 0.5, 2.5, 5, 50, 100, 500 µg/ml GBL. The calibration curves were
constructed in the case of the culture media by using 0, 0.4, 0.8, 1, 2.5, 5, 50,
100 and 500 µg/ml final γ-butyrolactone concentrations, and in the cases of
blood and urine by using 0, 0.5, 1, 2, 5, 10, 20, 50 µg/ml final GBL concentrations.
ACKNOWLEDGEMENTS
The work was supported by the European Commission grant
STREP-FP6-NMP4-CT2006-032811 and by the grants TÁMOP 4.2.2./A-11/1/
KONV-2012-0065, OTKA K-100667 and the Foundation of Faculty of Medicine,
University of Pécs.
91
ANIKÓ PÉTER, TÍMEA DERGEZ, IBOLYA KISS, FERENC KILÁR
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2. Z.Nemeth, B.Kun, Z.Demetrovics, J. Psychopharmacol. 2010, 24, 1281.
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Chromatography B-Analytical Technologies in the Biomedical and Life
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8. S.D.Ferrara, L.Tedeschi, G.Frison, F.Castagna, L.Gallimberti, R.Giorgetti,
G.L.Gessa, P.Palatini, Journal of Pharmaceutical and Biomedical Analysis
1993, 11, 483.
9. J.D.Doherty, O.C.Snead, R.H.Roth, Analytical Biochemistry 1975, 69, 268.
10. T.B.Vree, E.Vanderkleijn, H.J.Knop, Journal of Chromatography 1976, 121, 150.
11. D.T.Yeatman, K.Reid, Journal of Analytical Toxicology 2003, 27, 40.
12. S.P.Elliott, Forensic Science International 2003, 133, 9.
13. W.A.M.S.Dunn, Emergency Medicine News 2001, 23, 40.
14. Y.Fukui, E.Matsusima, K.Muramoto, N.Nagai, K.Ohama, K.Yamashita, Journal
of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences
2003, 785, 73.
15. S.Raina, D.De Vizio, M.Odell, M.Clements, S.Vanhulle, T.Keshavarz, Biotechnology
and Applied Biochemistry 2009, 54, 65.
16. S.Raina, M.Odell, T.Keshavarz, Journal of Biotechnology 2010, 148, 91.
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18. A.Kankaanpaa, R.Liukkonen, K.Ariniemi, Forensic Sci. Int. 2007, 170, 133.
19. F.Tateo, M.Bononi, Journal of Food Composition and Analysis 2003, 16, 721.
20. M.Villain, V.Cirimele, B.Ludes, P.Kintz, Journal of Chromatography B-Analytical
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92
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 93 – 104)
(RECOMMENDED CITATION)
HETEROCYCLES 34. SYNTHESIS AND ANTIINFLAMMATORY ACTIVITY OF NEW POLYHETEROCYCLIC
SCHIFF BASES AND MANNICH BASES
ALEXANDRA TOMAa, DENISA HAPĂUa, MARA NAGHIb,
LAURIAN VLASEc, CRISTINA MOGOŞANd*, VALENTIN ZAHARIAa
ABSTRACT. New polyheterocyclic Schiff bases and Mannich bases containing
5-(pyridin-4-yl)-2H-1,2,4-triazole-3-thione moiety have been synthesized. The
structures of the newly obtained compounds were confirmed by spectral
analysis IR, 1H NMR, 13C NMR and MS. The obtained Schiff bases and
Mannich bases were screened for their anti-inflammatory activity using the
carrageenan-induced rat paw oedema test. Compounds 6c, 6f, 7b, 7c, 7d,
8a, 8c, 8d, 8f and 10 showed significant anti-inflammatory activity.
Keywords: polyheterocyclic compounds, Schiff bases, Mannich bases, antiinflammatory activity
INTRODUCTION
Heterocyclic ring systems thiazole, 1,2,4-triazole and pyridine can be
commonly found in the structure of many compounds of medicinal interest,
presenting a diverse array of biological activities, including antimicrobial [1,2],
anti-inflammatory [2c,3,4] enzyme inhibitory [5] and anticancer [6] properties.
Moreover, the condensed ring system thiazolo-triazole was also found to be
responsible for antimicrobial [7] and anti-inflammatory activity [7b,8].
a
Iuliu Haţieganu University of Medicine and Pharmacy Cluj-Napoca, Department of Organic
Chemistry
b
Babeş-Bolyai University of Cluj-Napoca, Department of Biochemistry and Biochemical
Engineering, Ro-400028 Cluj-Napoca, Arany János 11, Romania
c
Iuliu Haţieganu University of Medicine and Pharmacy Cluj-Napoca, Department of Pharmaceutical
Technology and Biopharmacy
d
Iuliu Haţieganu University of Medicine and Pharmacy Cluj-Napoca, Department of Pharmacology,
Pysiology and Physiopathology, Ro-400012 Cluj-Napoca, Victor Babeş 41, Romania,
*corresponding author: cmogosan@umfcluj.ro
A. TOMA, D. HAPĂU, M. NAGHI, L. VLASE, C. MOGOŞAN, V. ZAHARIA
Schiff bases and Mannich bases are important classes of pharma
cologically and chemically useful compounds due to their therapeutic potential
and to the reactivity of their functional groups. In particular, Schiff bases and
Mannich bases derived from 1,2,4-triazole were recently reported as potent
anticancer [9], antimicrobial [10], anti-inflammatory and analgesic [11,12]
agents. Consequently, polyheterocyclic Schiff bases and Mannich bases
rejoining the above mentioned ring systems are becoming even more important
in medicinal research.
As a part of our interest for the synthesis of new biologically active
compounds containing azolic rings, herein we report the synthesis, charac
terization and anti-inflammatory evaluation of some new polyheterocyclic
Schiff bases and Mannich bases.
Mannich reaction has found broad application in synthetic organic
chemistry, as a key step for new C-C and C-N bond forming. Besides the
classical variant, which involves the use of an enolisable carbonyl compound
as CH-acidic substrate, atypical Mannich reactions involving other compounds
with mobile hydrogen have been already described. Encouraged by the recently
reported regioselective aminoalkylation of 2H-1,2,4-triazole-3-thione derivatives
[12], which afforded the corresponding N-Mannich bases in good yields, we
decided to apply the N-aminoalkylation reaction in the series of azolic
derivatives and Schiff bases containing the 5-(pyridin-4-yl)-2H-1,2,4-triazole-3thione moiety, in order to obtain new biologically active polyheterocyclic
Mannich bases.
RESULTS AND DISCUSSION
Synthesis of polyheterocyclic compounds
As illustrated in Scheme 1, the heterocyclic precursors 1-4 were
obtained as previously described in the literature [13], starting from isonicotinic
hydrazide.
Condensation of 4-amino-5-(pyridin-4-yl)-2H-1,2,4-triazole-3-thione 4
with various thiazole and thiazolo-triazole aldehydes 5a-f [14,15], in glacial
acetic acid [10a], afforded the corresponding Schiff bases 6a-f in good yield.
Mannich bases 7a-f, 8a,c,d,f, 9-12 were obtained by the amino
methylation of 4-substituted-5-(pyridine-4-yl)-2H-1,2,4-triazole-3-thiones 1-3
and 6a-f with formaldehyde and secondary amines (pyrrolidine and
piperidine) [10].
The structures of all newly synthesized polyheterocyclic compounds
were established by their spectral analysis IR, 1H NMR, 13C NMR and MS.
The IR spectra of Schiff bases 6a-f revealed the presence of the NH absorption band in the range of 3446-3482 cm-1 and the C=S stretching
94
HETEROCYCLES 34. SYNTHESIS AND ANTI-INFLAMMATORY ACTIVITY…
at 1263-1286 cm-1, due to the existence of the thione tautomeric form. The
absorption bands for the primary amino group -NH2 were not observed,
indicating the formation of the Schiff base. The -C=N- stretching vibration
appeared in the range of 1603-1611 cm-1. In the IR spectra of the Mannich
bases 7a-f, 8a,c,d,f, 9-12, the absence of the -NH- absorption band confirmed
the formation of N-Mannich bases.
1. R-N=C=S
2. OH-
O
N
H
N
NH2
CH2O, HN
N NH
S
N
N
N
R
1,2,3
N
N N
S
N
R
9,10,11,12
1. CS2, OH2. H2N-NH-OH
N NH
N
N
S + O
Het
NH2
4
5a-f
N
mCH3-C6H4
c
pBr-C6H4
e
b
N
S
N
S
N
1
S
N
N
7a-f;
8a,c,d,f
Het
N
N N
N
Compound
pCH3-C6H4
S
a
S
N
Het
C6H5
Compound
N
N
6a-f
Compound
5,6,7a-f,
8a,c,d,f
CH2O, HN
N NH
Het
R
N
_
CH3
S
pCl-C6H4
d
C6H5
f
N
S
_
3
NN
N
_
2
S
9
CH3
10
N
N
N
11
7a-f
N
8a,c,d,f
N
N
12
N
Sheme 1. The synthesis of polyheterocyclic compounds
95
A. TOMA, D. HAPĂU, M. NAGHI, L. VLASE, C. MOGOŞAN, V. ZAHARIA
Previously reported spectral studies have already confirmed that 4amino-5-(pyridine-4-yl)-2H-1,2,4-triazole-3-thione exists in the thione tautomeric
form [13b]. In the 1H NMR spectra of compounds 6a-f, the NH proton resonated
as a singlet at δ 14.53 ppm, indicating also in this case the existence of the
thione tautomeric form. The formation of the Schiff bases 6a-f was confirmed
by the presence of the -N=CH- proton as a singlet at δ 9.93-9.97 ppm,
whereas the signal due to the NH2 protons was completely absent.
In the 1H NMR spectra of products 7a-f, 8a,c,d,f, 9-12, the signal at
δ 14.53 ppm due to the NH proton was absent and the >N-CH2-N< protons
appeared as a singlet at δ 5.26-5.53 ppm, confirming the formation of the
corresponding Mannich bases. The presence of the pyrrolidine/piperidine
ring was confirmed by other characteristic signals in the aliphatic region.
In the 13C NMR spectra of Schiff bases 6a-f, the C=S carbon belonging
to the thione tautomeric form was recorded at δ 168.52-169.26 ppm. For
compounds 7a-f, 8a,c,d,f, 9-12, formation of Mannich bases was confirmed
by the presence of a characteristic signal around δ 65.94-71.18 ppm due to
the >N-CH2-N< carbon and by other aliphatic signals due to the pyrrolidine
ring (2 signals at δ 23.84-23.95 ppm and 50.34-50.67 ppm), respectively
the piperidine ring (3 signals at δ 23.77-23.98 ppm, 25.95-26.23 ppm and
51.89-52.13 ppm ), which are absent in 13C spectra of the precursors 1,2,3
and 6a-f. The C=S carbon signal remained present in all 13C spectra of
Mannich bases, at δ 168.32-171.17 ppm.
The anti-inflammatory activity
The anti-inflammatory activity of the tested compounds was found to
be in the inflammatory oedema inhibition range of 10.74% - 58.87%, while
standard drug Diclofenac showed 62.61% inhibition, after 4h (Table 1).
Among the tested compounds, Schiff base 6f and Mannich bases
7b, 7d, 10, 8d and 8f displayed the most potent anti-inflammatory activity,
the percentages of oedema inhibition being close to those of diclofenac. A
moderate anti-inflammatory activity was observed for the Schiff base 6c
and the Mannich bases 7c, 8a and 8c.
Compounds 6c, 10, 8d and 8f proved to be more potent than
diclofenac 1 hour after inducing inflammation (Table 1). Schiff base 6f
displayed anti-inflammatory activity comparable to diclofenac 2 and 3 hours
after inducing inflammation, while the corresponding Mannich base 8f
displayed a better profile after 3 and 4 hours.
96
HETEROCYCLES 34. SYNTHESIS AND ANTI-INFLAMMATORY ACTIVITY…
Table 1. Anti-inflammatory activity of Schiff bases and Mannich bases
Oedema volume in ml (average±SD)
% inhibition
Compound
Control
Diclofenac
6a
6b
6c
6d
6e
6f
7a
7b
7c
7d
7e
7f
9
10
11
8a
8c
8d
12
8f
1h
2h
3h
4h
0.69±0.16
1.48±0.21
1.78±0.28
2.14±0.37
0.40±0.14*
42.02%
0.55±0.12
20.28%
0.71±0.23
-2.89%
0.39±0.14*
43.47%
0.54±0.16
21.74%
0.51±0.14
26.08%
0.49±0.19
28.98%
0.69±0.31
0%
0.43±0.25
37.68%
0.57±0.15
17.39%
0.62±0.27
10.14%
0.49±0.06*
28.98%
0.58±0.22
15.94%
0.44±0.24
36.23%
0.31±0.05*
55.07%
0.51±0.24
26.08%
0.36±0.13*
47.82%
0.47±0.16*
31.88%
0.38±0.15*
44.92%
0.67±0.26
2.89%
0.39±0.22*
43.47%
0.61±0.11*
58.78%
1.24±0.39
16.21%
1.12±0.39
24.32%
0.98±0.3*
33.78%
1.37±0.41
7.43%
1.01±0.42*
31.75%
0.68±0.28*
54.05%
1.11±0.47
25%
0.86±0.43*
41.89%
1.21±0.13*
18.24%
0.79±0.24*
46.62%
1.26±0.43
14.86%
1.03±0.34*
30.40%
1.47±0.30
0.67%
0.90±0.32*
39.18%
1.47±0.30
0.67%
0.97±0.41*
34.45%
1.18±0.25*
20.27%
0.73±0.12*
50.67%
1.64±0.65
-10.81%
0.73±0.26*
50.67%
0.85±0.23*
52.24%
1.25±0.28*
29.77%
1.18±0.41*
33.70%
1.40±0.36
21.34%
1.65±0.51
7.30%
1.27±0.51
28.65%
0.86±0.27*
51.68%
1.33±0.44
25.28%
1.02±0.38*
42.69%
1.19±0.21*
33.14%
1.07±0.35*
39.88%
1.34±0.56
24.71%
1.33±0.43
25.28%
1.53±0.31
14.04%
1.12±0.28*
37.07%
1.35±0.31*
24.15%
1.26±0.37*
29.21%
1.25±0.25*
29.77%
1.00±0.25*
43.82%
1.82±0.70
-2.24%
0.88±0.37*
50.56%
0.80±0.24*
62.61%
1.87±0.47
12.61%
1.49±0.27*
30.37%
1.47±0.38*
31.3%
1.82±0.27
14.95%
1.32±0.45*
38.31%
1.22±0.35*
42.99%
1.91±0.65
10.74%
1.46±0.35*
31.77%
1.31±0.3*
38.78%
1.10±0.43*
48.59%
1.12±0.46*
47.66%
1.3±0.42*
39.25%
1.48±0.35*
30.84%
1.03±0.18*
51.86%
1.28±0.40*
40.18%
1.45±0.31*
32.24%
1.39±0.29*
35.04%
1.13±0.28*
47.19%
1.85±0.59
13.55%
0.88±0.32*
58.87%
* p<0.05 t-test
97
A. TOMA, D. HAPĂU, M. NAGHI, L. VLASE, C. MOGOŞAN, V. ZAHARIA
CONCLUSIONS
A serie of new polyheterocyclic compounds representing Schiff bases
and Mannich bases containing the 5-(pyridine-4-yl)-2H-1,2,4-triazole-3-thione
moiety have been synthesized, characterized and evaluated for their antiinflammatory activity. Schiff bases 6c, 6f and Mannich bases 7b, 7c, 7d, 8a,
8c, 8d, 8f, 10 significantly reduced the inflammatory response, their maximum
percent inhibition ranging from 30 to 58.87%. Derivatization of Schiff bases 6af at NH (2th position of the 1,2,4-triazole ring) into the corresponding NMannich bases enhanced in most cases the anti-inflammatory activity.
EXPERIMENTAL SECTION
All chemicals (solvents and reagents) were purchased from Merck. 1H
NMR and 13C NMR spectra were recorded in CDCl3 and DMSO-D6 solution on a
Brucker Avance DPX spectrometer operating at 300 MHz and respectively 75
MHz. Chemical shifts are expressed in ppm values (δ scale) from TMS as
internal standard. Mass Spectra were recorded on Agilent 1100 Ion Trap mass
spectrometer operating at 70 eV, while IR spectra were recorded on a Brucker
Equinox 55 FT-IR spectrometer. Melting points were determined on open glass
capillaries using an Electrothermal IA 9000 digital melting point apparatus.
General procedure for the synthesis of Schiff bases 6a-f
To a solution of 4-amino-5-(pyridine-4-yl)-2H-1,2,4-triazole-3-thione
(4, 1 mmol) in 10 ml glacial acetic acid, the thiazolic aldehyde 5a-f (1,5 mmol)
was added. The mixture was refluxed for 2 h. The formed precipitate was
isolated by filtration and washed with water and then with ethanol.
4-((2-phenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2H-1,2,4-triazole-3thione (6a): Yield 86%; solid; m.p. 307.7-309.70C; IR (KBr, cm-1): ν = 3450 cm-1
(N-H secondary); 3085 cm-1 (C-H aromatic); 1603 cm-1 (C=N); 1271 cm-1 (C=S);
1
H NMR (300 MHz, DMSO-D6): δ = 7.54-7.56 (m, 3H); 7.93 (d, J = 6.0 Hz, 2H);
8.01-8.03 (m, 2H); 8.67 (s, 1H); 8.76 (d, J = 5.8 Hz, 2H); 9.96 (s, 1H); 14.53 (s,
1H); 13C NMR (75 MHz, DMSO-D6): δ = 122.41; 127.02; 128.00; 129.90; 131.48;
132.71; 133.14; 147.06; 149.83; 150.76; 159.77; 163.77; 169.18; ESI+-MS: M+
found (M+ calculated for C17H12N6S2): 365.2 (364.4).
4-((2-p-tolylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2H-1,2,4-triazole-3thione (6b): Yield 78%; solid; m.p. 313.3-315.50C; IR (KBr, cm-1): ν = 3450 cm-1
(N-H secondary); 3082 cm-1 (C-H aromatic); 1603 cm-1 (C=N); 1269 cm-1 (C=S);
1
H NMR (300 MHz, DMSO-D6): δ = 2.37 (s, 3H); 7.35 (d, J = 7.6 Hz, 2H); 7.897.92 (m, 4H); 8.63 (s, 1H); 8.76 (d, J = 4.4 Hz, 2H); 9.93 (s, 1H); 14.52 (s, 1H); 13C
NMR (75 MHz, DMSO-D6): δ = 21.46; 122.41; 126.95; 127.60; 130.14; 130.42;
133.15; 141.18; 147.06; 149.70; 150.76; 159.88; 163.27; 169.27; ESI+-MS: M+
found (M+ calculated for C18H14N6S2): 379.3 (378.5).
98
HETEROCYCLES 34. SYNTHESIS AND ANTI-INFLAMMATORY ACTIVITY…
4-((2-m-tolylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2H-1,2,4-triazole-3thione (6c): Yield 89%; solid; m.p. 310.3-314.70C; ν = 3450 cm-1 (N-H secondary);
3055 cm-1 (C-H aromatic); 1611 cm-1 (C=N); 1263 cm-1 (C=S); 1H NMR (300 MHz,
DMSO-D6): δ = 2.39 (s, 3H); 7.34 (d, J = 7.5 Hz, 1H); 7.42 (t, J = 7.6 Hz, 1H); 7.787.82 (m, 2H); 7.92 (dd, J = 4.6 Hz, 1.5 Hz, 2H); 8.64 (s, 1H); 8.76 (d, J = 6.0 Hz,
2H); 9.96 (s, 1H); 14.53 (s, 1H); 13C NMR (75 MHz, DMSO-D6): δ = 21.32; 122.41;
124.22; 127.34; 127.75; 129.76; 132.13; 132.66; 133.14; 139.31; 147.05; 149.78;
150.74; 159.63; 163.29; 169.26; ESI+-MS: M+ found (M+ calculated for
C18H14N6S2): 379.3 (378.5).
4-((2-p-chlorophenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2H-1,2,4triazole-3-thione (6d): Yield 97%; solid; m.p. 307.3-308.40C; ν = 3446 cm-1 (N-H
secondary); 3058 cm-1 (C-H aromatic); 1604 cm-1 (C=N); 1276 cm-1 (C=S); 1H
NMR (300 MHz, DMSO-D6): δ = 7.62 (d, J = 8.1 Hz, 2H); 7.92 (d, J = 4.5 Hz, 2H);
8.05 (d, J = 7.9 Hz, 2H); 8.70 (s, 1H); 8.77 (d, J = 4.5 Hz, 2H); 9.97 (s, 1H); 14.53
(s, 1H); 13C NMR (75 MHz, DMSO-D6): δ = 120.20; 123.88; 126.97; 129.98;
133.29; 135.36; 137.52; 146.30; 149.16; 150.76; 162.83; 165.06; 168.52; ESI+MS: M+ found (M+ calculated for C17H11ClN6S2): 399.2 (398.9).
4-((2-p-bromophenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2H-1,2,4triazole-3-thione (6e): Yield 87%; solid; m.p. 296.1-298.30C; ν = 3482 cm-1 (N-H
secondary); 3055 cm-1 (C-H aromatic); 1604 cm-1 (C=N); 1277 cm-1 (C=S); 1H
NMR (300 MHz, DMSO-D6): δ = 7.76 (d, J = 8.4 Hz, 2H); 7.92 (d, J = 5.7 Hz, 2H);
7.98 (d, J = 8.4 Hz, 2H); 8.71 (s, 1H); 8.77 (d, J = 5.5 Hz, 2H); 9.97 (s, 1H); 14.53
(s, 1H); 13C NMR (75 MHz, DMSO-D6): δ = 121.84; 124.35; 127.57; 128.44;
131.44; 132.39; 132.82; 146.60; 149.57; 150.27; 158.60; 162.92; 167.43; ESI+MS: M+ found (M+ calculated for C17H11BrN6S2): 443.3 (443.3).
4-((2-phenylthiazolo[3,2-b][1,2,4]-triazol-6-yl)methyleneamino)-5-(pyridin-4yl)-2H-1,2,4-triazole-3-thione (6f): Yield 77%; solid; m.p. 285.3-288.20C; ν = 3461
cm-1 (N-H secondary); 3067 cm-1 (C-H aromatic); 1604 cm-1 (C=N); 1286 cm-1
(C=S); 1H NMR (300 MHz, DMSO-D6): δ = 7.51-7.56 (m, 3H); 8.12-8.16 (m, 2H);
8.29 (dd, J = 4.6 Hz, 1.5 Hz, 2H); 8.40 (s, 1H); 8.65 (d, J = 5.9 Hz, 2H); 9.97 (s,
1H); 14.53 (s, 1H); 13C NMR (75 MHz, DMSO-D6): δ = 121.42; 122.93; 123.95;
126.69; 127.04; 129.59; 130.32; 136.83; 137.42; 147.55; 148.45; 150.47; 151.64;
161.91; ESI+-MS: M+ found (M+ calculated for C17H11BrN6S2): 404.3 (404.5).
General procedure for the synthesis of Mannich bases 7a-f;
8a,c,d,f; 9-12
1 mmol of the previously obtained 1,2,4-triazole derivatives (Schiff bases
6a-f and triazole derivatives 1-3) was suspended into a mixture of 2.5 ml DMF and 1
ml of absolute ethanol. To the obtained mixture were added 0.15 ml of formaldehyde
solution 37% and 1 mmol of secondary amine (pyrrolidine, piperidine). The reaction
mixture was stirred at room temperature for 48 h and then kept for 12h at 0ºC. The
formed precipitate was filtered and washed with ethanol.
99
A. TOMA, D. HAPĂU, M. NAGHI, L. VLASE, C. MOGOŞAN, V. ZAHARIA
4-((2-phenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((pyrrolidin-1yl)methyl)-2H-1,2,4-triazole-3-thione (7a): Yield 50%; solid; m.p. 145.2-143.80C;
ν = 3093 cm-1 (C-H aromatic); 2964 cm-1 (C-H aliphatic); 1676 cm-1 (C=N); 1268
cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.77 (m, 4H); 2.95 (m, 4H); 5.36 (s,
2H); 7.46-7.48 (m, 3H); 7.98-8.02 (m, 5H); 8.76 (d, J = 6 Hz, 2H); 10.46 (s, 1H);
13
C NMR (75 MHz, CDCl3): δ = 24.02; 50.50; 66.10; 122.32; 124.61; 126.95;
129.21; 130.99; 132.80; 133.00; 145.95; 150.36; 150.43; 156.53; 164.33; 169.88.
4-((2-p-tolylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((pyrrolidin-1yl)methyl)-2H-1,2,4-triazole-3-thione (7b): Yield 69%; solid; m.p. 151.2-153.90C;
ν = 3090 cm-1 (C-H aromatic); 2971 cm-1 (C-H aliphatic); 1676 cm-1 (C=N); 1266
cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.78 (m, 4H); 2.43 (s, 3H); 2.97 (m,
4H); 5.38 (s, 2H); 7.29 (d, J = 6.7 Hz, 2H); 7.92 (d, J = 8.1 Hz, 2H); 8.01-8.02 (m,
3H); 8.76 (d, J = 6.1 Hz, 2H); 10.45 (s, 1H); 13C NMR (75 MHz, CDCl3): δ = 21.62;
24.03; 50.50; 66.10; 122.32; 124.40; 126.89; 129.89; 130.19; 133.01; 141.42;
145.96; 150.21; 150.44; 156.67; 164,40; 169.93.
4-((2-m-tolylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((pyrrolidin-1yl)methyl)-2H-1,2,4-triazole-3-thione (7c): Yield 69%; solid; m.p. 177.6-178.90C;
ν = 3031 cm-1 (C-H aromatic); 2967 cm-1 (C-H aliphatic); 1679 cm-1 (C=N); 1282
cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.77 (m, 4H); 2.43 (s, 3H); 2.95 (m,
4H); 5.36 (s, 2H); 7.29-7.38 (m, 2H); 7.78 (d, J = 7.5 Hz, 1H); 7.84 (s, 1H); 7.988.01 (m, 3H); 8.76 (d, J = 6.1 Hz, 2H); 10.45 (s, 1H); 13C NMR (75 MHz, CDCl3): δ
= 21.32; 23.87; 50.34; 65.94; 122.17; 124.03; 124.48; 127.31; 128.93; 131.66;
132.54; 132.85; 138.91; 145.79; 150.11; 150.26; 156.39; 164.24; 169.82.
4-((2-p-chlorophenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2((pyrrolidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione (7d): Yield 57%; solid; m.p.
170.2-172.80C; ν = 3031 cm-1 (C-H aromatic); 2972 cm-1 (C-H aliphatic); 1674 cm-1
(C=N); 1267 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.79 (m, 4H); 2.96 (m,
4H); 5.38 (s, 2H); 7.46 (d, J = 8.0 Hz, 2H); 7.94-8 (m, 4H); 8.05 (s, 1H); 8.76 (d, J=
4.3 Hz, 2H); 10.49 (s, 1H); 13C NMR (75 MHz, CDCl3): δ = 23.94; 50.43; 66.06;
122.24; 124.54; 128.05; 129.39; 131.20; 132.89; 136.94; 145.87; 150.35; 150.44;
156.27; 164.30; 168.39.
4-((2-p-bromophenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((pyrrolidin1-yl)methyl)-2H-1,2,4-triazole-3-thione (7e): Yield 58%; solid; m.p. 168.8-171.30C;
ν = 3035 cm-1 (C-H aromatic); 2972 cm-1 (C-H aliphatic); 1673 cm-1 (C=N); 1266 cm1
(C=S); 1H NMR (300 MHz, CDCl3): δ =1.79 (m, 4H); 2.97 (m, 4H); 5.38 (s, 2H);
7.63 (d, J = 8.5 Hz, 2H); 7.90 (d, J = 8.5 Hz, 2H); 7.99 (d, J = 6.1 Hz, 2H); 8.06 (s,
1H); 8.77 (d, J = 6.1 Hz, 2H); 10.50 (s, 1H); 13C NMR (75 MHz, CDCl3): δ = 23.95;
50.43; 66.07; 122.24; 124.52; 125.31; 128.25; 131.63; 132.35; 132.89; 145.88;
150.36; 150.48; 156.08; 164.25; 168.38.
4-((2-phenylthiazolo[3,2-b][1,2,4]-triazol-6-yl)methyleneamino)-5-(pyridin-4-yl)2-((pyrrolidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione (7f): Yield 50%; solid; m.p.
208.5-210.70C; ν = 3043 cm-1 (C-H aromatic); 2964 cm-1 (C-H aliphatic); 1672 cm-1
(C=N); 1274 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.79 (m, 4H); 2.97 (m,
100
HETEROCYCLES 34. SYNTHESIS AND ANTI-INFLAMMATORY ACTIVITY…
4H)); 5.38 (s, 2H); 7.48-7.51 (m, 3H); 7.66 (s, 1H); 8.19-8.22 (m, 2H); 8.38 (dd, J =
4.6 Hz, 1.6 Hz, 2H); 8.77 (dd, J = 4.6 Hz, 1.6 Hz, 2H); 11.16 (s, 1H); 13C NMR (75
MHz, CDCl3): δ = 24.20; 50.62; 66.11; 121.54; 122.66; 127.01; 128.05; 129.03;
130.42; 130.92; 132.84; 145.99; 146.68; 150.70; 157.53; 163.95; 168.36.
4-((2-phenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((piperidin-1yl)methyl)-2H-1,2,4-triazole-3-thione (8a): Yield 87%; solid; m.p. 188.3-188.90C;
ν = 3031 cm-1 (C-H aromatic); 2944 cm-1 (C-H aliphatic); 1669 cm-1 (C=N); 1270
cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.42 (m, 2H); 1.61 (m, 4H); 2.84 (m,
4H); 5.27 (s, 2H); 7.49 (m, 3H); 8.01-8.04 (m, 5H); 8.78 (d, J = 4.8 Hz, 2H); 10.47
(s, 1H); 13C NMR (75 MHz, CDCl3): δ =23.77; 26.01; 51.89; 70.87; 122.25; 124.54;
126.88; 129.13; 130.91; 132.73; 132.96; 145.67; 150.29; 150.36; 156.51; 164.40;
169.64.
4-((2-m-tolylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2-((piperidin-1yl)methyl)-2H-1,2,4-triazole-3-thione (8c): Yield 67%; solid; m.p. 151.8-155.50C;
ν = 3023 cm-1 (C-H aromatic); 2933 cm-1 (C-H aliphatic); 1676 cm-1 (C=N); 1270
cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.42 (m, 2H); 1.61 (m, 4H); 2.45 (s,
3H); 2.84 (t, J = 5.1 Hz, 4H); 5.27 (s, 2H); 7.28-7.40 (m, 2H); 7.80 (d, J = 7.5 Hz,
1H); 8.01-8.03 (m, 3H) overlapped with 7.81 (s, 1H); 8.79 (dd, J = 4.7 Hz, 1.5 Hz,
2H); 10.45 (s, 1H); 13C NMR (75 MHz, CDCl3): δ = 21.39; 23.78; 26.01; 51.90;
70.65; 122.25; 124.12; 124.57; 127.40; 129.02; 131.73; 132.63; 132.97; 138.89;
145.67; 150.20; 150.30; 156.54; 164.41; 169.91.
4-((2-p-chlorophenylthiazol-4-yl)methyleneamino)-5-(pyridin-4-yl)-2((piperidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione (8d): Yield 58%; solid; m.p.
187.3-187.9 0C; ν = 3103 cm-1 (C-H aromatic); 2930 cm-1 (C-H aliphatic); 1669 cm1
(C=N); 1273 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.42 (m, 2H); 1.60 (m,
4H); 2.84 (t, J = 5.0 Hz, 4H); 5.26 (s, 2H); 7.45 (d, J = 8.5 Hz, 2H); 7.94-8.00 (m,
4H); 8.05 (s, 1H); 8.78 (d, J = 6.0 Hz, 2H); 10.47 (s, 1H); 13C NMR (75 MHz,
CDCl3): δ = 23.84; 26.07; 51.96; 70.96; 122.29; 124.60; 128.12; 129.45; 131.27;
132.99; 137.00; 154.73; 150.43; 150.51; 156.38; 164.45; 168.32.
4-((2-phenylthiazolo[3,2-b][1,2,4]-triazol-6-yl)methyleneamino)-5-(pyridin-4yl)-2-((piperidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione (8f): Yield 60%; solid;
m.p. 212.4-215.70C; ν = 3055 cm-1 (C-H aromatic); 2932 cm-1 (C-H aliphatic); 1670
cm-1 (C=N); 1261 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.42 (m, 2H); 1.61
(m, 4H); 2.84 (t, J = 5.1 Hz, 4H); 5.26 (s, 2H); 7.49-7.51 (m, 3H); 7.66 (s, 1H);
8.19-8.22 (m, 2H); 8.38 (dd, J = 4.6 Hz, 1.6 Hz, 2H); 8.77 (dd, J = 4.6 Hz, 1.6 Hz,
2H); 11.16 (s, 1H); 13C NMR (75 MHz, CDCl3): δ = 23.98; 26.23; 52.13; 70.96;
121.50; 122.67; 127.03; 128.08; 129.04; 130.42; 130.93; 132.88; 145.94; 146.96;
150.72; 159.18; 164.31; 168.42.
4-methyl-5-(pyridin-4-yl)-2-((pyrrolidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione
(9): Yield 59%; solid; m.p. 140.3-142.80C; ν = 2964 cm-1 (C-H aliphatic); 1220 cm-1
(C=S); 1H NMR (300 MHz, CDCl3): δ = 1.71-1.75 (m, 4H); 2.90 (t, J = 6.4 Hz, 4H);
3.71 (s, 3H); 5.27 (s, 2H); 7.54 (dd, J = 4.5, 1.5 Hz, 2H); 8.79 (dd, J = 4.5, 1.5 Hz,
2H); 13C NMR (75 MHz, CDCl3): δ = 23.86; 33.24; 50.47; 66.27; 122.17; 133.39;
147.95; 150.79; 169.88.
101
A. TOMA, D. HAPĂU, M. NAGHI, L. VLASE, C. MOGOŞAN, V. ZAHARIA
4-allyl-5-(pyridin-4-yl)-2-((pyrrolidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione
(10): Yield 40%; solid; m.p. 110.5-111.90C; ν = 3036 cm-1 (C-H vinyl); 2975 cm-1
(C-H aliphatic); 1267 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.73-1.78 (m,
4H); 2.91 (t, J = 5.5 Hz, 4H); 4.78-4.80 (m, 2H); 5.30 (s, 2H); 5.93-6.05 (m,
1H); 7.58 (dd, J = 4.5 Hz, 1.5 Hz, 2H); 8.77 (dd, J = 4.5 Hz, 1.5 Hz, 2H); 13C
NMR (75 MHz, CDCl3): δ = 23.85; 47.85; 50.50; 66.24; 118.52; 122.20;
130.87; 133.33; 148.18; 150.73; 169.78.
4-phenyl-5-(pyridin-4-yl)-2-((pyrrolidin-1-yl)methyl)-2H-1,2,4-triazole-3thione (11): Yield 61%; solid; m.p. 160.5-161.50C; ν = 3031 cm-1 (C-H
aromatic); 2957 cm-1 (C-H aliphatic); 1151 cm-1 (C=S); 1H NMR (300 MHz,
CDCl3): δ = 1.77-1.81 (m, 4H); 2.97 (t, J = 5.5 Hz, 4H); 5.35 (s, 2H); 7.18 (dd, J
= 4.6 Hz, 1.5 Hz, 2H); 7.29-7.32 (m, 3H); 7.52-7.54 (m, 2H); 8.54 (dd, J = 4.6
Hz, 1.5 Hz, 2H); 13C NMR (75 MHz, CDCl3): δ = 23.92; 50.67; 66.54; 121.59;
129.21; 130.04; 130.29; 132.92; 134.72; 146.83; 150.34; 170.98.
4-phenyl-5-(pyridin-4-yl)-2-((piperidin-1-yl)methyl)-2H-1,2,4-triazole-3-thione
(12): Yield 60%; solid; m.p. 204.5-206.30C; ν = 3029 cm-1 (C-H aromatic); 2932
cm-1 (C-H aliphatic); 1273 cm-1 (C=S); 1H NMR (300 MHz, CDCl3): δ = 1.421.46 (m, 2H); 1.59-1.66 (m, 4H); 2.86 (t, J = 5.2 Hz, 4H); 5.27 (s, 1H); 7.21 (dd,
J = 4.6 Hz, 1.5 Hz, 2H); 7.31-7.34 (m, 2H); 7.55-7.57 (m, 3H); 8.57 (dd, J = 4.6
Hz, 1.5 Hz, 2H); 13C NMR (75 MHz, CDCl3): δ =23.77; 25.95; 51.91; 71.18;
121.61; 128.24; 130.04; 130.29; 132.99; 134.75; 146.61; 150.32; 171.17.
The anti-inflammatory activity
All synthesized compounds were evaluated in order to determinate
their anti-inflammatory activity, by performing the rat paw oedema test,
according to the method of Winter et al (1962) modified by the introduction of a
commercially available plethysmometer from Ugo Basile, Varese, Italy [16].
Male rats Winstar breed with an average weight around 175g were divided into
22 groups of 6 rats. All animals were housed in standard conditions with food
and water ad libitum. The first group which represents the control one was
injected intraperitoneally (i.p.) with 1 ml vehicle (Tween 80 and distilled water).
The second group which represents the standard one was injected i.p. with
diclofenac 20mg/kg as reference drug. In the 20 treated groups, all tested
compounds were injected i.p. with doses of 20mg/kg. For all 22 groups the
volume of the solution used for intraperitoneal administration was 1ml.
The inflammation was induced thirty minutes after intraperitoneal
injection by administrating 0.1 ml carrageenan solution 1% intraplantar. Rats
oedema were evaluated by measuring the rat hind left paw volume at hourly
intervals from 1 to 4 hours. The rats paw volume was also measured before
inducing inflammation.
102
HETEROCYCLES 34. SYNTHESIS AND ANTI-INFLAMMATORY ACTIVITY…
The inhibition percent was calculated according to the following
formula: % Inhibition of oedema = (1-Ēt/Ēm)x100, where Ēt represents the
average value of the oedema in all treated groups 1 – 4 hours after the
induced inflammation (in ml) and Ēm represents the average value of the
oedema in control group 1 – 4 hours after after the induced inflammation (in
ml).
Statistical analysis was performed by Student’s ‘t’ test, and p-value
was choosen less than 0.05 for statistical significance.
The biological experiment was conducted according to the EC
Directive 2010/63/EU, which regulates the use of laboratory animals.
ACKNOWLEDGMENTS
The present study was conducted with the financial support of the
European Social Fund under the project POSDRU number 107/1.5/S/78702.
The authors are grateful to Mr. Mircea Dan Puia for providing the IR spectra.
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104
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 105 – 114)
(RECOMMENDED CITATION)
ELECTROCHEMICAL BEHAVIOR OF THE HEMIN MODIFIED
GRAPHITE ELECTRODE FOR H2O2 DETECTION
GEORGETA MARIA MARESa, GRAZIELLA LIANA TURDEANa*,
a
IONEL CĂTĂLIN POPESCU
ABSTRACT. Aiming to detect amperometrically H2O2, iron (III) protoporphyrin
IX (hemin; Hm) was immobilized by simple adsorption on the surface of a
graphite (G) electrode. The electrochemical behavior of the G/Hm modified
electrode was investigated by using cyclic voltammetry (CV) and squarewave voltammetry (SWV) under different experimental conditions (scan rate
or frequency and pH). The catalytic current measured at G/Hm was found
to depend linearly on the H2O2 concentration from ~0.01 mM up to 0.04
mM H2O2 (R/N = 0.987 / 4) and from ~0.01 mM up to 0.08 mM H2O2 (R/N =
0.973/14) for CV and SWV measurements, respectively. For both methods
the detection limit was ~10 μM, while the sensitivity was much higher for
SWV [(276 ± 12) mA/M] than for CV [(13.5 ± 1.6) mA/M].
Keywords: iron(III) protoporphyrin (IX), hydrogen peroxide, cyclic voltammetry,
square wave voltammetry, electrocatalysis.
INTRODUCTION
As defined by IUPAC, a chemically modified electrode (CME) “is an
electrode made of a conducting or semiconducting material that is coated
with a selected monomolecular, multimolecular, ionic, or polymeric film of a
chemical modifier and that by means of faradaic (charge-transfer) reactions or
interfacial potential differences (no net charge transfer) exhibits chemical,
electrochemical, and/or optical properties of the film” [1]. Usually, the chemically
modified electrodes can be obtained by one of the following approaches: (i)
chemisorption, (ii) covalent bonding, (iii) polymer film coating, and (iv) entrapment
in a conductive material. Among these, the simplest way exploiting the
a
Department of Physical Chemistry, ‘‘Babes-Bolyai’’ University, Arany Janos 11, RO-3400
Cluj-Napoca, Romania,*corresponding author: gturdean@chem.ubbcluj.ro
GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN POPESCU
adsorption of the modifier on the electrode surface, generates a stable film.
Usually, this approach yields monolayer modified electrodes with high
electrocatalytic activity.
Hemin (iron protoporphyrin IX; Hm) is
one of the most important biological substances.
It corresponds to the active center of several
families of heme proteins, for example C-type
cytocromes, peroxidase and oxygen–carrying
proteins such as hemoglobin (Hb) and myoglobin
(Mb) [2]. Hemin dissolved in an aqueous solution,
adsorbed on the electrode surface or incorporated
within a polymeric film immobilized on the electrode
surface, maintains its electrochemical activity [3].
Hemin, due to its peculiar chemical structure
(Scheme 1), is strongly adsorbed on the carbonaceous
Scheme 1
electrode materials, especially on pyrolytic graphite
(PG) [4, 5]. The so obtained modified electrodes were used for the amperometric
detection of H2O2 [6], superoxide [7], nitritc oxide [8], 4-aminophenol [9] and
tryptophan or its derivates [10].
In this work we report on the preparation, by simple adsorption, of a
hemin modified graphite electrode. The electrochemical behavior of G/Hm
was examined by using two complementary electrochemical methods:
cyclic voltammetry (CV) and square-wave voltammetry (SWV). Finally, the
G/Hm modified electrode was used for the amperometric detection of H2O2
and the electroanalytical and kinetic parameters were estimated.
RESULTS AND DISCUSSION
Electrochemical behavior of G/Hm electrode
In figure 1 are showed the CV and SWV responses, recorded at
G/Hm modified electrodes. In both cases, stable and well-defined peaks
pairs corresponding to the immobilized hemin were observed. Also, the CV
measurements show that the peak potentials shift progressively towards
higher absolute values when the scan rate increases, suggesting a quasireversible electrochemical process.
The cyclic voltammogram recorded at 50 mV/s (Figure 1A) was
used to evaluate the formal standard potential [E0’ = (Epa + Epc)/2, where Epa
and Epc stand for the anodic and cathodic peak potentials, respectively] of the
hemin redox couple. The calculated value (-0.33 V vs. Ag/AgCl,KClsat) was
found in good agreement with that already reported (-0.34 V vs. Ag/AgCl,KCl3M)
for hemin [11]. Additionally, the peak potentials separation (ΔEp = Ep,a – Ep,c
= 0.034 V, at 50 mV/s), confirms that the investigated redox process corresponds
106
ELECTROCHEM. BEHAVIOR OF THE HEMIN MODIFIED GRAPHITE ELECTRODE FOR H2O2 DETECTION
to a quasi-reversible one [8]. Additionally, the Ipa/Ipc ratio is very close to 1
(0.955, at 50 mV/s). Finally, it can be concluded that the adsorbed hemin
exhibits the characteristic features for a quasi-reversible redox couple [12].
I / mA
I / mA
50
0
A
0
-50
-200
20 mV/s
50 mV/s
100 mV/s
200 mV/s
-100
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KClsat.
B
8 Hz
25 Hz
50 Hz
100 Hz
-400
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KClsat.
Figure 1. Cyclic (A) and square-wave (B) voltammograms recorded at G/Hm modified
electrode. Experimental conditions: supporting electrolyte, 0.1 M phosphate
buffer (pH 7.0); starting potential, -0.6 V vs. Ag/AgCl,KClsat. (A) and 0 V vs.
Ag/AgCl,KClsat (B); SWV amplitude, 20 mV; deaerated solution (Ar)
As expected for a surface confined redox couple [13], in the investigated
range of potential scan rate (20 – 200 mV/s), the anodic (Iap) and cathodic
(Icp) peak currents depend linearly on the potential scan rate (v) (Figure 2A).
Within the limits of the experimental error, this conclusion was
confirmed by the slope values obtained from the log(Ip) - log(v) dependencies
(Table 1).
Table 1. The slopes of the log(Ip) vs. log(v) dependencies for G/Hm electrode.
Redox process
anodic
cathodic
Slope
1.18 ± 0.05
0.82 ± 0.02
R / No. of exp. points
0.990 / 6
0.997 / 7
For CV measurements, this parameter is considered a relevant
criterion helping to distinguish between the adsorbed (slope ∼1) or dissolved
(slope ∼0.5) redox couples. Furthermore, it is worth to mention that SWV
measurements confirm that hemin behaves as a redox couple strongly
immobilized on the graphite surface. Thus, the Icp depends linearly on the
square root of the applied frequency (f) (Figure 2B).
107
600
80
A
-Ipc / µA
Ipa / mA
GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN POPESCU
40
400
Ipc / mA
0
pH 4
pH 7
pH 8
200
-40
B
-80
0
40
80
0
120 160 200
0
3
6
9
1/2
-1/2
-1
f
/ s
v / mVs
Figure 2. The Ip vs. potential scan rate (A) and Ipc vs. ν½ (B) dependencies recorded at
G/Hm modified electrode. Experimental conditions: see figure 1.
Both methods (CV and SWV) used to investigate the electrochemical
behavior of the G/Hm modified electrode showed that, when the pH of the
supporting electrolyte increases, a negative shift of the recorded cyclic
voltammograms can be clearly observed (Figure 3).
pH 4.0
200
pH 5.7
pH 7.0
100
0
-5
-10
pH 5.7
pH 7.0
pH 8.0
I / μA
I / μA
5
pH 4.0
pH 8.0
0
-100
A
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KClsat.
B
-200
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KClsat.
Figure 3. pH influence on the electrochemical response of G/Hm modified electrode
recorded using CV (A) and SWV (B) measurements. Experimental conditions:
supporting electrolyte, 0.1 M phosphate buffer; starting potential, -0.6 V
vs. Ag/AgCl,KClsat (A) and 0 V vs. Ag/AgCl,KClsat (B); scan rate, 20 mV/s
(A); frequency 25 Hz (B); amplitude, 20 mV (B); deaerated solution (Ar).
108
ELECTROCHEM. BEHAVIOR OF THE HEMIN MODIFIED GRAPHITE ELECTRODE FOR H2O2 DETECTION
0
A
100
anodic peak
cathodic peak
90
-10
t = 0 min
t = 100 min
t = 300 min
-20
-0.6
-0.4
-0.2
0.0
E / V vs. Ag/AgCl,KClsat
Γt/Γ0 / %
I / μA
The E0’ values, estimated from the CV and SWV measurements
illustrated in figures 3A and 3B, respectively, were found to depend linearly
on the pH of supporting electrolyte (results not shown). However, in the pH
range from 4 up to 8, the values of the slopes calculated for these dependencies
[CV: (-0.041 ± 0.005) V/pH, with R = 0.962 and n = 4; SWV: (-0.033 ±
0.001) V/pH, with R = 0.99 and n = 4], do not agree with the theoretical value
(0.059 V/pH) expected for a redox process involving the transfer of 1e-/1H+.
This peculiar behavior was already observed for hemin [14, 15] and was
attributed to the protonation states of the trans ligands of the heme iron,
combined with the protonation of the amino acids surrounding the heme or
the protonation of the water molecule coordinated to the iron atom [16, 17, 18].
The stability of the modified electrode is a very important characteristic
because it provides information on the electrode life-time, a decisive parameter
for its future applications. For this reason, the short-time stability of G/Hm
was evaluated by continuous cycling of the electrode potential when it was in
contact with the supporting electrolyte (0.1 M PB, pH 7). Figure 4A shows
qualitatively that for both cathodic and anodic peak currents no significant
variation in time can be observed after 12 repetitive full potential scans.
20
0
0
200 400 600
Time / s
800
Figure 4. Repetitive CV measurements performed at G/Hm modified electrode (A)
and the time dependence of the relative surface coverage (Γt/Γ0) (B).
Experimental conditions: supporting electrolyte, 0.1 M PB (pH 7.0); starting
potential, -0.6 V vs. Ag/AgCl,KClsat.; scan rate, 50 mV/s; deaerated
solution (Ar)
109
GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN POPESCU
The variation in time of the electrode surface coverage [Γ(mol/cm2)
= Q/(nFA), where Q(Coulomb) is the amount of charge corresponding to
the cathodic or anodic under-peak area, estimated after the background
current correction; n(=1) is the number of electrons transferred during the
redox process, which generates the voltammetric peak; F (Coulomb) is the
Faraday’s constant; A(cm2) is the electrode geometric area] confirms that
hemin is strongly adsorbed on the graphite surface (Figure 4B).
The tables 2-4 summarized the data concerning the variation in time
of the surface coverage (Table 2) and the peak parameters (Tables 3 and 4) of
the voltammetric response recorded at G/Hm modified electrode. Between
measurements the G/Hm electrodes were stored at 4°C, in a water saturated
atmosphere. All data prove the high stability of the G/Hm modified electrode.
This behavior was related to the hemin insolubility under acidic and neutral
conditions [19], associated with the strong π-π interaction between hemin
and graphite [20].
Table 2. Short time stability of G/Hm modified electrode.
Time(s
)
48
240
480
720
Гc
(nmol/cm2)
76.2
76.6
76.8
76.5
Гa
(nmol/cm2)
129
128
135
130
ΔГa
(%)
0.08
4.65
0.08
ΔГc
(%)
0.53
0.79
0.39
ΔГc= 100(Гc,t – Гc,t=48)/Гc,t=48; ΔГa= 100(Гa,t – Гa,t=48)/Гa,t=48
Table 3. Short time variation of the peak parameters for the voltammetric
response of G/Hm modified electrode.
Time
Epc
E0’
Epa
ΔEp
Iap/Icp
(s)
(V)
(V*)
(V*)
(V*)
48
-0.346
-0.306
0.040
0.020
1.38
240
-0.348
-0.306
0.042
0.021
1.36
480
-0.348
-0.306
0.042
0.021
1.38
720
-0.348
-0.306
0.042
0.021
1.37
*Epc, Epc and E0’ were measured vs. the Ag/AgCl,KClsat reference electrode
Table 4. Long time variation of the peak parameters for the voltammetric
response of G/Hm modified electrode.
ΔIap
(%)
7.6
ΔIcp
(%)
2.4
ΔГc
(%)
6.5
ΔГa
(%)
9.3
ΔEp
(mV)
23
Iap/Icp
1.15
where: ΔIcp = 100(Icp, t=305 - Icp, t=0)/Icp, t=0 ; ΔIap = 100(Iap, t=305 – Iap, t=0)/Iap, t=0
ΔГc= 100(Гc,t=305 – Гc,t=0)/Гc,t=0; ΔГa= 100(Гa,t=305 – Гa,t=0)/Гa,t=0
110
ELECTROCHEM. BEHAVIOR OF THE HEMIN MODIFIED GRAPHITE ELECTRODE FOR H2O2 DETECTION
Electrocatalytic behavior of G/Hm modified electrode
Taking into account that H2O2 is a product of the biochemical
reactions catalyzed by oxidases, its detection is of considerable importance
in clinical, food, pharmaceutical and environmental analysis [2, 21]. In this
context, the electrocatalytic behavior of the G/Hm modified electrode was
investigated for H2O2 electrocatalytic reduction by using CV and SWV
measurements (Figure 6). As can be seen from figure 6 and table 6, the
SWV measurements provided better analytical and kinetic parameters than
those obtained from CV measurements. Probably, this difference is due to
the higher resolution of SWV technique, associated with the easier and better
correction for the background current in the case of SWV measurements.
0.80
0.40
0.00
30
0
100
H2O2 / mM
ISWV / μA
ICV / μA
60
0
200
Figure 6. Calibration curve of the G/Hm modified electrode for H2O2 detection using
CV and SWV measurements. Experimental conditions: supporting electrolyte,
0.1 M PB (pH 7.0); starting potential, -0.6 V vs. Ag/AgCl,KClsat.(CV), 0 mV vs.
Ag/AgCl,KClsat. (SWV); scan rate, 20 mV/s; amplitude, 20 mV; frequency, 25
Hz; deaerated solution (Ar).
Table 5. Analytical and kinetic parameters of G/Hm modified electrode.
Method
Parameters
Imax (µA)
KMapp (mM)
Sensitivity (mA/M)
R/N
Slope (A/mM)
Detection limit /mM
Linear range (mM)
R/N
*Sensitivity = Imax/KMapp
CV
Michaelis-Menten fitting
0.77 ± 0.02
20.2 ± 2.5
0.038
0.9836 / 11
Linear fitting
16.0 ± 1.3
0.011
10 - 40
R = 0.979 / n = 5
SWV
101.4 ± 16.1
311.6 ± 68.3
0.325
0.9861 / 12
276.3 ± 11.9
0.012
10 - 80
R = 0.993 / n = 9
111
GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN POPESCU
CONCLUSIONS
This work describes a simple and reproducible way to prepare a
modified electrode for H2O2 detection, based on the hemin adsorption on the
graphite surface. The electrochemical characterization of the G/Hm electrode,
performed by using CV and SWV measurements, allowed establishing the
influence of the experimental conditions (scan rate, pH and duration of use) on
the electrode performances. Additionally, it was confirmed that the immobilized
hemin is involved in a quasi-reversible 1e−/1H+ redox process, with the
features of a surface confined species. The electrocatalytic behavior of
G/Hm modified electrode for H2O2 electroreduction recommends it as a
promising transducer for sensors and biosensors construction.
EXPERIMENTAL SECTION
Reagents
Hemin, iron (III) protoporphyrin (IX) chloride (Hm), tris(hydroxymethyl)
aminomethane (TRIS) and H2O2 (30%) were purchased from Fluka, Sigma
and Merck, respectively. A stock solution of 5 mM Hm was prepared by
dissolving the appropriate amount of salt in 0.05 M TRIS chloride buffer (pH
10.5). The 0.1 M phosphate buffer solution (PB, pH 8.0) was prepared from
0.05 M KH2PO4 and 0.05 M K2HPO4 (Sigma). The pH of PB was adjusted
by using HCl and NaOH (Reactivul-Bucharest). Deionized water was used
for preparing all solutions.
Equipments
All electrochemical measurements were carried out using a computer
controlled voltammetric analyzer (Autolab-PGSTAT 10 EcoChemie, The
Netherlands).
A standard single-compartment three electrode cell was equipped
with a Pt counter electrode, a Ag/AgCl,KClsat reference electrode (Radiometer,
France), and the working electrode made of spectral graphite (RingsdorffWerke Gmbh, Bonn-Bad Godesberg, Germany).
In order to remove the dissolved oxygen, highly purified argon gas
was purged into the working solution for at least 15 minutes prior to the
experiment. Additionally, the argon flow was kept over the solution during all
time of measurements. All experiments were performed at room temperature
(25 ± 2 °C).
A combined glass electrode connected to a digital pH meter (Hanna
Instruments HI 1230) was used for the pH measurements.
112
ELECTROCHEM. BEHAVIOR OF THE HEMIN MODIFIED GRAPHITE ELECTRODE FOR H2O2 DETECTION
Preparation of G/Hm modified electrode
Before Hm deposition, the graphite disc electrode (3 mm diameter)
was polished by using wet emery paper (320 and P1200C grit), until a smooth
surface was obtained. Then, the electrodes were ultrasonicated for 2 minutes.
The cleanness of the graphite electrode surface was validated by performing
CV measurements in 0.1 M PB (pH 7), between -0.6 and 0 V vs. Ag/
AgCl,KClsat and using a scan rate of 20 mV/s.
The G/Hm modified electrode was prepared by dropping 5 μL of 5
mM Hm solution on the graphite surface. Further, the electrode was dried in
air by keeping it during the night. Between measurements, the modified
electrodes were at 4 °C.
ACKNOWLEDGEMENTS
The authors acknowledge the financial support from ID_PCCE_
129/2008 (NANOBIOFUN) grant.
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GEORGETA MARIA MARES, GRAZIELLA LIANA TURDEAN, IONEL CĂTĂLIN POPESCU
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18. J. Yang, N. Hu, J.F. Rusling, Journal of Electroanalytical Chemistry, 1999, 463, 53.
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114
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 115 – 125)
(RECOMMENDED CITATION)
DETERMINATION OF COBALT AND NICKEL AFTER
MODIFIED-COLD-INDUCED AGGREGATION
MICROEXTRACTION BASED ON IONIC
LIQUID IN HAIR AND WATER SAMPLES
FARIBA TADAYONa*AND MAHNOOSH HANASAEIa
ABSTRACT. Modified-cold-induced aggregation microextraction(M-CIAME)
as a separation and preconcentration method for Co+2 and Ni+2 ions
determination based ionic liquid (IL) coupled to UV-Vis spectrophotometry
is proposed. Cobalt and nickel were complexed with4-(2-pyridylazo)resorcinol (PAR) as a chelating at pH 6. Then 60µL of 1-Hexyl-3methylimidazoliumhexafluorophosphate [CMIM][PF6] was injected to 10mL
of sample solution. Afterward, the mixture was cooled in an ice bath and
complex extracted in to ionic liquid phase. After centrifuging the extractant
phase was analyzed using a spectrophotometric detection method.Several
factors influencing the microextraction efficiency of Co+2 and Ni+2 ions such
as: pH, concentration of chelating agent, extractant phase volume,
extraction time and interfering effect, have been investigated. Under the
optimum conditions, the detection limits (LODs) of the method were5.9 and
5.87 ngL-1 for Co+2 and Ni+2, with the relative standard deviations (RSDs)
for 59 ngL-1 (n=4) of Co+2 and Ni+2 were 1.85% and 1.24%. The developed
method was applied to the determination of trace cobalt and nickel in water
and hair samples with satisfactory results.
Keywords: Cold-induced aggregation microextraction, Ionic Liquid, Cobalt,
Nickel, UV-Vis spectrophotometry.
1. INTRODUCTION
The determination of trace amounts of cobalt and nickel in biological
and environmental samples are getting increasingly important in contamination
monitoring studies. Nickel is the metal component of the enzymeurease [1]
and a necessary partaker of metabolism of plants and some animals [2].
a
Department of Chemistry, North Tehran Branch, Islamic Azad University, Tehran, Iran.
* Email:F_tadayon@iau-tnb.ac.ir. Fax:(98)(21)22949650; Tel(98)(21)22222263
FARIBA TADAYON, MAHNOOSH HANASAEI
Also, cobalt is an essential trace element in nature,having an important role
in many body functions, as a component of vitamin B12[3]. However, if both
of metals ingest in high levels, these could be harmful to human health. UVVis spectrophotometry is relatively simple, cheap and available technique in
many laboratories for heavy metal determinations. In the determination of
traces of cobalt and nickel in biological and environmental samples, serious
interferences often occur owing to matrix components. Therefore, several
preconcentration methods have been reported for the separation and
preconcentration of Co and Ni ions, such as: dispersive liquid–liquid
microextraction (DLLME) [4-5], in situsolvent formation microextraction(ISFME)
[6], classical liquid–liquid extraction(LLE) [7-8], Solidified floating organic
drop microextraction (SFODME) [9], solid phase extraction(SPE) [10-12],
cloud point extraction(CPE) [13-16] and liquid phase microextraction (LPME)
[17]. Also preconcentration is a very important issue for obtaining of low limits
of detection. Modified-cold-induced aggregation microextraction(M-CIAME) is a
highly sensitive, efficient and rapid method for the preconcentration and
determination of traces of organic and inorganic compounds in several samples.
So it can easily settle a salt content of up to40% [18-19]. This procedure can
effectively decrease the detection limit while eliminating matrix interferences
[20-21].
Ionic liquids (ILs) are salts that are usually composed of organic or
an inorganic anions and either large asymmetric organic cations. They as
replacement solvents in the sample preparation, due to their unique chemical
and physical properties, such as: negligible vapor-pressure, high stability,
good extractability for metal ions [22-24]. ILs are regarded to have the potential
to be alternative reaction media for" Green Chemistry"[25]. In this work, a
green preconcentration and extraction of Co+2and Ni+2ions with complexation
were carried out using 4-(2-pyridylazo)-resorcinol(PAR) as a chelating and
an ion liquid(1-hexyl-3-methylimidazolium hexafluorophosphate [CMIM][PF6]) as
an extractant solvent based on modified-cold-induced aggregation microextraction
(M-CIAME). This was followed by UV-Vis spectrophotometry.
2. RESULTS AND DISCUSSION
In this study, one variable at a time optimization was used to obtain
the optimum conditions for the M-CIAME based IL. These conditions for
preconcentration and determination of cobalt and nickel ions were: pH,
volume of IL as an extractant, the concentration of the chelating agent, extraction
time, centrifuge condition, salts concentration, which were investigated and
optimized in order to achieve a high recovery and enrichment factor.
116
DETERMINATION OF COBALT AND NICKEL AFTER MODIFIED-COLD-INDUCED AGGREGATION
2.1. Effect of pH
pH plays an important and unique role on complex formation and
subsequent extraction, as it defines the charge of the complex. The effect
of pH on the formation of complex for cobalt and nickel was studied in the
range of 2–9. Absorbance increased in the range 2-6 and then started to
decrease, because PAR activity decreases in the acidic qualification due to
protonation of oxygen and nitrogen. The results illustrated in Fig.1 showed
that the absorbance at pH of 6was much stronger. Therefore, samples and
standards were adjusted at pH6 before M-CIAME based IL procedure.
Figure 1. Effect of pH on cobalt and nickel extraction: sample volume, 10 mL;
cobalt and nickel concentration, 59 ngL-1.;PAR concentration,10-4 M;
IL volume, 65µL;extraction time, 10min.
2.2. Effect of chelating agent concentration and IL volume
The influence of the amount of PAR on extraction efficiency of Co+2
and Ni were studied and the experimental results are shown in Fig2. The
absorbance Co+2 and Ni+2 incised by increasing the PAR concentration up
to 4×10-4 molL-1 of PAR and then decreased. So, a concentration of 4×10-4
molL-1 was chosen as the optimum PAR concentration in order to achieve
the highest possible extraction efficiency.
The volume of [CMIM][PF6] that is used in this preconcentration
procedure is a critical factor to obtain high extraction efficiency. Therefore,
the effect of [CMIM][PF6] volume on the performance of the microextraction
procedure was studied within the range of 10-100 µL. By increasing the
[CMIM][PF6] volume, the absorbance of Co+2 and Ni+2 initially increased up
+2
117
FARIBA TADAYON, MAHNOOSH HANASAEI
to about 60-70µL of [CMIM][PF6] and then started to decrease(Fig. 3).
Thus, in order to achieve a good enrichment factor, low viscosity, 60 and70
µLof IL as optimum were chosen for Co+2 and Ni+2 respectively.
Figure 2. Effect of concentration PAR on cobalt and nickel extraction: sample
volume, 10 mL;cobalt and nickel concentration, 59 ngL-1; pH 6;
IL volume, 65µL; extraction time, 10min.
Figure 3. Effect of IL volume on cobalt and nickel extraction: sample volume, 10 mL;
cobalt and nickel concentration, 59 ngL-1.; pH6; PAR concentration,
4×10-4 M; extraction time, 10min.
118
DETERMINATION OF COBALT AND NICKEL AFTER MODIFIED-COLD-INDUCED AGGREGATION
2.3. Effect of temperature and extraction time
Optimal temperature is necessary to complete reactions, and to achieve
easy and complete phase separation and preconcentration as efficient as
possible [26]. Before shaking a solution containing IL, they were heated in
the range of 20–60°C. So the temperature of 50°C for 4min was chosen.
Because that the increase of temperature has no suitable effect up on the
extraction efficiency.
In M-CIAME based IL, the extraction time is defined as the interval
time between finishing the disruption of[CMIM][PF6] and starting to centrifuge.
Hence, extraction time plays an important role in this new procedure. In
order to have excellent precision and high speed, it is essential; to select an
extraction time that guarantees the attainment of equilibrium between aqueous
and IL phase and maximize the extraction of analyte. The effect of extraction
time was evaluated in the range of 5–25min. Fig.4 shows that the amount of
complex extracted into IL phase increased with the increase of extraction time
to15min. Therefore, a extraction time of 15min was selected in this work.
Figure 4. Effect of extraction time on cobalt and nickel extraction: sample
volume,10 mL;cobalt and nickel concentration, 59 ngL-1.; pH6;
PAR concentration, 4×10-4 M; IL volume, 60µL.
2.4. Effect of centrifuge condition and salt content
The effect of centrifugation rate on the absorbance was studied in
the range of 1000–6000rpm. It was found that over 4000rpm, IL-phase
completely settled and a centrifugation time of 5 min at 5000rpm was selected
for subsequent experiments, due to complete separation occurred at this time.
119
FARIBA TADAYON, MAHNOOSH HANASAEI
The effect of salt concentration on the extraction of Co+2 and Ni+2 was
studied in the presence of NaNO3 (10-60%W/V). Absorbance of Co+2 and
Ni+2 decreased rapidly by increasing the salt concentration due to increase
in solubility of [CMIM][PF6]. Thus, concentration of 10% and 20% NaNO3
(wv-1) were selected for Co+2 and Ni+2respectively in this work (Fig.5).
Figure 5. Effect of NaNO3 on cobalt and nickel extraction:sample volume, 10 mL;
cobalt and nickel concentration, 59 ngL-1.; pH6; PAR concentration,
4×10-4 M;IL volume, 60µL; extraction time, 15min.
2.5. Interference study
The effect of diverse ions on the determination of Co+2 and Ni+ were
studied according to the abovedescribed procedure. For this purpose,
solution of 59 ngL-1 of studied analyte containing the corresponding
interfering ions were prepared and operated according to the suggested
procedure. The tolerable limit were defined the largest amount of foreign
ions that produced an error not exceeding5% in the determination of Co+2
and Ni+2. Most of cations and anions examined did not interference with the
microextraction and determination of Co+2 and Ni+2. The recoveries of Co+2
and Ni+2 were almost quantitative in the presence of all interfering ions in
experiments, shown in Table1. All studied ions were found not interference
from the coexisting ions for the determination of Co+2 and Ni+2. Only Mn+2
interfered with the determination of Ni+2 in this experiment.
120
DETERMINATION OF COBALT AND NICKEL AFTER MODIFIED-COLD-INDUCED AGGREGATION
Table 1. Effect of foreign ions the recovery of cobalt and nickel(59 ngL-1)
92.3
Molar
ratio(Ion/Ni+2)
1
Foreign
ion
Cr3+
Co
recovery(%)
92.69
Molar
ratio(Ion/Co+2)
1
Foreign
ion
Cr3+
88
1
Mn2+
97.46
1
Mn2+
91.42
98.81
100
1
Mg2+
Co2+
104
98.41
100
1
Mg2+
Ni2+
99.4
10
Cu2+
96.82
10
Cu2+
93.19
1000
Na+
95.23
1000
Na+
94.97
100
K+
101
100
K+
Ni recovery(%)
2+
94.37
98.81
1
10
Pb
Fe3+
95.87
102
1
10
Pb2+
Fe3+
103
100
Hg2+
101
100
Hg2+
97.63
100
Cl-
103
100
Cl-
90
100
104
100
98.22
100
95.2
100
N
S
N
S
Table 2.1. Determination of Co+2 and Ni+2inTap water
Metal
Added(ngL-1)
Found
a
mean± SD
UV-Vis(ngL-1)
Recovery
(%)
Found
mean±SD (ET-AAS)
(ngL-1)
Co
0
0. 59±0.017
-
-
59
61.06±0.06
102.4
63.18
0
0.587±0.026
-
-
60.5±0.064
102
59.11
Ni
a
58.7
Standard deviation (n=4)
Table 2.2. Determination of Co+2 and Ni+2 in human and cow hairs(n=4)
Found
mean± SD
-1
UV-Vis(µgg )
Found mean±SD
(ET-AAS) (µgg-1)
Metal
Sample
Co
Human hair
1.65±0.07
1.70
Cow hair
1.21±0.095
1.18
Human hair
1.83±0.054
1.82
Cow hair
1.42±0.086
1.46
Ni
121
FARIBA TADAYON, MAHNOOSH HANASAEI
2.6. Figures of merit
Under the optimized experimental conditions,some parameters were
investigated. The calibration curves were observed to be linear in the
concentration range of(0.058-590µgL-1) of Co+2 and Ni+2. The correlation
coefficient of the calibration curve equations was higher than0.990 for all
elements. The detection limits calculated according to three times the
standard deviation of the blank signals with the preconcentration step were
5.9 and 5.87 ngL-1for Co+2 and Ni+2respectively. Extraction recovery(ER)
was calculatedaccording to the following given equation [29]:
Equation.1
%ER=
100
Enhancement of factors was obtained from the slope ratio of the
calibration curve after and before preconcentration. The analytical characteristics
of the methods are summarized in Table 3.
Table 3. Analytical characteristics of modified CLAME method
Parameter
Co+2 with preconcentration
Ni+2 with preconcentration
0.997
0.995
Correlation coefficient(R2)
-1
Limit of detection (ngL )
5.9
5.87
Enrichment factor(EF)
74
79.05
RSD % (n=4)
1.85
1.24
Extraction recovery (ER)
94
101
3. CONCLUSIONS
In this study, a new method of Modified-cold-induced aggregation
microextraction(M-CIAME) based- ionic liquid solvent was successfully
used for preconcentration and determination trace of cobalt and nickel by
UV-Vis spectrophotometry in environmental and biological samples with
good accuracy and reproducibility. This method is simple, environmentally
friendly, selective, fast, safe and robust against very high content of salt
(upto40%). Also our proposed method requires smallest volume of solvent
while having good LOD and enhancement factor. This developed method was
employed to determine cobalt and nickel ions in biological and environmental
samples with satisfactory recovery.
122
DETERMINATION OF COBALT AND NICKEL AFTER MODIFIED-COLD-INDUCED AGGREGATION
4. EXPERIMENTAL SECTION
4.1. Apparatus
A lambda 25 UV-Vis spectrometer was purchased from Perkin-Elmer (USA).
A100µL microsyringe(Hamilton) was employed to inject ionic liquid extracting
phase to the sample solution. A (H-11 n) Kokusan Japan centrifuge was used
to accelerate the phase separation process and aJeio Tech BW-05G water
bath was used.
4.2. Reagents and materials
Standard stock solutions of Co+2 and Ni+2 at a concentration 1000 ppm
were prepared by dissolving appropriate amounts of the pure nitrate salts in
100mL double distilled water. Solutions of lower concentrations were prepared
daily by a suitable dilution of the stock solution with distilled water. Buffer
solution with pH6 was prepared from 1.8 molL-1sodium acetate solution and
0.1molL-1 acetic acid solution by mixing the appropriate volumes of the two
solutions and diluting to100mL. Acetic acid, sodium acetate and metal salts
are all of analytical grade and purchased from Merck Chemical Company.
A 4×10-4molL-1 PAR solution was prepared in deionized water and ethanol
50:50(v/v) (Aldrich Com) and also appropriate amounts of [CMIM][PF6] was
prepared in acetonitrile(Aldrich).
4.3. Modified CIAME procedure
For M-CIAME procedure 10mLof the sample solution containing Co+2 or Ni+2
and PAR (4×10-4 molL-1) were adjusted to pH6 (acetate/acetic acid buffer)
in a glass test tube with a conical bottom. Then, 60µL of [CMIM][PF6] with a
microsyringe was added to the solution. The tube was placed in a thermo
stated bath at 50°C for 4min. The next step, the mixture was cooled in an
ice bath for 10min, cloudy solution was immediately formed and metal ions
was extracted in to the fine droplets of IL . Then separation of two phases was
obtained by centrifugation for 5min at 5000rpm and IL-phase was diluted with
100µL ethanol and transferred to 350µL quartz cell for UV-Vis spectrophotometry
determination.
4.4. Real samples preparation
The method was applied to tap water, human hair and cow hair sample from
Tehran city. Standard hair samples were washed with 1% (w/v) (DDTC), 0.1M
HCl and deionized water. The hair samples were firstly washed with HCL then
one time with deionized water then with acetone and again one time with
deionized water. Afterwards, the hair sample dried in oven at 70°C for 8 hours
123
FARIBA TADAYON, MAHNOOSH HANASAEI
and then digested the next day [27]. Then 1g of washed hair samples were
weighted and transferred to a teflon bombs and 10mL of concentrated
HNO3(65%) was added. The samples were heated on a plate about 100°C
for 2h. After dissolution, the solution was allowed to cool and 5mL of H2O2
(30%) was added. The mixture was heated at(80°C for 2h). After digestion,
the sample was diluted to final volume with deionized water and was treated
according to the given procedure[28]. The results are show in Table2.
ACKNOWLEDGMENTS
With special thanks of Ms. Vahideh Mohajeri and Ms. Mahtab
Rezazadeh that supported us in this project.
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STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 127 – 132)
(RECOMMENDED CITATION)
SECOND-CONNECTIVITY INDEX OF CAPRA-DESIGNED
PLANAR BENZENOID SERIES Can(C6)
MOHAMMAD REZA FARAHANIa*, KATALIN KOLLOb,
MIRANDA PETRONELLA VLADc
ABSTRACT. The benzene is a key molecule in organic chemistry. In this
paper, we focus on the structure of the Capra-designed planar benzenoid
series Can(C6) and compute the 2-connectivity index in the general case of
this family of benzenoids.
Keywords: Randić connectivity index, Sum-connectivity index, Benzenoid,
Capra, Second connectivity index.
INTRODUCTION
Let G=(V,E) be a simple connected graph with the vertex set V(G)
and the edge set E(G). Molecular connectivity indices are related to the
accessibility to the reaction centres. In identifying the accessibility perimeters,
we have to recognize the atom degrees. The generalized connectivity index
is the m-connectivity index, defined as:
m
χ (G ) =
vi vi
...v
1 2
where v i v i v i
1
2
m +1
1
i m +1
d i d i ...d i
1
2
m +1
runs over all paths of length m in G and di is the degree
of vertex vi ∈V (G) . In particular, 1-connectivity index (the original Randić
index) can be written as
1
χ (G ) =
di d j
e = ( i , j )∈E ( G )
a
b
c
Department of Mathematics of Iran University of Science and Technology (IUST), Narmak,
Tehran 16844, Iran. Mr_Farahani@Mathdep.iust.ac.ir
Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, 400028, Aranj
Janos 11, Cluj, Romania. katalinkollo@gmail.com
Dimitrie Cantemir University, Bucharest, Faculty of Economic Sciences, No 56 Teodor Mihali
Street, 400591, Cluj Napoca, Romania, mirandapv@yahoo.com
MOHAMMAD REZA FARAHANI, KATALIN KOLLO, MIRANDA PETRONELLA VLAD
The Randić Connectivity Index was introduced by Milan Randić [1, 2]
in 1975. For more study, see references [3-9]. The 2-connectivity index is
defined as follows:
2
χ (G ) =
v i 1v i 2v i 3
1
d i1 d i 2 d i 3
The Randić and second-order connectivity indices (or 2-connectivity
index) represents the molecular accessibility areas and volumes, respectively.
The benzene is a usual chemical molecule in chemistry with a
distinctive structure. The benzene is a key molecule in chemistry and related
sciences, with various applications in different fields.
We use the Capra-designed operation to generate new structures
called benzoids. This operation was introduced by M.V. Diudea and used in
many papers [10-19], see Figure 1.
Figure 1. The first two graphs Ca1(C6) and Ca2(C6) from the Capra of planar
benzenoid series and molecular graph benzene C6=Ca0(C6).
RESULTS AND DISCUSSION
Let dij denote the number of edges in G connecting vertices of
degrees i and j; clearly, dij=dji. Define dijk as a number of 2-edges paths with
3 vertices of degree i, j and k, respectively. It is obvious that dijk =dkji and the
number of 2-edge paths for all possible i, j and k is denoted by d2(G).
Theorem 1. [16] Consider the graph G=Cak(C6), k ∈N is the Capradesigned planar benzenoid series. Then Randić connectivity index χ(Cak(C6))
k
k −1
is equal to 2(7 ) + (4 6 − 1)3 + 1 .
2
Theorem 2. Second-connectivity index of Cak(C6) is computed as:
3 2
2 3 k 7 2 5 3 k
2
−
7 +
χ (Cak (C 6 )) =
3 + 3 −
.
2
3
18
6
128
SECOND-CONNECTIVITY INDEX OF CAPRA-DESIGNED PLANAR BENZENOID SERIES Can(C6)
Proof of Theorem 2. Let G=Cak(C6) be the Capra-designed planar
benzenoid series. Since, this graph has 2×7k+3k+1+1 vertices and 3×7k+3k+1
edges (denoted by nk and ek, respectively). At the first, we determine the
number of 2-edge paths d 2( k ) (G ) in G=Cak(C6). So, we attend to dijk for every
arbitrary vertices i, j and k; and obviously the number of dijk is dependent of
the degree of vertex j (denoted by dj). On the other hand, the number of 2edge paths passing the vertex j of G is equal to (dj-1)+(dj-2)+
…+(2)+(1)=
d j (d j − 1)
2
dv (dv −1) There are two
.
2
v ∈V (G )
and obviously d 2(k ) (G ) =
partitions V2 ={v ∈V (Cak (C6 ))| dv = 2} and V 3 = {v ∈V (Cak (C6 ))| dv = 3}, with size
v 2( k ) =|V2|= 3k+1+3 and v 3(k ) =|V3|=2(7k-1) respectively. Then,
d 2( k ) (Cak (C 6 )) =
d v (d v − 1)
2
v ∈V (Cak (C 6 ))
=
3(3 − 1)
2(2 − 1)
+
2
2
v ∈V 3
v ∈V 2
= 3 × 2(7 k − 1) + 1× 3(3k + 1)
=6×7k+3k+1+3
Now, according to the Capra-designed structure (Figure 2), we see
that there exist two kinds of 2-edge paths d 2( k ) (Cak(C6)): internal 2-edge
paths and external 2-edge paths. Thus we have:
d 2( k ) (Cak (C6 )) =
k
6(7
)
6ζ k
k +1
3
−3
+
v( k ) − 6
2
internal 2−edge paths
external 2−edge paths
where ζk is the number of cycles with length six and is equal to 7k.
Alternatively, the number of internal 2-edge paths of Cak(C6) is equal to
d 2(k )(in ) =6 ζk=6(7k). The number of external 2-edge paths of Cak(C6) is equal
to d2(k )(ex ) =3k+1-3, being obtained from the sequence:
( k −1)
0, 6, 24, 6×13,..., d 2(k )(ex ) = 6(d 2
2
(ex )
+ 1).
In proving theorem 2 we have to calculate the number of 2-edges
(k )
(k )
(k )
(k )
, d 333
from internal 2-edge paths and d 323
, d 232
from external 2paths d 223
edge paths:
d 2( k ) (Cak(C6))=
(k )
(k )
(k )
d 223
+ d 333
+ d 233
+
internal 2 −edges paths
(k )
(k )
d 232
+ d 323
external 2 −edges paths
129
MOHAMMAD REZA FARAHANI, KATALIN KOLLO, MIRANDA PETRONELLA VLAD
Figure 2. The internal 2-edges paths and external 2-edges paths of Ca2(C6).
(0)
(0)
(0)
(0)
(0)
It is obvious that, in C6=Ca0(C6), d 223
= d323
= d 232
= d 233
= d333
= 0,
6
(0)
2
d222
=6 and
χ (C a 0 (C 6 )) =
= 2.1213
2×2×2
(1)
(1)
(1)
(1)
(1)
=2×6, d 323
= 0, d 232
= 6, d 233
=2×6 and d333
=18. Thus
Next, for Ca1(C6), d 223
12
6
12
0
18
2
χ (Ca1 (C 6 )) =
+
+
+
+
= 11.4886.
2× 2×3
2 × 3× 2
2 × 3× 3
3× 2 × 3
3× 3× 3
Now, by simple calculation and induction on n=1,2,3,…,k, (see
Figure 1., 2. and 3.) we show that for G=Cak(C6)
(0)
(1)
(2)
(3)
(k )
d 223
= 0, d 223
= 12, d 223
= 24, d 223
= 2(33 + 3) = 60, …, d 223
= 2(3k + 3) = 2e 4( k ) .
internal
d
(0)
323
(1)
323
= 0, d = 0, d
(2)
323
= 12, d
(3)
323
k
k +1
k
= 24, …, d ( k ) = v ( k ) − 2e ( k ) = 3 +3−2(3 +3) =3 -3.
323
2
4
external
(k −1)
d
(0)
(1)
(2)
12
k
(k )
(k −1)
(3)
d232
= 0, d 232
= 6, d 232
= 12, d 232
= 6( 232 −1) = 3d232
− 6 =3 +3.
= 6( −1) = 30, …, d232
2
2
d
(0)
233
= 0, d
(1)
233
= 0 + 2
× 6 = 12, d
ex
…,
(k )
233
d
where
130
(k )
233(ex)
=d
(2)
233
in
= 2
× 6 + 6
× 6 = 48, d
ex
in
(3)
232
= 8
× 6 +18
× 6 = 156,
ex
in
(k )
k
233(in) =6(3 -1)
+d
k +1
(k )
(k )
(k )
d 233
− 3 − (3k + 3) = 6(3k −1 − 1)
(ex ) = d 323 (ex ) − d 232 (ex ) = 3
( k −1)
(k )
d 233
( in )
( k −1)
k
) = 3d 233
d 233 (in ) = 6(
( in ) = 4(3 )
2
SECOND-CONNECTIVITY INDEX OF CAPRA-DESIGNED PLANAR BENZENOID SERIES Can(C6)
(0)
d333
= 0,
(k )
333
d
=d
(k )
2
−d
(1)
d 333
= 18,
(2)
d 333
= 228,
(k )
233 (ex )
(k )
232 (ex )
−d
(k )
233 (in )
−d
−d
(k )
323 (ex )
(3)
d 333
= 1866,
−d
…,
(k )
223 (in )
internal
= 6(7k ) +3k +1 −3−2(3k ) −6−3k +3−6(3k ) +6−3k −3 =6×7k-7(3k)-3
In totally,
6(7k ) − 7(3k ) − 3
ijk = 333
(k )
internal 2 − edge paths
k
ijk = 223
2e4 = 2(3 + 3)
(k )
dijk
= 6(3k −1 −1) + 4(3k ) = 6(3k −1)
ijk = 233
(k )
(k )
k
ijk = 323
v2 − 2e4 = 3 − 3
external 2 − edge paths
3k + 3
ijk = 232
where e 4( k ) = 3k − 3 is the number of edge of Cak(C6) with end-point and
first-point of degree 2. Therefore:
2
χ (Cak (C 6 )) =
v v v
i1 i 2 i 3
1
di di di
1
2
3
2(3k + 3) + 3k + 3 3k − 3 + 6(3k ) − 6 6(7k ) − 7(3k ) − 3
=
+
+
12
18
27
k +1
k
k
k
3 +9
7(3 ) − 9
6(7 ) − 7(3 ) − 3
=
3+
2+
3
6
6
9
(3k +2 + 27 + 12(7k ) −14(3k ) − 6) 3 + (7(3k +1 ) − 27) 2
=
18
k
k
((12(7 ) − 5(3 ) + 21) 3 + (7(3k +1 ) − 27) 2)
=
.
18
The second-connectivity index of Cak(C6) is equal to
2
χ (Cak (C 6 )) =
2 3 k 7 2 5 3 k
3 2
−
7 +
3 + 3 −
.
3
18
2
6
Thus, we completed the proof of Theorem 2.
We can use formula for 2χ(Cak(C6)) to compute some numerical
examples:
2
^
χ (Cak (C 6 )) = 1.1547(7 k ) + 1.1688(3k ) − 0.3892.
Examples for 2χ(Cak(C6)) for k=1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 100
are given in Table 1.
131
MOHAMMAD REZA FARAHANI, KATALIN KOLLO, MIRANDA PETRONELLA VLAD
Table 1. Values of second-connectivity index 2 χ (Cak (C6 ))
k
1
2
3
4
5
10
20
30
40
50
100
Number of Vertices
24
123
768
5046
34344
565127646
1. 5958454306×1017
4. 5078680582×1025
1. 2733611522×1034
3. 596330085×1042
6. 4689530192×1084
Number of edges
30
174
1110
7446
51150
847602894
2. 3937680935×1017
6. 6718020873×1025
1. 9100417283 ×1034
5. 3953951279 ×1042
9. 7034295289 ×1084
2-connectivity index
11. 2001
66. 7103
427. 2305
2866. 7183
19690. 6721
326243186. 1023
9. 2136133969×1016
2. 602617623×1025
7. 3517506121 ×1033
2. 0766875847 ×1042
6. 4689530192 ×1084
RE F E R E N CE S
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
M. Randić and P. Hansen. J. Chem. Inf. Comput. Sci. 1988, 28, 60.
M. Randić. J. Am. Chem. Soc. 1975, 97, 6609.
N. Trinajstić. Chemical Graph Theory. CRC Press, Boca Raton, FL, 1992.
P. Yu. J. Math. Study Chinese. 1998, 31, 225.
M.R. Farahani. Acta Chim. Slov. 2012, 59, 779–783.
E. Estrada. J. Chem. Inf. Comput. Sci. 1995, 35, 1022.
E. Estrada. Chem. Phys. Lett. 1999, 312, 556.
Z. Mihali and N. Trinajstić. J. Chem. Educ. 1992, 69(9), 701.
D. Morales and O. Araujo. J. Math. Chem. 1993, 13, 95.
M. Goldberg. Tohoku Math. J. 1937, 43, 104.
A. Dress and G. Brinkmen. MATCH Commun. Math. Comput. Chem. 1996, 33,
87.
M.V. Diudea, M. Ştefu, P.E. John, and A. Graovac, Croat. Chem. Acta, 2006,
79, 355.
M.V. Diudea, J. Chem. Inf. Model, 2005, 45, 1002.
M.R. Farahani and M.P.Vlad. Studia Universitatis Babes-Bolyai Chemia. 2012,
57(4), 55-63.
M.R. Farahani. J. Applied Math. & Info. 2013, 31(5-6), in press.
M.R. Farahani and M.P.Vlad. Studia Universitatis Babes-Bolyai Chemia. 2013,
58(2), accepted.
M.R. Farahani. Polymers Research Journal. 2013, 7(3), In press.
M.R. Farahani. Advances in Materials and Corrosion. 2012, 1, 61-64.
M.R. Farahani. Chemical Physics Research Journal. 2013, In press.
132
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 133 – 142)
(RECOMMENDED CITATION)
COMPUTING FIRST AND SECOND ZAGREB INDEX, FIRST
AND SECOND ZAGREB POLYNOMIAL OF CAPRADESIGNED PLANAR BENZENOID SERIES Can(C6)
MOHAMMAD REZA FARAHANIa, MIRANDA PETRONELLA VLADb
ABSTRACT. In graph theory, various polynomials and topological indices are
known, as invariants under graph automorphism. In this paper, we focus on
the structure of Capra-designed planar benzenoid series Cak(C6), k≥0 and
compute on it several topological indices and polynomials: first and second
Zagreb polynomials and their corresponding indices.
Keywords: Capra Operation, benzenoid series, First Zagreb index, second
Zagreb index, First Zagreb polynomial, second Zagreb polynomial.
INTRODUCTION
Let G=(V,E) be a molecular graph with the vertex set V(G) and the
edge set E(G). |V (G)|=n, |E(G)|=e are the number of vertices and edges. A
molecular graph is a simple finite graph such that its vertices correspond to
the atoms and the edges to the chemical bonds. The distance d(u,v) in the
graph G is the number of edges in a shortest path between two vertices u
and v. The number of vertex pairs at unit distance equals the number of
edges. A topological index of a graph is a number related to that graph and
is invariant under graph automorphism.
Wiener index W(G) is the oldest topological index [1-5], which has
found many chemical applications. It is defined as:
W (G ) =
a
1
d (u ,v )
2 u ∈V (G ) v ∈V (G )
Department of Mathematics of Iran University of Science and Technology, (IUST), Narmak,
Tehran 16844, Iran. Mr_Farahani@Mathdep.iust.ac.ir
b
Dimitrie Cantemir University, Bucharest, Faculty of Economic Sciences, No 56 Teodor Mihali
Street, 400591, Cluj Napoca, Romania, mirandapv@yahoo.com
MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD
Hyper-Wiener index is a more recently introduced distance-based
molecular descriptor [6]:
WW (G ) =
1
1
1
d (u ,v ) + d (u ,v )2 ) = W (G ) + d (u ,v )2 .
(
2 u ∈V (G ) v ∈V (G )
2
2 u ∈V (G ) v ∈V (G )
Denote by d(G,k) the number of vertex pairs of G lying at distance k
to each other and by d(G) the topological diameter (i.e, the longest
topological distance in G). Then Wiener and hyper-Wiener indices of G can
be expressed as [7, 8]:
1 d (G )
i .d (G , i )
2 i =1
W (G ) =
W W (G ) =
1 d (G )
i (i + 1)d (G , i ).
2 i =1
Other oldest graph invariant is the First Zagreb index, which was
formally introduced by Gutman and Trinajstić [9, 10]. It is denoted by M1(G)
and is defined as the sum of squares of the vertex degrees:
M 1 (G ) =
[d (u ) + d (v )]
d (v ) 2 =
v ∈V (G )
e =uv ∈E (G )
where dv is the degree of vertex v. Next, Gutman introduced the Second
Zagreb index M2(G) as:
M 2 (G ) =
[d (u ) × d (v )]
e =uv ∈E (G )
Some basic properties of M1(G) can be found in ref. [9]. For a survey
on theory and applications of Zagreb indices see ref. [10]. Related to the
two above topological indices, we have the first Zagreb Polynomial M1(G,x)
and second Zagreb Polynomial M2(G,x), respectively. They are defined as:
M 1 (G , x ) =
x d (u ) +d (v )
x d (u )d (v )
e =uv ∈E (G )
M 2 (G , x ) =
e =uv ∈E (G )
There was a vast research concerning Zagreb indices and Wiener
index with its modifications [6] and relations between Wiener, hyper-Wiener
and Zagreb indices [9-26].
WHAT IT IS THE CAPRA OPERATION?
A mapping is a new drawing of an arbitrary planar graph G on the
plane. In graph theory, there are many different mappings (or drawing); one of
them is Capra operation. This method enables one to build a new structure
of a planar graph G.
134
COMPUTING FIRST AND SECOND ZAGREB INDEX, FIRST AND SECOND ZAGREB POLYNOMIAL…
Let G be a cyclic planar graph. Capra map operation is achieved as
follows:
(i)
insert two vertices on every edge of G;
(ii)
add pendant vertices to the above inserted ones and
(iii)
connect the pendant vertices in order (-1,+3) around the boundary
of a face of G. By runing these steps for every face/cycle of G, one
obtains the Capra-transform of G Ca(G), see Figure 1.
Figure 1. Examples of Capra operation on the square face
(top row) and mapping Capra of planar hexagon (bottom row).
By iterating the Capra-operation on the hexagon (i.e. benzene graph
C6) and its Ca-transforms, a benzenoid series (Figures 2 and 3) can be
designed. We will use the Capra-designed benzene series to calculate some
connectivity indices (see below).
This method was introduced by M.V. Diudea and used in many papers
[27-36]. Since Capra of planar benzenoid series has a very remarkable
structure, we lionize it.
We denote Capra operation by Ca, in this paper, as originally Diudea
did. Thus, Capra operation of arbitrary graph G is Ca(G), iteration of Capra
will be denoted by CaCa(G) (or we denote Ca2(G)) (Figures 2 and 3).
The benzene molecule is a usual molecule in chemistry, physics and
nano sciences. This molecule is very useful to synthesize aromatic compounds.
We use the Capra operation to generate new structures of molecular graph
benzene series.
Theorem 1. Let Ca(C6) be the first member of Capra of benzenoid series.
Then, Hosoya polynomial of Ca(C6) is equal to:
H(Ca(C6),x)=24+30x1+48x2+57x3+x54x4+45x5+30x6+12x7
and the Wiener index of Ca(C6) is equal to 1002.
135
MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD
Hosoya polynomial H(G) is equal to 1
2 u∈V (G ) v ∈V (G )
x d (u ,v ) . It is easy to
see that Wiener index is obtained from Hosoya polynomial as the first
derivative, in x=1.
Figure 2. The first two graphs Ca(C6) and Ca2(C6) from the Capra of planar
benzenoid series, together with the molecular graph of benzene
(denoted here Ca0(C6))
Figure 3. Graph Ca3(C6) is the third member of Capra
planar benzenoid series.
136
COMPUTING FIRST AND SECOND ZAGREB INDEX, FIRST AND SECOND ZAGREB POLYNOMIAL…
By these terminologies, we have the following theorem:
Theorem 2. Consider the graph G=Cak(C6) as the iterative Capra of planar
benzenoid series. Then:
First Zagreb polynomial of G is equal to
M1(Cak(C6),x)=(3(7k)-2(3k)-3)x6+4(3k)x5+(3k+3)x4
and the First Zagreb index is M1(Cak(C6))=18(7k)+12(3k)-6.
Second Zagreb polynomial of G is equal to
M2Cak(C6),x)=(3(7k)-2(3k)-3)x94(3k)x6(3k+3)x4
and the Second Zagreb index of G is M2(Cak(C6))=27(7k)+10(3k)-15.
RESULTS AND DISCUSSION
Capra transforms of a planar benzenoid series is a family of molecular
graphs which are generalizations of benzene molecule C6.
In other words, we consider the base member of this family is the
planar benzene, denoted here Ca0(C6)=C6=benzene. It is easy to see that
Cak(C6)=Ca(Cak-1(C6)) (Figures 2 and 3) [27-36]. In addition, we need the
following definition.
Definition 3. [21] Let G be a molecular graph and dv is the degree of vertex
v ∈V (G ). We divide vertex set V(G) and edge set E(G) of graph G to
several partitions, as follow:
∀i , δ < i < Δ,V i = {v ∈V (G ) | d v = i },
and ∀k , δ 2 ≤ k ≤ Δ 2 , E k* = {e = uv ∈ E (G ) | d v × d u = k }.
Obviously, 1 ≤ δ ≤ d v ≤ Δ ≤ n − 1 such that δ = Min {d v | v ∈V (G )} and
Δ = Max {d v | v ∈V (G )}. Now, we start to proof of the above theorem.
Proof of Theorem 2. Let G=Cak(C6) (k≥0) be the Capra planar benzenoid
series. By construction, the structure Cak(C6) collects seven times of structure
Cak-1(C6) (we call "flower" the substructure Cak-1(C6) in the graph Cak(C6)).
Therefore, by simple induction on k, the vertex set of Cak(C6) will have
7×|V(Cak(C6))|-6(2×3k-1+1) members. Because, there are 3k-1+1 and 3k-1
common vertices between seven flowers Cak-1(C6) in Cak(C6), marked by
full black color in the above figures. Similarly, the edge set E(Cak(C6)) have
7×|E(Cak(C6))|-6(2×3k-1+1) members. Since, there are 3k-1 and 3k-1 common
edges (full black color in these figures).
137
MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD
Now, we solve the recursive sequences |V(Cak(C6))| and
|E(Cak(C6))|. First, suppose nk=|V(Cak(C6))| and ek=|E(Cak(C6))| so
k
k
nk = 7nk −1 − 4(3
) − 6 and e k = 7e k −1 − 4 (3
). Thus, we have
òk
òk
n k = 7 n k −1 − 4 òk − 6
= 7(7 n k − 2 − 4òk −1 − 6) − 4òk − 6
= 7 2 n k − 2 − 7(4òk −1 + 6) − (4òk + 6)
= 73 n k −3 − 7 2 (4òk − 2 + 6) − 7(4òk −1 + 6) − (4òk + 6)
= 7i n k −i − 7i −1 (4òk −( i −1) + 6) −…− 7(4òk −1 + 6) − (4òk + 6)
= 7 i n k −i −
i −1
7
j =0
j
( 4 òk − j + 6 )
k −1
= 7 k n k − k − 7i (4òk −i + 6)
i =0
k −1
k −1
i =0
i =0
= 7 k n 0 − 4 7i 3k −i − 6 7i .
(1)
where n0=6 is the number of vertices in benzene C6 (Figure 2) and
k
k −1
6 i = 0 7i is equal to 6(7 −1) = 7k −1. On the other hand, since
7 −1
n
(α − β )α i β n −i = (α − β )(α 0 β n + α 1β n −1 +…+ α n −1β 1 + α n β 0 ) = (α n +1 − β n +1 ).
Hence
i =0
k −1
i
7 3
k −i
= (7 0 3 k + 713 k −1 + … + 7 k − 2 3 2 + 7 k −131 ) + 7 k 30 − 7 k 30
i =0
7 k +1 − 3k +1
− 7 k 30
1
1
7 −3
k +1
7 − 3k +1 − 4(7 k )
=
4
k
3(7 ) − 3(3k )
=
4
3
= (7 k − 3k ).
4
=
138
(2)
COMPUTING FIRST AND SECOND ZAGREB INDEX, FIRST AND SECOND ZAGREB POLYNOMIAL…
Therefore, by using equations (1) and (2), we have
3
k
k+1
nk = 6× 7k − 4 (7k − 3k ) + (7k −1) and ∀ k ≥ 0, nk=|V(Cak(C6))|=2×7 +3 +1.
4
By using a similar argument and (1), we can see that
e k = 7 e k − 1 − 4 òk = 7 2 e k − 2 − 7 ( 4 òk − 1 ) − 4 òk
= 7k ek
k −1
−k =0
− 4 7 i òk
i =0
k −1
−i
= 7 k e 0 − 4 7i 3k
−i
.
i =0
It is easy to see that, the first member of recursive sequence ek is
3
4
e0=6, (Figure 2). Now, by using (2), we have e k = 6 × 7 k − 4 (7 k − 3k ) and
the size of edge set E(Cak(C6)) is equal to: ek=|E(Cak(C6))|=3(7k+3k), ∀k ≥0.
Also, according to Figures 2 and 3, we see that the number of
vertices of degree two in the graph Cak(C6) (we denote by v 2( k ) ) is equal to
v ( k −1)
6 × 3 2 − 6 . The six removed vertices are the common ones between
6
the six flowers "Cak-1(C6)" with degree three. By using a similar argument
and simple induction, we have v 2( k −1) the numbers of edges of graph
(k )
Cak(C6), which are in the set E 4 or E 4* (denoted by e 4
).
v ( k −1)
Now, we solve the recursive sequence v 2( k ) = 6(3 2 − 1) and we
6
conclude v 2( k ) = 3v 2( k −1) − 6 = 3(3v 2( k − 2) − 6) − 6 = … = 3k v 2(0) − 6
k −1
3 .
i
i =0
It is obvious that, according to the structure of benzene, v2(0) = n0 = 6 .
Thus, v
(k )
2
3k − 1
k +1
= 6×3 − 6
= 3 + 3.
3 −1
k
Also, e 4( k ) =| E 4 |=| E 4* |= v 2( k −1) = 3k + 3 and according to the above
definition, it is obvious that, for Capra of planar benzenoid series G=Cak(C6)
we have two partitions:
V 2 = {v ∈V (Cak (C6 )) | dv = 2} and V 3 = {v ∈V (Cak (C 6 )) | d v = 3}, with the size
3k +1 + 3 and 2(7 k − 1), respectively.
139
MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD
On the other hand, according to the structure of Capra planar
benzenoid series Cak(C6), there are 2v 2( k ) edges, such that the first point of
them is a vertex with degree two. Among these edges, there exist v 2( k −1)
edges, of which the first and end point of them have degree 2 (the
members of E 4 or E 4* ).
Thus, e 5( k ) =| E 5 |=| E 6* |= 2v 2( k ) − 2e 4( k ) = 2v 2( k ) − 2v 2( k −1) . So, the size
of edge set E 5 and E 6* is equal to e5( k ) = 2(3k +1 + 3 − 3k − 3) = 4(3k )
Now, it is obvious that:
e 6( k ) =| E 6 |=| E 9* |= 3 ( 7 k + 3k ) − e 5( k ) − e 4( k )
= 3 × 7 k + 3k +1 − 4 × 3k − 3k − 3
= 3 × 7 k − 2 × 3k − 3
= 3(7k − 2(3k −1 ) − 1).
Now, we know the size of all sets V 2 ,V 3 , E 4 , E 4* , E 5 , E 6* , E 6 and E 9* .
So, we can calculate the First and Second Zagreb Polynomial of Capra
planar benzenoid series G=Cak(C6), as follow:
First Zagreb Polynomial of G=Cak(C6):
M 1 (G , x ) =
e ∈ E (G )
x d (u ) + d (v )
= e ∈E x 6 + e ∈E x 5 + e ∈E x 4
6
5
6
4
5
=| E 6 | x + | E 5 | x + | E 4 | x
4
= 3(7 k − 2(3k −1 ) − 1)x 6 + 4(3k )x 5 + 3(3k −1 + 1)x 4
Second Zagreb Polynomial of G = Cak (C 6 ) :
M 2 (G , x ) =
e ∈E (G )
x d (u )d (v ) =
x
e ∈E 9*
9
+
x
e ∈E 6*
6
+
x
4
e ∈E 4*
= 3(7k − 2(3k −1 ) − 1)x 9 + 4(3k )x 6 + 3(3k −1 + 1)x 4 .
Also, according to definition of First and Second Zagreb index, we
have:
M 1 (G ) =
140
∂M 1 (G , x)
|x =1 = 18(7 k − 2(3k −1 ) − 1) + 20(3k ) + 12(3k −1 + 1)
∂x
= 18(7 k ) + 12(3k ) − 6
COMPUTING FIRST AND SECOND ZAGREB INDEX, FIRST AND SECOND ZAGREB POLYNOMIAL…
and
M 2 (G ) =
∂M 2 (G , x)
|x =1 = 27(7 k − 2(3k −1 ) − 1) + 24(3k ) + 12(3k −1 + 1)
∂x
= 27(7 k ) + 10(3k ) − 15
Of course, by using |V2| and|V3|, we have
M 1 (G ) = (3k +1 + 3)22 + 2(7 k − 1)32 = 18(7 k ) + 12(3k ) − 6.
Thus, we completed the proof of the theorem 3.
ACKNOWLEDGMENTS
The first author is thankful to Dr. M. Alaeiyan and Dr. A. Aghajani of
Department of Mathematics, Iran University of Science and Technology
(IUST) for their precious support and suggestions.
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MOHAMMAD REZA FARAHANI, MIRANDA PETRONELLA VLAD
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142
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 143 – 150)
(RECOMMENDED CITATION)
ASSESSMENT OF AIR POLLUTION WITH SULPHUR
DIOXIDE FROM ELECTRIC ARC FURNACES
DANA – ADRIANA ILUŢIU – VARVARAa*, DAN RĂDULESCUb
ABSTRACT. The purpose of the paper constitutes the assessment of air
pollution with sulphur dioxide (SO2) from the electric arc furnaces. Experimental
procedure for determining SO2 emission levels during the steelmaking and
the sulphur dioxide concentrations variation diagrams with the melting
temperature of the three types of charges are presented. Sulphur dioxide has
a negative impact on the quality of the air, being responsible for generating
acid rain. The negative impact of sulphur dioxide manifests itself on the
steel works and on the population.
Keywords: air pollution, sulphur dioxide, electric arc furnace.
INTRODUCTION
The steelmaking in the electric arc furnace belongs to the category
of industrial processes with high degree of pollution because the following
pollutants are transferred in the air: carbon oxides, sulphur oxides, nitrogen
oxides, volatile organic compounds (VOC), particulate matter, dioxins and
furans [1].
Sulphur dioxide (SO2) forms sulphate aerosols that are thought to
have a significant effect on global and regional climate. Sulphate aerosols
reflect sunlight into space and also act as condensation nuclei, which tend
to make the clouds more reflective and change their lifetimes [2].
Sulphur emissions have grown rapidly and extensive researches have
documented a variety of effects on the environment [3]. Sulphur dioxide is
the primary cause of acid precipitation, which adversely affects natural systems,
agriculture and building materials. The sulphate aerosol particles formed as
a consequence of these emissions impair visibility and affect human health.
a
Universitatea Tehnică din Cluj – Napoca, Str. Memorandumului, Nr. 28, RO-400114 ClujNapoca, Romania, *corresponding author: dana.varvara@gmail.com
b
Universitatea de Medicină şi Farmacie Iuliu Haţieganu Cluj – Napoca, Facultatea de Medicină,
Str. Emil Isac, Nr. 13, RO-400023 Cluj-Napoca, Romania
DANA – ADRIANA ILUŢIU – VARVARA, DAN RĂDULESCU
Sulphur dioxide, dissolves in the water vapors from the air to form acids
and interacts with other gases and particles in the air to form particles
known as sulphates and other products that can be harmful to people and
their environment [4].
In Table 1, there are presented the health effects of respiratory exposure
to sulphur dioxide.
Table 1. Health effects of respiratory exposure to sulphur dioxide [5, 6, 7]
Exposure limits [ppm]
Health Effects
1-5
Threshold for respiratory response in healthy individuals
upon exercise or deep breathing
3-5
Gas is easily noticeable. Fall in lung function at rest and
increased airway resistance
5
Increased airway resistance in healthy individuals
6
Immediate irritation of eyes, nose and throat
10
Worsening irritation of eyes, nose and throat
10-15
Threshold of toxicity for prolonged exposure
>20
Paralysis or death occurs after extended exposure
150
Maximum concentration that can be withstood for a few
minutes by healthy individuals
Sulphur dioxide has a negative impact on the human health. Sulphur
dioxide penetrates the human organism through the respiratory system. At
high concentrations its absorption reaches up to 90% in the upper respiratory
tract and less in the lower parts of the respiratory system. During short-term
exposure to sulphur dioxide the respiratory system is mainly affected.
Population groups sensitive to sulphur dioxide exposure are children, elderly,
asthmatic patients, people suffering from cardiovascular diseases or chronic
lung diseases. Sulphur dioxide health effects are expressed in respiratory
disorders, lung diseases, lung immune protection disorder, aggravation of
existing lung and cardiovascular diseases. The asthmatic patients are ten
times more sensitive and sulphur dioxide than healthy people. Children,
suffering from asthma are particularly sensitive, and sulphur dioxide exposure
may lead to inflammatory lung diseases [1, 6, 8, 9].
The European Union (EU) defines the obligations to be met by
industrial activities with a major pollution potential. The objective is to avoid
or minimize polluting emissions in the atmosphere, water and soil, as well as
waste from industrial and agricultural installations, with the aim of achieving
a high level of environmental and health protection [10, 11, 12, 13].
144
ASSESSMENT OF AIR POLLUTION WITH SULPHUR DIOXIDE FROM ELECTRIC ARC FURNACES
The sources with sulphur dioxide generating potential in the electric
arc steelmaking are [9]: the metallic charge; additions of auxiliary materials;
first fusion pig iron (0.05 – 0.07% S); electric arc furnace atmosphere, when
using fuels containing sulphur.
RESULTS AND DISCUSSION
The composition of the charge I is presented in Table 2.
Table 2. The composition of the charge I
Charge
Painted plate
Zincked plate
First fusion pig iron
Plastics
Total
Composition [%]
50
20
27
3
100
Weight [g]
5
2
2.7
0.3
10
In Fig. 1 sulphur dioxide concentration variation and maximum
concentration variation of sulphur dioxide for charge I is represented. The
graph shows that the sulphur dioxide concentration increased with the
increasing of temperature in the interval 350-450oC, so that at the temperature
of 450oC reaches the maximum value of 95 [ppm], after which the SO2
concentration decreases with the increasing of the temperature.
Figure 1. Variation with temperature of sulphur dioxide concentration and
maximum concentration variation of sulphur dioxide for charge I
145
DANA – ADRIANA ILUŢIU – VARVARA, DAN RĂDULESCU
The composition of the charge II is presented in table 3.
Table 3. The composition of the charge II
Charge
Painted plate
Zincked plate
First fusion pig iron
Plastic and vaseline
Total
Composition [%]
40
40
15
5
100
Weight [g]
4
4
1.5
0.5
10
In Fig. 2 sulphur dioxide concentration variation and maximum
concentration variation of sulphur dioxide for charge II is represented. The
graph shows that the sulphur dioxide concentration decreases with the
increasing of temperature in the 520–750oC, 800–860oC and 900-1070oC
intervals, and in the intervals 750-800oC and 860 - 900oC sulphur dioxide
concentration increases with the increasing of the temperature.
Figure 2. Variation with temperature of sulphur dioxide concentration and
maximum concentration variation of sulphur dioxide for charge II
The composition of the charge III is presented in table 4.
Table 4. The composition of the charge III
Load
Painted plate
Zincked plate
First fusion pig iron
Plastic and vaseline
Total
146
Composition [%]
15
45
33
7
100
Weight [g]
1.5
4.5
3.3
0.7
10
ASSESSMENT OF AIR POLLUTION WITH SULPHUR DIOXIDE FROM ELECTRIC ARC FURNACES
In Fig. 3 sulphur dioxide concentration variation and maximum
concentration variation of sulphur dioxide for charge III is represented. The
graph shows that in the 680-780oC, 800-850oC and 900-950oC intervals,
the maximum sulphur dioxide concentration increases as long as the
temperature increases, and in the 780-800oC, 850-900oC and 950-1100oC
intervals, decreases as the temperature increases.
Figure 3. Variation with temperature of sulphur dioxide concentration and
maximum concentration variation of sulphur dioxide for charge III
Based on the sulphur dioxide concentrations recorded by the burned
gases computer analyzer – MAXILYZER, there were computer the average
sulphur dioxide concentrations for the three types of charges analyzed were
calculated. Average values are 17.45, 14.90 and 15.00 ppm for the three
charges, respectively.
From the analysis of the sulphur dioxide concentrations recorded for
the three types of charges, we concluded that the intervention threshold
value for SO2 (13.36 ppm according to the reference [14]) was exceeded by
1.3 times for the first charge, by 1.11 times for the second charge and by
1.12 times for the third charge.
CONCLUSIONS
After analyzing the SO2 and SO2max concentrations variation graphs
for the three charges, it results that: in all the three charges it the presence
of sulphur dioxide was detected the presence; the greatest concentration was
detected for the charge I (95 ppm); the recorded SO2 concentrations decreased
with the increasing of the temperature; the average concentrations of sulphur
dioxide exceed the intervention threshold.
147
DANA – ADRIANA ILUŢIU – VARVARA, DAN RĂDULESCU
The emissions level of the sulphur dioxide and maximum sulphur
dioxide registered for the three charges are influenced by the sulphur contained
in the charge components.
In order to reduce sulphur dioxide emissions it is necessary to select
the charge and to preheat the furnace. The charge components selection
process refers to the reduction/elimination of the sources having a potential
to generate sulphur dioxide. The techniques to reduce the air pollution with
sulphur dioxide from electric arc furnaces include the followings: the selection
of raw materials (first fusion pig iron; scrap with low sulfur content); the usage
of fuel with low sulfur content, such as natural gas; flue gas desulphurization
(absorption, adsorption, catalytic oxidation and catalytic reduction).
The original aspects of the article are: conception of three types of
charge for determining the sulphur dioxide concentrations; identification of air
pollution sources with sulphur dioxide from electric arc furnaces; identification
of techniques to reduce the sulphur dioxide concentration; assessment of
air pollution with sulphur dioxide from electric arc furnaces.
Also for monitoring sulphur dioxide emissions from steelmaking plants
it is necessary to achieve a database containing charge compositions, which
will make possible the prediction of the emissions concentrations.
EXPERIMENTAL SECTION
In order to determine the sulphur dioxide emissions, which are
transferred during steelmaking, three charge types were considered.
In order to realize these determinations, the following equipments
were used: an analytical balance; a contact thermometer MICROTEC
DIGITEMP 01K; nacelles; a mono-phased electric furnace with chamber type
resistance with spirals (model WG/ r01/1522/ 2 VEB) having the following
characteristics: P = 2 KV, Umax = 250 V, Imax = 9A, Tmax = 1650oC and
transformer of type RFT/SST / 250 V / 20A; a computer for burned gases
analysis MAXILYZER.
The nacelle which contains the considered charge was introduced in
the furnace with chamber type resistance with spirals, without prior heating,
for charges I and III and with preliminary heating at 520oC.
Sulphur dioxide emissions were determined in the 350-1400oC
interval (T1 = 350oC, T2 = 400oC, T3 = 450oC, T4 = 500oC, T5 = 550oC, T6 =
600oC, T7 = 650oC, T8 = 700oC, T9 = 750oC, T10 = 800oC, T11 = 880oC, T12 =
1000oC, T13 = 1100oC, T14 = 1200oC, T15 = 1210oC, T16 = 1220oC, T17 =
1250oC, T18 = 1300oC, T19 = 1350oC and T20 = 1400oC), 520-1070oC (T1 =
520oC, T2 = 700oC, T3 = 750oC, T4 = 800oC, T5 = 820oC, T6 = 860oC, T7 =
900oC, T8 = 950oC, T9 = 1000oC and T10 = 1070oC) and 680-1100oC (T1 =
680oC, T2 = 780oC, T3 = 800oC, T4 = 850oC, T5 = 900oC, T6 = 950oC, T7 =
1000oC, T8 = 1060oC and T9 = 1100oC) for charge I, II and III, respectively.
148
ASSESSMENT OF AIR POLLUTION WITH SULPHUR DIOXIDE FROM ELECTRIC ARC FURNACES
The concentrations of the sulphur dioxide were red every two minutes.
The variation diagrams for the three types of charges were made
using MathCAD 7 Professional software.
RE F E R E N CE S
1. D.A. Iluţiu-Varvara, "The Generation and Transfer of Pollutant Substances in
Industrial Processes", Tehn. Univ. Publishing, Cluj-Napoca, 2007.
2. P. Forster, V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey,
J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga,
M. Schulz, R. Van Dorland, Changes in atmospheric constituents and in radiative
forcing. Climate Change, 2007. The Physical Science Basis, "Contribution of
Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change", Edited by: S.D. Solomon, Qin, M. Manning, Z., M.
Chen, K.B. Marquis, M. Averyt, M. Tignor, and H.L. Miller, Cambridge University
Press, Cambridge, UK, New York, NY, USA, 2007, 129–234.
3. US Environmental Protection Agency (USEPA), National Air Pollutant Emission
Trends, 1900–1995. EPA-454/R-96-007, Washington, DC, 1996.
4. L.G. Chestnut, Human Health Benefits From Sulfate Reductions Under Title IV
of the 1990 Clean Air Act Amendments, Final Report, U.S. EPA, Office of
Atmospheric Programs, Acid Rain Division, 1995.
5. B. Nemery, P.H.M. Hoet, A. Nemmar, "The Meuse Valley fog of 1930: an air
pollution disaster", The Lancet 357(9257), 704-708, 2001.
6. National Institute for Occupational Safety and Health (NIOSH), "Occupational
Health Guidelines for Chemical Hazards", DHHS (NIOSH) Publication No. 81123, 1981.
7. A. Wellburn, "Air Pollution and Climate Change: the biological impact", Addison
Wesley Longman Limited, Harlow, 1994, 268.
8. WHO (World Health Organization), “Sulfur Oxides and Suspended Particulate
Matter.” Environmental Health Criteria 8. Geneva, 1979.
9. D.A. Varvara, "Studies Concerning the Substances Transfer between the
Steelmaking Phases", PhD Thesis, TUC-N, 2007.
10. Directive 2008/1/EC of the European Parliament and of the Council of 15 January
2008 concerning “Integrated Pollution Prevention and Control”, 2008.
11. Directive 2001/81/EC of the European Parliament and of the Council of 23
October 2001 on national emission ceilings for certain atmospheric pollutants.
Official Journal of the European Communities L 309: 22-30, 2001.
149
DANA – ADRIANA ILUŢIU – VARVARA, DAN RĂDULESCU
12. Directive 2001/80/EC of the European Parliament and of the Council of 23 October
2001 on the limitation of emission from certain pollutants into the air from large
combustion plants. Official Journal of the European Communities L 309: 1-20,
2001.
13. Directive 2010/75/EU of the European Parliament and of the Council of 24
November 2010 on industrial emissions (integrated pollution prevention and
control), 2010.
14. "Concerning Atmosphere Protection and Emission Norms for the Determination of
Air Pollutants Produced by Stationary Sources", MAPPM Order no. 462/1993.
150
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 151 – 160)
(RECOMMENDED CITATION)
EQUILIBRIUM AND THERMODYNAMIC STUDY OF
COMPLEXES OF THALLIUM WITH URACIL AT DIFFERENT
TEMPERATURES AND CONSTANT IONIC STRENGTH
ELHAM HEIATIANa, FARHOUSH KIANIb, SASAN SHARIFIa,
AZAR BAHADORIa, AND FARDAD KOOHYAR*b
ABSTRACT. In aqueous solution, the protonation equilibria of uracil and their
complex formation with thallium(I) ion were investigated using a combination
of potentiometric and spectrophotometric methods at different temptatures
(283.15, 288.15, 293.15, 298.15, 303.15 and 308.15) K and constant ionic
strength (0.1mol dm-3 sodium perchlorate). A careful and accurate method
based on chemometrical concepts was used in order to determine stability
constants. For this purpose, spectral titration data were used and the spectra
were recorded in the range (200-500 nm). The stability constants of thallium(I)
ion with all the heterocyclic bases were calculated at various temperatures
by means of computer fitting of the pH-absorbance data with appropriate
mass balance equations. The computer program equispec was used to extract
the desired information from the spectral data. The outputs of the fitting
processes were protonation and stability constants, spectral profiles of pure
forms, distribution diagrams, and other factor analysis data. The composition
of the formed complexes were determined and it was shown that thallium(I)
forms a mononuclar 1:1 species with the uracil, of the type TlL in the pH
range of study (1.0-12.4), where L represents each heterocyclic base. Finally,
The effect of temprature on the protonation and stability constants were
studied and thermodynamic functions such as change in enthalpy (ΔH),
change in entropy (ΔS) and change in gibbs energy (ΔG) have been obtained
for the complexes of thallium(I) ion with the heterocyclic bases from the
stability constants values and their temperature dependence.
Key words: Equispec, Thallium(I) complexe, Uracil, Temperature, Constant
ionic strengh.
a
b
Chemistry Department, Islamic Azad University of Arak, Arak, Iran
Department of chemistry, Faculty of Science, Islamic Azad University, Ayatollah Amoli Branch,
Amol, Iran, *Corresponding Author: E-mail: FardadKoohyar@yahoo.com
ELHAM HEIATIAN, FARHOUSH KIANI, SASAN SHARIFI, AZAR BAHADORI, FARDAD KOOHYAR,
INTRODUCTION
In our life today, the physico-chemical data of biological and organic
molecules are very important due to their usages in various fields of industry
such as food, pharmacy, cosmetic and detergents. Also, these data help us
to better understanding of interaction between molecules in their solutions
[1-8].
Uracil is one of the four nucleobases in the nucleic acid of RNA. In
the body Uracil help to carry out the synthesis of many enzymes necessary
for cell function through bonding with riboses and phosphates [9]. It can be
used for drug delivery and as a pharmaceutical [10].
NH
O
N
H
O
Scheme 1. Structures of the uracil
On the otherhand, thallium is a toxic element and acts on the central
nervous system and induces inflammatory response. Since thallium(I) shows
marked similarities to that of potassium cation, its interaction with nucleotides,
the monomeric units of DNA and RNA, in aqueous would be of a major
biochemical interest [11].
Aqueous solutions of Metal complex were studied by various techniques
[12]. Also, there are several methods for the determination of acidity constants
[13-18]. Spectroscopic methods are in general highly sensitive and are
frequently used to analyze chemical equilibria in solution. In among of various
properties of analyte, the physical property is measured (in most of these
methods) as a function of the pH of the solution and the resulting data are
used for the determination of the dissociation constants [19].
In the present work, the protonation and stability constants of uracil
with Tl(I) were determined spectropotometrically at six different temperatures
in ionic strength 0.1 mol dm-3 NaClO4.
The stability constants of the formed complexes at different tempratures
were evaluted by the Equispec program using the corresponding spectral
absorption-pH data and these values have been compared with similar
systems and interpreted. Then, thermodynamic functions have been obtained
from the stability constants values and their temperature dependence.
152
EQUILIBRIUM AND THERMODYNAMIC STUDY OF COMPLEXES OF THALLIUM WITH URACIL ..
RESULTS AND DISCUSSION
All measurements were carried out at six different temperatures
(283.15, 288.15, 293.15, 298.15, 303.15 and 308.15) K. The ionic strength
was maintained to 0.1 mol dm-3 with sodium perchlorate. The pH meter was
calibrated for the revalent H+ concentration with a solution of 0.01 mol dm-3
perchloric acid solution containing 0.09 mol dm-3 sodium perchlorate (for
adjusting the ionic strength to 0.1 mol dm-3). For this standard solution, we
set –log [H+]=2.00 [20]. Junction potential corrections have been calculated
from the bellow equation:
-log[H+]real = -log[H+]measured + a + b[H+]measured
(1)
where a and b were determined by measuring hydrogen ion
concentration for two different solutions of HClO4 or NaOH with sufficient
NaClO4 to adjust the ionic strength in solutions.
The species MpHqLr(np+q+r)+ formed is characterized by it stoichiometry
(x:y:z), where M and L represent the metal ion and each ligand, respectively.
To determine the stability constant of the complexation or protonation, eq 2
is defined by βpqr [21]:
pM n + + qH + + rL− ⇔ M p H q Lr
β pqr =
[ M p H q Lr
( np + q + r ) +
( np + q + r ) +
(2)
]
(3)
[ M + n ] p [ H + ] q [ L− ] r
The protonation constants of the heterocyclic bases have been used
for computation of the stability constant, βpqr, of the metal-ligand. For thallium (I)uracil system a linear relation between logβ and 1/T is observed in Figure 1.
In addition, all these linear diagrams (logβ vs 1/T) have the high R2 (R2 ≈ 0.99).
8
7
y = 12.495x - 36.221
R2 = 0.9901
6
y = 14.358x - 43.011
R2 = 0.9925
logβ 5
4
y = 7.3944x - 21.465
R2 = 0.9916
3
log β021
log β011
log β110
2
3.2
3.3
3.4
1/T
3.5
3.6
Figure 1. Cureve logβ versus 1/T for Tl(I)-uracil system
in ionic strength 0.1 mol dm-3 NaClO4.
153
ELHAM HEIATIAN, FARHOUSH KIANI, SASAN SHARIFI, AZAR BAHADORI, FARDAD KOOHYAR,
In this work, the electronic absorption spectra of uracil were recorded
in different tempratures and at various pH values. The protonation constants of
the uracil were determined using a potentiometric technique and calculated
using a computer program which employs a nonlinear least-squares
method (Microsoft Excel Solver) [22, 23]. These values are listed in Table 1
(the values reported in the literature are, pK1 = 0.6 and pK2 = 9.46) [24].
Determination of the formation constant was employed using the
method mentioned before. Absorbance, A, and -log [H+] were measured by
successive addition of an alkali solution of the ligand to the acidic metal ion
solution in the UV range (200 to 500) nm; see Experimental Section.
Treatment of the spectrophotometric data (every 5 nm) obtained during the
titrations, as a function of H+ concentration, was conducted with the computer
program Equispec (by using the matrix based in the Matlab environment) [25].
Table 1. Average values of the protonation constants of the uracil at
different tempratures and constant ionic strength, I, (0.1 mol dm-3 NaClO4)
T(ºK)
logβ021
ΔH
(Kj.mol-1)
ΔS
(j.mol-1)
ΔG
(Kj.mol-1)
log β011
283.15
4.74 ± 0.44
7.80 ± 0.53
288.15
4.16 ± 0.39
7.15 ± 0.50
293.15
3.71 ± 0.32
6.55 ± 0.45
298.15
3.40 ± 0.22 -142.10 -412.43
303.15
2.86 ± 0.23
-19.12
4.98 ± 0.41
308.15
2.61 ± 0.34
4.20 ± 0.21
ΔH
(Kj.mol-1)
5.90 ± 0.12 -248.53
ΔS
(j.mol-1)
ΔG
-1
(Kj.mol )
-724.91
-32.40
The stoichiometric formation constants were computed from the data
using the computer program. The number of experimental points (absorbance
vs pH) was more than 30 for each titration. It is most convenient to arrange
a series of the measured absorption spectra at different wavelengths and
various pH values as the rows of a matrix Y. According to Beer-Lambert’s law,
Y can be decomposed into the product of a concentration matrix C and a
matrix A of molar absorptivities. The concentration profiles of the absorbing
species form the columns of C and the molar absorption spectra form the
corresponding rows of A. Due to the instrumental and experimental errors,
this decomposition is not perfect, the difference being the matrix E of
residuals. A matrix equation can be written as:
Y = CA + E
154
(4)
EQUILIBRIUM AND THERMODYNAMIC STUDY OF COMPLEXES OF THALLIUM WITH URACIL ..
Data fitting consists of determining those unknown parameters for
which the sum of the squares over all the elements of the matrix E of residuals
is minimal. Initially, the unknown parameters including the equilibrium
constants, a vector p of nonlinear parameters, overall formation constants, and
all the molar absorptivities of all the components, i.e., the complete matrix A of
linear parameters, were determined. C is defined by the model and the
appropriate equilibrium constants and is calculated numerically using the law
of mass action and the analytical (total) concentration of each componentin
solution [26, 27]. If the spectra are measured at many wavelengths, the total
number of parameters could be very high, and it is crucial to reduce this
number by separation of the linear and nonlinear parameters. For any set off
nonlinear parameters, p, which defines the concentration matrix C, the best set
of linear parameters, the matrix A, is an explicit least-squares calculation
(5)
A = C+Y
C+ is the pseudoinverse which can be calculated as C+ = (CtC)-1Ct or
preferably using a numerically more stable algorithm (i.e., an algorithm which
guarantees to reach physically meaningful final results) [28]. A is now defined
as a function of p and consequently E, and sums of the squares (ssq) are
defined as a function of the nonlinear parameters only
ssq = E(i, j) 2 = f (Y, model, parameters) = f(P)
(6)
In the equilibrium condition, the model is a collection of equilibria
between the component species, and the parameters are the equilibrium
constants. The computation of the pseudo-seems to be a trivial task. In
equilibrium studies, inverse C+ generally the concentration matrix C has, at
least theoretically, full rank; i.e., the chemical and mathematical ranks are
equal, and the concentration profiles for all species are linearly independent.
C+ can be computed, and A is determined by eq 5. This is, however, not
always the case, and near linear dependency (i.e., when the distribution
diagram of some species can be expressed as a linear combination of some
other species) and (or) species with only very low concentrations result in
deficiencies in the equilibrium model. In this status, C, then, does not have full
rank, and the pseudoinverse, C+, is not or is only poorly defined, which can
render its computation difficult to impossible and thus corrupt the resulting
A as well as the residuals, E, and the sum of squares. There are powerful
algorithms such as the Newton-Gauss-Levenberg/Marquardt algorithm available
for this task [29].
The output of Equispec comprises the spectrum, pka values and
diagrams of the concentration distribution of each assumed species. From
inspection of the experimantal spectra, it is hard to guess even the number
of protolytic species involved.
155
ELHAM HEIATIAN, FARHOUSH KIANI, SASAN SHARIFI, AZAR BAHADORI, FARDAD KOOHYAR,
Considering eq 2, different models including ML, MHL and several
polynuclear and protonated species were tested by the program. As expected,
polynuclear complexes were systematically rejected by the computer program,
as also were, MH2L, and MHL2, ML2 and MH2L2. Values for some species
were calculated by the program, but the species were not considered further
because the estimated error in its formation constant was unacceptable, and
its inclusion does not improve the goodness of the fit. The models finally
chosen, formed by ML for the studied system, resulted in a satisfactory fitting.
Also, the thermodynamic functions for the heterocyclic base have
been obtained from the protonation and stability constants values and their
temperature dependence.
The calculated average values of the protonation and stability constants
for different experiments are listed in Tables 1, 2. In Figure 2 the equilibrium
distributions of various species of Tl(I) with uracil system are shown as a
function of –log [H+], respectively. The most important features of the distribution
diagrams are the pH limits of the evolving and disappearing of components.
Table 2. Avrage values of the formation constants of Tl(I) with uracil at different
temperature and constant ionic strength (0.1 mol dm-3 NaClO4) some
thermodynmic Parameters at Different Temperatures
T (ºK)
logβ101
283.15
7.60±0.65
288.15
6.82±0.65
293.15
6.10±0.65
298.15
5.36±0.65
303.15
4.38±0.65
308.15
3.44±0.72
ΔH (Kj.mol-1) ΔS (j.mol-1) ΔG (Kj.mol-1)
-275
-823.52
-29.52
The calculations shown are based on the stability constant values
given in Tables 1 and 2. The curves clearly demonstrate that an increase of
the pH is accompanied by an increase in the formation of deprotonated
complex species.
156
Species concentration
(×10-4 mol dm-3)
EQUILIBRIUM AND THERMODYNAMIC STUDY OF COMPLEXES OF THALLIUM WITH URACIL ..
3.0
H2L
2.5
2.0
HL
L-
TlL
1.5
1.0
0.5
0.0
0
2
4
6
8
10
12
-log[H+]
Figure 2. The equilibrium distribution of the species for the system Tl(I)-uracil as a
function of log[H+] at 298.15 K and constant ionic strength 0.1 mol dm-3 NaClO4.
CONCLUSION
The stability constants of thallium(I) with uracil were calculated with
spectrophotometric titrations using a chemometric method. The striking
advantage of the proposed method is using of the whole spectral information
in the computation process which enable us to have more precise and
accurate thermodynamic constants in comparison to the classical methods
such as single wavelength approach. The effect of the temprature on the acid
dissociation and stability constants is investigated and it reveals the complex
relations of the acid dissociation and stability constants to temprature. The
results show good consistency with the previous reported results. However,
the differences are mostly due to the different techniques, various ionic
strengths with different background electrolytes, and different temperatures
that were used.
EXPERIMENTAL
Chemicals
All the chemicals used were of analytical reagent grade. Uracil
(C4H4N2O2) was obtained from Merck. The aqueous stock solutions of the
uracil were freshly prepared daily. The NaOH solution was prepared from a
titrisol solution (Merck), and its concentration was determined by several
titrations with standard HCl. Perchloric acid and thallium (I) nitrate were from
Fluka and were used without further purification. Dilute perchloric acid solutions
were standardized against standard NaOH solution. Sodium perchlorate was
purchased from Merck and was kept in a vacuum at least 72 h before use.
157
ELHAM HEIATIAN, FARHOUSH KIANI, SASAN SHARIFI, AZAR BAHADORI, FARDAD KOOHYAR,
All The reagents were used without furthere purification and dilute solutions
were prepared from double-distilled water with specific conductance equal
to (1.8 ± 0.1) μΩ-1 cm-1.
Apparatus and software
The pH values were measured with a HORIBA M-12 pH-meter using a
combined glass electrode. The glass electrode was calibrated on the basis of
the proton concentration at constant ionic strength (0.1 mol dm-3) according
to the procedure described elsewhere [30]. The calibration was repeated at
each specific temperature (t ± 0.1) °C by circulation of thermostated water
through the jacket. Nitrogen purge gas was used to remove CO2. An
Eppendorf micropipette (±0.6%) was used for the addition of a standard
base to the solution. The calibration procedure was as recommended by
the IUPAC for glass electrodes [31].
A HP-8453 spectrophotometer controlled by a computer and equipped
with a 1 cm path length quartz cell was used for UV-Vis spectra acquisition.
Spectra were acquired between 200 and 500 nm (5 nm resolution). The
measurement cell was of a flow type. A Masterflex pump allowed circulation of
the solution under study from the potentiometer cell to the spectrophotometer
cell, so the absorbance and the pH of the solution could be measured
simultaneously.
The data were preprocessed using MATLAB software, version 6.5
(Mathworks, Natick, U.S.A) and the deconvolution of the obtained data
matrix was performed using Equispec version 3.1.
Procedure
Volumes of 10 cm3 acidic solution of Tl+ [(3.85×10-5 to 2.8×10-4 mol
dm-3)] was titrated with an alkali solution (0.1 mol dm-3 NaOH) of the uracil
[(8.05×10-5 to 1.6×10-4 mol dm-3). Titration of each the heterocyclic base
was carried out at 6 temperatures (283.15, 288.15, 293.15, 298.15, 303.15 and
308.15) K in ionic strength 0.1mol dm-3. Ionic strength fixed with NaClO4
solution. The starting points of pH titrations were pH 1.0, which were set using
concentrated solutions of HCl and NaOH. The concentrated NaOH solution
was also used for titrations, to avoid dilution of the working solutions. The log [H+] and absorbance were measured after addition of a few drops of
titrant, and the procedure was extended up to required -log [H+]. A purified
nitrogen atmosphere was maintained in the vessel during the titrations.
158
EQUILIBRIUM AND THERMODYNAMIC STUDY OF COMPLEXES OF THALLIUM WITH URACIL ..
ACKNOWLEDGMENTS
Thanks are gratefully extended to the Chemistry Department of Islamic
Azad University, Arak and Ayatollah Amoli Branch, for its invaluable help
of this work.
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21. M.T. Beck, I. Nagypal, "Chemistry of complex equilibria", Ellis Harwood: New
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22. N. Maleki, B. Haghighi, A. Safavi, Microchemical Journal, 1999, 62, 229.
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160
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 161– 174)
(RECOMMENDED CITATION)
KINETICS AND MECHANISM OF OXIDATION OF MALIC
ACID BY N-CHLORONICOTINAMIDE (NCN) IN THE
PRESENCE OF A MICELLAR SYSTEM
LAKSHMINARASIMHAN PUSHPALATHAa
ABSTRACT The oxidation of malic acid by N-chloronicotinamide in the
presence of HClO4 is studied. First order kinetics with respect to NCN is
observed. The kinetics results indicate fractional order in hydroxy acid.
Rate of the reaction increases with a decrease in the percentage of acetic
acid. Inverse first order in [H+] and [nicotinamide] are noted. Decrease in
the rate constant was observed with the increase in [SDS]. The values of
rate constants observed at four different temperatures were utilized to
calculate the activation parameters. A suitable mechanism consistent with
the experimental findings has been proposed.
Keywords: Malic acid, N-Chloronicotinamide, kinetics, oxidation, micelles
INTRODUCTION
The kinetics of the oxidation of hydroxy acids has been studied with
a number of oxidizing agents like potassium bromate, hexamethylenetetraminebromine, sodium N-chlorobenzenesulfonamide, N-bromoacetamide,
ditelluratocuprate(III), 2,2- bipyridium chlorochromate, benzo-dipteridine
etc. The presence of micelles can have marked effects on thermodynamic
favorability and reaction kinetics as well as on many physical properties1.
Organic reactions involving ionic, polar and neutral reactants in micellar
solution are generally believed to occur in the Stern layer of a micelle of an
ionic surfactant. The catalysis and inhibition by ionic micelles is due to ionic
micellar incorporation of both the reactants. Due to these facts a significant
amount of systematic kinetic results have been reported on the effect of
micelles on various organic reactions during past few decades.
A.K. Singh1 studied the kinetics and mechanism of oxidation of
some hydroxy acids by N-bromoacetamide. Chand Waqar2 investigated the
a
Postgraduate and Research Department of Chemistry, National College, Trichy — 620 001,
Tamil nadu, India. lathaa_ramesh@yahoo.com
LAKSHMINARASIMHAN PUSHPALATHA
mechanism of Ru(III)-catalysed oxidation of glycollic and mandelic acids with
N-bromosuccinimide in acidic media. Pradeep K. Sharma3 reported the
oxidation of some α-hydroxy acids by tetraethylammonium chlorochromate.
Ajaya Kumar Singh4 followed the kinetic and mechanistic study on the
oxidation of hydroxy acids by N-bromophthalimide in the presence of a micellar
system. E.V. Sundaram5 explained the oxidation of α-hydroxy acids with
Quinolinium Dichromate. Asim K Das6 studied the micellar effect on the
reaction of Chromium(VI) oxidation of some representative alpha-hydroxy
acids in the presence and absence of 2,2’-bipyridyl in aqueous acid media.
A perusal of literature shows that the reactivity of N-chloronicotinamide
(NCN) could be compared with other N-haloimide such as N-bromosuccinimide
(NBS) and N-bromosaccharin (NBSa). There are several reports available in
the literature on the oxidation of alpha-hydroxy acids by oxidants such as Nbromosuccinimide, N-bromoacetamide, potassium bromate, N-bromobenzenesulphonamide, and iodate7. However, the details of oxidation of malic
acid by NCN are yet to be explored. This prompted the micellar effect on
the kinetics of the oxidation of the malic acid by NBN in the acidic medium.
RESULTS AND DISCUSSION
The kinetic results for the oxidation of malic acid by N-Chloronicotinamide
(NCN) in the presence of surfactant (SDS) can be summarized as follows.
The kinetic studies were carried out under pseudo-first order conditions
with [malic acid] >> [NCN]. The kinetics of the oxidation of malic acid by
NCN in presence of surfactant (SDS) and HClO4 was investigated at
several initial concentrations of the reactant. The reaction was of first order
linearity of a plot of log [NCN] versus time for malic acid. The rate constants
at different initial [NCN] are reported. Table 1 summarizes the pseudo first
order rate constant’s dependence on the NCN concentration. It was observed
that, with the increase in initial NCN concentration, the value of rate constant
decreased (Fig. 1).
At a constant value of NCN, surfactant (SDS) and HClO4 the rate
constant was determined at different initial concentrations of malic acid
ranging from 5 × 10–3 to 50× 10–3 mol dm–3. Table 2 summarizes the pseudo
first order rate constant’s dependence on malic acid concentration. The rate
constant, increased with increasing [malic acid]. The plot of log k versus log
[malic acid] was linear with a slope of less than unity showing fractional
order dependence on [malic acid] (Fig. 2).
Furthermore, a plot of log k versus malic acid was linear with an
intercept on y axis, confirming the fractional order concentration dependence
on substrate. The rate constant k decreased with increase in [HClO4] from 5
× 10–3 to 50× 10–3 mol dm–3 (Table 2) (Fig. 3).
162
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
Table 1. Effect of variation of [NCN] on reaction rate
[Malic acid]=0.03mol dm-3 [HClO4]=0.01 mol dm-3, [NaClO4]=0.1mol dm-3,
AcOH:H2O (1:4) Temp. =308 K [SDS]=0.01 mol dm-3
[NCN]
105 kobs sec-1
104 moldm-3
1.0
38.96
1.5
28.43
2.0
22.86
2.5
19.69
3.0
17.71
4.0
14.76
5.0
13.09
Effect of variation of oxidant
-1
k (obs) in sec
k(obs) in 1/sec
40
35
30
25
y = 0.0032x + 6.758
20
R2 = 0.9998
15
10
1500
6500
11500
1/[oxidant]
Figure 1. Effect of variation of [NCN] on reaction rate
This may be due to protonation of the substrate. The plot of log k
versus log[HClO4] is linear with negative slope. The slope being less than
unity indicates inverse fractional order dependence on [HClO4]. Successive
addition of nicotinamide (as one of the oxidation products of NCN) to the
reaction mixture showed a decreasing effect on the rate of oxidation of malic
acid. Addition of NaClO4 (to study the effect of ionic strength) in the reaction
mixture showed an insignificant effect on the rate of oxidation. In order to
find the effect of dielectric constant (polarity) of the medium on the rate, the
oxidation of malic acid by NCN was studied in aqueous acetic acid mixtures
of various compositions (Table 2) (Fig.4). The data clearly reveal that the
rate of reaction increases with a decrease in the percentage of acetic acid,
i.e., increasing dielectric constant or polarity of the medium leads to the
inference that there is a charge development in the transition state involving
a more polar activated complex than the reactants11.
163
LAKSHMINARASIMHAN PUSHPALATHA
Table 2. Effect of variation of [Malic acid], [HClO4] and the
dielectric constant on reaction rate
103[MA]
103[HClO4]
5
10
20
25
30
40
50
30
30
30
30
30
30
30
30
30
30
30
30
10
10
10
10
10
10
10
5
10
20
25
30
40
50
10
10
10
10
10
105 k(obs)
-1
sec
9.76
15.39
24.12
28.15
31.30
38.29
44.58
46.38
28.87
18.11
15.73
13.86
11.21
9.72
27.89
25.15
22.18
16.17
10.66
CH3COOH
%(v/v)
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
25
30
40
50
[NCN]=0.00015 mol dm-3 [NaClO4]=0.1mol dm-3, Temp. =308K, [SDS]=0.01 mol dm-3
Effe ct of [Sub]
1.7
1.6
5+logk(obs)
1.5
1.4
SMA C
1.3
1.2
1.1
y = 0.6576x + 0.5289
R2 = 0.9999
1
0.9
0.55
1.05
1.55
3+log[s ub]
Figure 2. Effect of variation of [malic acid] on reaction rate
164
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
5+logk(obs)
Effect of [HCl]
1.75
1.65
1.55
1.45
1.35
1.25
1.15
1.05
0.95
0.85
SMAC
y = -0.6781x + 2.1404
2
R = 0.9999
0.55
1.05
1.55
3+log(HCl]
Figure 3. Effect of variation of [HClO4] on reaction rate
Effect of medium
1.463
1.413
1.363
5+logk(obs)
1.313
1.263
SMAC
1.213
1.163
1.113
1.063
y = -53.796x + 2.2854
R = 0.999
1.013
0.014
2
0.016
0.018
0.02
0.022
0.024
1/D
Figure 4. Effect of variation of medium on reaction rate
The effect of added salts on the rate of reaction was also explored
because salts as additives, in micellar systems, acquire a special ability to
induce structural changes which may, in turn, modify the substrate–surfactant
interaction. In the present case, KBr has no effect whereas with the increasing
concentration of KCl, rate of reaction increased.
165
LAKSHMINARASIMHAN PUSHPALATHA
Test for Free Radicals
To test for the presence of free radicals in the reaction, the reaction
mixture containing acrylamide was kept for 24 h in an inert atmosphere.
When the reaction mixture was diluted with methanol, the formation of a
precipitate was not seen. This suggests that there is no possibility of formation
of free radicals in the reaction.
Mechanism
It has been reported 11-16 earlier that NCN is a stable oxidizing and
chlorinating agent because of the large polarity of the N–Cl bond. NCN, like
other similar N-haloimides, may exist in various forms in an acidic medium,
that is, free NCN, protonated NCN, Cl+, HOClr, (H2OCl)+ according to the
following equilibria17-22.
NCN + H2O
HOCl + NA
(1)
NCN + H+
NA + Cl+
(2)
NCN + H+
[NCNH] +
(3)
HOCl + H+
[H2OCl]+
(4)
Addition of nicotinamide to the reaction mixture decreases the rate
of oxidation in acidic media suggesting that the pre-equilibrium step
involves a process in which nicotinamide is one of the products. When NCN
or (NCNH)+ is assumed as the reactive species, the derived rate laws fail to
explain the negative effect of nicotinamide, hence neither of these species
can be considered as reactive species. When (H2OCl)+ is taken as the
reactive species, the rate law obtained shows first order kinetics with respect
to hydrogen ion concentrations contrary to the observed negative fractional
order in HClO4; although it fully explains the negative effect of nicotinamide.
Therefore, the possibility of cationic chlorine (Cl+) as a reactive species is
also ruled out. Thus, the only choice left is HOCl, which, when considered
as the reactive species of NCN, leads to a rate law capable of explaining all
the kinetics observations and other effects. Hence, in the light of kinetic
observations, HOCl can safely be assumed to be the main reactive species
of NCN for the present reaction. On the basis of the above experimental
findings and taking HOCl to be the most reactive species of NCN, the
following scheme can be proposed for the kinetics of oxidation of malic acid
by NCN in acidic medium.
K1
NCN + H2O
HOCl + NA
(5)
166
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
K2
HOCl +NA
X − + (H3O)+
k
X−
Rate controlling step
(HO)CH (CH2COOH)+ NA+ CO2+ HCl
(6)
(7)
The rate of disappearance of NCN is given as
d [ NCN ]
kK 1K 2[ MA][ NCN ]TOTAL
=
dT
[ NA][ HCl ] + K 1K 2[ MA]
where
[NCN] TOTAL = [NCN] + [NA] + [X−]
The above rate law is in good agreement with the experimental results.
Influence of SDS on kobs
A continuous decrease in the rate constant was observed with the
increase in [SDS] at constant [MA] and [NCN] (Table 4). The inhibition effect is
due to the fact that N-chloronicotinamide has N -Cl bond which it binds to SDS
micelles in Stern layer, while ionized malic acid, bearing negative charge is
repelled by the head group of negatively charged SDS micelles.
nD+S
DnS
DnS
Km
Products
S
kw
Products
Piszkiewicz23 model assumes that ‘n’ number of surfactant molecules
(D) and substrate (S) aggregate to yield the catalysis aggregate DnS which
then reacts to yield the product (P). This is represented by the above scheme
where KD is the dissociation constant of micelle back to its free components
and km is the rate of reaction within the micelle. As per the above scheme the
observed rate constant (kobs) is expressed as a function of surfactant
concentration D, by the equation:
km[ D] n + kwKD
KD + [ D ] n
k (obs ) − k w
= nlog[D] - logKD
log
k m − k (obs )
k(obs) =
167
LAKSHMINARASIMHAN PUSHPALATHA
Table 3. Effect of [SDS] on reaction rate
103 SDS
105 k(obs) sec-1
0
2
2.5
4
5
6
8
10
20
30
40
50
60
70
80
100
110
120
130
25.65
22.32
20.01
18.28
16.83
14.59
13.48
12.59
-
[Malic acid]=0.03 mol dm-3 [HClO4]=0.01mol dm-3,[NCN]=0.0015 mol dm-3
[NaClO4]=0.1mol dm-3,AcOH:H2O (1:4) Temp. =308K
Effect of temperature
Increase in temperature increases the rate of oxidation and plot of log
kobs Vs reciprocal of temperature is linear. The oxidation of malic acid by NCN
was studied at different temperatures in the presence and absence of SDS
(308 to 323K) (Table 4) (Fig.5) and the activation parameters were evaluated
(Table 5) (Fig.6). Activation parameters are believed to provide useful
information regarding the environment in which chemical reactions take place.
Table 4. Effect of Temperature on reaction rate
Temperature
K
308
313
318
323
105 kobs sec-1
27.98
31.65
35.67
40.04
[Malic acid]=0.03 mol dm-3 [HClO4]=0.01mol dm-3,
[NCN]=0.0015 mol dm-3 [NaClO4]=0.1mol dm-3, AcOH:H2O (1:4)
168
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
Effect of tem perature
1.65
1.6
5+logk(obs)
1.55
1.5
1.45
SMAC
y =-1.0422x + 4.8298
R2 =0.9999
1.4
1.35
3.05
3.1
3.15
3.2
3.25
3.3
3.35
10 0 0 / T
Figure 5. Effect of Temperature on reaction rate
Table 5. Effect of Temperature on reaction rate in the presence of SDS
Temperature
K
308
313
318
323
105 kobs sec-1
25.75
30.02
34.58
39.79
[SDS]=0.01 mol dm-3
169
LAKSHMINARASIMHAN PUSHPALATHA
Effect of tem perature-SDS
1.65
1.6
5+logk(obs)
y = -1.2513x +5.4739
R2 = 0.9999
1.55
SMAC-SDS
1.5
1.45
1.4
3.05
3.1
3.15
3.2
3.25
3.3
1000/ T
Figure 6. Effect of Temperature on reaction rate in presence of SDS
Table 6. Activation Parameters
Substrate
Ea kJmol-1
ΔH# kJmol-1
Malic acid
11.14
8.58
− 186.5
66.04
Malic acid+SDS
12.95
10.39
−180.9
66.14
170
ΔS# J K-1mol-1 ΔG#kJmol-1
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
A ct ivat io n p ar amet er s
-1.86
0.00308 0.0031 0.00312 0.00314 0.00316 0.00318 0.0032 0.00322 0.00324 0.00326
-1.88
-1.9
5+logk(obs)
-1.92
-1.94
SMAC
-1.96
-1.98
-2
-2.02
-2.04
1/ T
A ct ivat io n p ar amet er sSD S
-1.85
0.0031 0.0031 0.0031 0.0031 0.0032 0.0032 0.0032 0.0032 0.0032 0.0033
L.mol-1sec-1
-1.9
-1.95
SMACSDS
-2
-2.05
y = -1249.4x +1.9912
R2 = 0.9999
-2.1
1/ T
Figure 7. Activation parameters
EXPERIMENTAL
Materials and methods
N-Chloronicotinamide (NCN) was prepared by the reported method8.
Standard solution of NCN was prepared afresh in water and its purity was
checked iodometrically. Standard solutions of SDS (GR) and malic acid
(Merck) were prepared using double distilled water. HClO4 (A.R. grade) was
diluted with double distilled water and was standardized via acid–base
171
LAKSHMINARASIMHAN PUSHPALATHA
titration. All other standard solutions of NaClO4, KCl, KBr and nicotinamide
were prepared using double distilled water. Double distilled water was distilled
over KMnO4 in an all glass (Pyrex) distillation set up. Distilled acetic acid was
used throughout the experiment (Table 1).
Kinetic measurements
The solution of malic acid and oxidant were kept in black coated
bottles separately. These solutions were kept in the thermostat to attain the
thermostatic temperature. The appropriate quantity of oxidant was added to
the substrate containing surfactant and other reagents and the reaction
bottle was shaken well. The reaction was followed potentiometrically by setting
up a cell made up of the reaction mixture into which the platinum electrode
and reference electrode(SCE) were dipped. The e.m.f of the cell was
measured periodically using a Equip-Tronics (EQ-DGD) potentiometer. The
reactions were studied at constant temperature 35◦C. Different studies such as
variation of malic acid, oxidant (NCN), perchloric acid, sodium perchlorate,
nicotinamide, surfactant and temperature were carried out. The reaction was
carried out under pseudo-first order condition ([malic acid] >>[NCN]). The pseudofirst order rate constants were computed from the linear (r2 > 0.9990) plots
of log (Et−E∞) against time. Duplicate kinetic runs showed that the rate
constants were reproducible within ±3%. The course of the reaction was
studied for more than two half-lives.
Stoichiometry
The reaction mixture containing a known excess of [NCN] >> [malic
acid] was kept in the presence of HClO4 and at 40°C for 72 h. After completion
of the reaction, the unconsumed NCN was calculated iodometrically. It was
found that nearly 2 moles of NCN were consumed for each mole of malic acid.
Product analysis
The presence of carbonyl compound (2-aldoethanoic acid) as the
main product of oxidation was detected by the spot test 9 and the 2,4dinitrophenylhydrazine method 10.
172
KINETICS AND MECHANISM OF OXIDATION OF MALIC ACID BY N-CHLORONICOTINAMIDE (NCN)
CMC determination
Surfactants spontaneously aggregate above a certain concentration
called critical micelle concentration (CMC) to form micelle, whose determination
has considerable practical importance, normally to understand the selforganizing behavior of surfactants in exact ways. Micelles act as microreactors,
which can both speed or inhibit the rate of uni- and bimolecular reactions.
Micelle aggregates affect chemical reactivity primarily by binding or
excluding reactants and only secondarily by changing the free energy of
activation. The critical micelle concentration values of the surfactant (SDS)
was determined conductometrically (Digital conductivitymeter, model 611E,
Electronic India Company) in the presence and absence of reactants at
40◦C. The CMC value was determined from plot of the specific conductivity
versus surfactant concentration. The breakpoints of nearly straight-line portions
in the plot are taken as an indication of micelle formation, and these
correspond to the CMC of surfactant. The CMC values of SDS in different
experimental conditions at 40◦C are summarized in Table 8. The CMC value is
lower than that given in the literature for aqueous solutions of SDS without
added electrolyte, which was found to be approximately about 3.21×10−3
mol dm−3 in reaction mixture for malic acid.
Table 8. Critical micelle concentration (CMC values of
SDS in different experimental conditions)
[Malic acid]=0.03mol dm-3 [HClO4] = 0.01 mol dm-3,
[NaClO4]=0.1mol dm-3, AcOH:H2O (1:4) Temp. =308 K
Solutions
Water
Water+NCN
Water+malic acid
Water+malic acid+NCN+ HClO4+20% v/v AcOH
103 CMC
mol dm-3SDS
7.9
7.1
4.2
2.8
CONCLUSIONS
In the light of kinetic observations for the micellar effect on the kinetics
of oxidation of malic acid by N-chloronicotinamide in the presence of perchloric
acid, the following conclusions can be easily drawn: the reactive species of
oxidant NCN is HOCl not NCN itself, the reaction rates are enhanced by
increase in [malic acid] and temperature. Added nicotinamide retards the rate.
2-Aldoethanoic acid is the product of oxidation. Activation parameters were
evaluated for both catalyzed and unanalyzed reactions. The critical micelle
concentration is much lower than values that given in the literature for aqueous
solutions of SDS without added electrolyte. The rate of oxidation slightly
173
LAKSHMINARASIMHAN PUSHPALATHA
decreases with increasing concentration of SDS. The micellar effect can be
correlated with the nature of the reducing substrates and the reactions
conditions. These micellar effects are quite important to understand and to
substantiate the proposed mechanistic pathways. This may widen the
applicability of NCN as oxidant in organic synthesis.
ACKNOWLEDGEMENTS
The author gratefully acknowledges her husband Mr. A. Ramesh for
the moral support.
RE F E R E N CE S
1. Madhu Saxena, Ranjana Gupta; Amar Singh; Bharat Singh; Singh, A.K. Journal of
Molecular Catalysis, 1991, 65(3), 317.
2. Chand Waqar, Bharat Singh, Sharma, J.P. Journal of Molecular Catalysis,
1990, 60(1), 49.
3. D. Preeti Swami, P. Yajurvedi, Mishra, Pradeep K. Sharma, International Journal
of Chemical Kinetics, 2010, 42(1), 50.
4. Patil Sangeeta, Y.R. Katre, Ajaya Kumar Singh, Journal of surfactants and
detergents, 2007,10(3),175.
5. Kailasa Aruna, Prerepa Manikyamba, Embar Venkatachari Sundaram, Collection
of Czechoslovak Chemical Communications, 1978, 58(7), 1624.
6. Ruhidas Baeyen, Mohirul Islam, Asim K. Das, Indian Journal of chemistry, 2009,
48A, 1055.
7. Sangeeta Patil, Y.R. Katre, Ajaya Kumar Singh, Colloids and Surfaces. A:
Physicochem. Eng. Aspects, 2007, 308, 6.
8. K, Vivekanandan, K, Nambi, Indian J. Chem., Sect. B, 1996, 35, 1117.
9. F. Feigl, Spot test in Organic Analysis, Elsevier, New York, 1975,425.
10. A. Mathur, V.Sharma, K.K.Banerji, Ind. J. Chem., 1988, 27A, 123.
11. L. Pushpalatha, K. Vivekanandan, J. Indian Chem. Soc., 2009, 86, 475.
12. L. Pushpalatha, K. Vivekanandan, Oxid. Commun., 2009, 32(1), 85.
13. L. Pushpalatha, K. Vivekanandan, Oxid. Commun., 2008, 31(3), 598.
14. L. Pushpalatha, K. Vivekanandan, J. Indian Chem. Soc., 2008, 85, 1027.
15. L. Pushpalatha, K. Vivekanandan, Oxid. Commun., 2010, 33(4), 851.
16. L. Pushpalatha, Oxid. Commun., (in press).
17. L. Pushpalatha, K. Vivekanandan, Oxid. Commun., (in press).
18. L. Pushpalatha, K. Vivekanandan, Oxid. Commun., (in press).
19. L. Pushpalatha, K. Vivekanandan, J. Indian Chem. Soc., 2010, 87, 1221.
20. L. Pushpalatha, Afinidad, 2011, 68, 551.
21. L. Pushpalatha, International Journal of Chemistry, 2012,1(2), 199.
22. L. Pushpalatha, K. Vivekanandan, M.N.Abubacker, J. Indian Chem. Soc., 2013,
90, 1027.
23. D.J. Piszkiewicz, J. Am. Chem. Soc. 1977, 99, 7695. A.V. Hill, J. Physiol. 1910,
40, 4.
174
STUDIA UBB CHEMIA, LVIII, 2, 2013 (p. 175 – 183)
(RECOMMENDED CITATION)
THE ANTIOXIDANT ACTIVITY OF TEA INFUSIONS
TESTED BY MEANS OF BRIGGS-RAUSCHER
OSCILLATORY REACTION
NORBERT MUNTEANa, GABRIELLA SZABÓa
ABSTRACT. The antioxidant capacity of tea extracts was determined by means
of Briggs-Rauscher oscillating system in batch conditions. This method consists
in the measurement of the inhibition time caused by the addition of tea extract
to the oscillating system. The inhibition time vs. the concentration of tea
extract shows linear dependence.
Keywords: Briggs-Rauscher oscillating reaction, inhibitory effect, analytical
method, tea extract
INTRODUCTION
The tea is one of the most popular worldwide beverages and a
major source of dietary antioxidants.
In 2011, researchers have conducted a trial to test the effects of
rooibos tea on various biological markers, considered to be indicative of risk for
cardio-vascular disease and other degenerative diseases. A high intake of
rooibos tea resulted in significant reductions in lipid peroxidation, LDL
cholesterol, triglycerides, and an increase in HDL cholesterol levels compared
with the control group. The researchers concluded that rooibos lowered the
risk factor [18].
The main flavonoids found in fresh tea leaves are the catechins
(flavan-3-ols, or flavanols) and the flavonols. These flavonoids represent
usually more than 30% of the dry weight of the leaves. Two flavonoids were
found in rooibos, the quercetin and luteolin, and they are used in cancer
therapy [1]. The rooibos leaves do not contain the antioxidant catechins [2].
The differences between the white, green and black tea is the processing
method of them. In order to prepare white tea the leaves are collected in
spring, when the leaves are covered with white dust. White tea and green
a
Department of Chemistry and Chemical Engineering, “Babeş-Bolyai” University, ClujNapoca,11 Arany Janos Str, Romania, RO-400028, E-mail: gszabo@chem.ubbcluj.ro.
NORBERT MUNTEAN, GABRIELLA SZABÓ
tea are produced using thermal processes, such as steaming or dry heating,
to inactivate polyphenol oxidase that oxidize catechins to more complex
oligomeric flavonoids characteristic of oolong and black teas.
During the manufacture of black and red teas, the colorless, monomeric
catechins are converted to orange-yellow- and red-brown-colored oligomeric
flavonoids. Additionally, oxidation of amino acids and lipids occurs with the
generation of numerous volatile flavor compounds. These oxidative changes
are reflected in the red-amber color, reduced bitterness, and increased
astringency and more complex flavor of black teas. Green and white tea
beverages contain 30–130 mg Epigallocatechin gallate (EGCG) per cup of tea,
while black tea beverages 0–70 mg EGCG per cup of tea. The flavonols,
such as quercetin, kaempferol, myricetin, and their glycosides, are present in
much lower concentrations than the catechins and are found in comparable
quantities in black, green, and oolong tea beverages (5–15 mg/cup) [3-6].
Tea polyphenols, especially the catechins, are possible antimicrobial
and antioxidant agents, with positive effects on human health. The antioxidant
activity can be determined by some well known analytical methods. All
these methods are based on the generation of free radicals in the reaction
mixture followed by their detection. In the presence of antioxidants, the
amount of the free radicals detected is much less in comparison with that of
a reference mixture. These are for example: Franckel, Pryor rapid screening,
TEAC (trolox equivalent antioxidant capacity), TRAP (total radical-trapping
antioxidant parameter) method, the FRAP (ferric reducing-antioxidant power)
method [7].
The Briggs-Rauscher (BR) reaction, one of the few reactions showing
long lived oscillations in batch conditions, was discovered by Briggs and
Rauscher. Its classical version is the oscillatory oxidation and iodination of
malonic acid (MA) by hydrogen peroxide and iodate, catalyzed by Mn2+ ions in
acidic medium. The reaction was studied by many research groups, including
that lead by Noyes, Furrow, Cervellati and Sørensen [8-10]. Recently a new
method was developed based on the inhibition of the well known oscillatory
system, the BR reaction [14]. An oscillating reaction is very sensitive -because
it is far away from chemical equilibrium - and this behavior is used in analytical
determinations.
Oscillations can be demonstrated by vivid color changes in the presence
of a starch indicator or usually they are monitored by recording platinum or
iodide selective electrode potentials vs. a reference electrode. Kinetically
important intermediates are I2, I-, I3-, O2, CO2, CO, HOI, HOO° and iodomalonic
acid (IMA) [10-13].
The basis of this analytical method consists in the fact that various
antioxidants (mono- and polyphenolic compounds), change the dynamics of
the BR reaction fundamentally by suppressing the oscillations even in a
surprisingly low concentration (usually in a few micromoles/liter).
176
THE ANTIOXIDANT ACTIVITY OF TEA INFUSIONS TESTED BY MEANS OF B.-R. OSCILLATORY REACTION
This kind of micro-analytical technique is used to determine the
antioxidant capacity of various chemical compounds or plant extracts. Cervellati
et al.[14] reported that the addition of mono- and polyphenolic compounds
to the active mixture causes a temporary but instant cessation of oscillations.
The time elapsed between the cessation and the subsequent regeneration
of the oscillatory regime is the so called inhibition time. A linear correlation
was found between the concentration and the inhibition time for numerous
phenolic substances added to the BR-mixture
The inhibitory effect was accounted for a fast reaction involving the
phenol compound and HOO• radical. Since polyphenols are known free
radical scavengers, they can reduce the concentration of HOO• in the BRmixture [15-17].
According to the suggested mechanism, as soon as the antioxidant
is consumed, the HOO• concentration rises to a critical level where the
oscillations can reappear.
In this study was made a comparison of white, green, black and rooibos
tea's activity. The first three were prepared from the processed young leaves of
Camellia sinensis, and the last one from the leaves of Calicotome villosa.
The study presented in this article is divided in two parts; first the
development of the optimal composition of the BR mixture, and in the second
part is presented the determination of antioxidant activity of white, green, black
and rooibos tea.
It is worth mentioning that, no studies have been published so far, in
which the antioxidant capacity of tea was determined by means of BR method.
RESULTS AND DISCUSSION
The optimal composition of the BR mixture
By varying the concentrations of iodate, hydrogen peroxide and H2SO4,
we expected to obtain a better composition of the mixture with higher amplitude
of the oscillations and a longer inhibition time.
These two factors are the most important characteristics of the
oscillations; the higher the values of these parameters, the larger the domain
of the applications of oscillatory reactions.
Increasing the amplitude of the oscillations the switch between
oscillation and inhibition is sharper. On the other hand, the oscillation period is
a limitative factor for the inhibition time. In the figure 1 are presented the
variations of these parameters vs. the concentration of one of BR mixture’s
component, and the optimal ones are encircled. The concentrations of the
other components in the reactor was kept constant and they were
[Mn2+] = 65 mM, [MA] = 50 mM, [H2SO4] = 25 mM, [KIO3] = 67 mM, if it’s not
mentioned otherwise.
177
NORBERT MUNTEAN, GABRIELLA SZABÓ
Figure 1 The values of amplitude and the duration of the oscillations as a
function of initial concentration of H2SO4, figs. a) and b), The values of
amplitude and the duration of the oscillations as a function of initial
concentration of KIO3 figs. c) and d) The H2O2 concentration was 0.65
M in figs. a) and c) and in figs. b) and d) it was 1.32 M
It can be concluded, that the optimal concentrations for BR method
are [H2SO4]0= 55 mM, [KIO3]0= 45 mM, [MA]0= 50 mM, [MnSO4]0= 65 mM,
[H2O2]0= 1.32 M
The antioxidant activity of teas
Perturbation of the oscillatory BR system with a tea extract causes
the immediate cessation of the oscillations; the time elapsed between the
cessation and returns of the oscillations, the so called inhibition time is
illustrated in Figure 2.
Using the optimal composition for the BR, the different tea extracts
antioxidant activity was determined for several dilutions and the calibration
curves were drawn for each of them. Variation of the inhibition time in function
of the antioxidant concentration was found to be linear as can be seen in
figure 3.
178
THE ANTIOXIDANT ACTIVITY OF TEA INFUSIONS TESTED BY MEANS OF B.-R. OSCILLATORY REACTION
Figure 2. The effect of the roiboos tea extract on the active BR mixture. At the
moment indicated by the arrow 0.35 ml of extract was added to the mixture
1200
b)
a)
1000
inhibition time (s)
inhibition time (s)
1000
800
600
400
200
800
600
400
200
0
0.2
0.4
0.6
0.8
1.0
0
relative concentration
0.2
0.4
0.6
0.8
1.0
relative concentration
inhibition time (s)
inhibition time (s)
300
200
100
0
d)
c)
400
400
200
0
0.2
0.4
0.6
0.8
relative concentration
1.0
0.2
0.4
0.6
0.8
1.0
relative concentration
Figure 3. The calibration curves of the tea extracts: a) green tea; b) white tea;
c) black tea; d) roiboos tea;
179
NORBERT MUNTEAN, GABRIELLA SZABÓ
The following equations can be achieved after applying the linear fitting.
tinh=47(±3.29) +1006.6(±6.18) *[green tea]
tinh=60(±3.80) +868.9(±6.41) *[ white tea]
tinh=-3.8(±2.28) +436.5(±3.84) *[ black tea]
tinh=-18.8(±0.98) +311.4(±1.63) *[ roiboos tea]
The antioxidant activity of the extracts was compared with that of
the chosen standard (green tea) and R.A.C (relative antioxidant activity related
to concentration) was calculated: the ratio between the concentrations of a
sample and that of the chosen standard (green tea) that give the same
inhibition time.
R.A.C. = [standard]/[ sample]
R.A.S (relative activity with respect to slopes): the ratio between the slope of
the straight line of the sample and that of the chosen standard (green tea).
R.A.S. = slope(sample)/slope(standard).
The results are presented in table 1.
Table 1. Values R.A.C and R.A.S for investigated sorts of tea
Relative
Green tea
concentration
0.1
0.2
1
0.6
1
R.A.C medium
R.A.S
White tea
R.A.C
Black tea
Roiboos tea
0.85
0.88
0.89
0.89
0.88
0.86
0.20
0.34
0.37
0.42
0.33
0.43
0.10
0.10
0.29
0.27
0.19
0.31
CONCLUSIONS AND OUTLOOK
The active BR system was used as an analytical method to determine
the antioxidant activity of some tea extracts. The analytical sign was the
inhibition time which shows linear dependence vs. the concentration. Using
the calibration curves two type of relative antioxidant activity was calculated.
The R.A.C value show us the sample amount with the same antioxidant
activity as the chosen reference (in our case the green tea), the R.A.S show to
us the increase of the antioxidant activity with the concentration. The following
order of antioxidant activity was found:
Green tea >white tea>black tea> rooibos tea
180
THE ANTIOXIDANT ACTIVITY OF TEA INFUSIONS TESTED BY MEANS OF B.-R. OSCILLATORY REACTION
It can be concluded (using the R.A.C medium value) that approximately
three cups of black tea or five cups of roiboos tea has the same antioxidant
activity as one cup of green tea, white tea has almost the same activity as
green tea. However the advantage of the roiboos tea is due to the absence
of caffeine in its composition and because of this can be consumed by
peoples with cardio-vascular disease history.
It is to be mentioned that the same order was established by means
of TEAC method of determining the antioxidant capacity.
Our future investigation will be focused on the synergetic effect of them.
EXPERIMENTAL SECTION
The instrumental set-up used to implement the proposed method
consisted of a double walled glass vessel of 10 mL capacity. Connection to a
FALC FA 90 thermostat ensures a constant temperature by water circulation
through the temperature jacket. We have chosen a value of 20°C.
Oscillations were monitored with a Pt electrode and an Ag/AgI indicator
electrode, both handmade. In the BR reaction both the Platinum and the
Ag/AgI electrodes are so called “indicator “ electrodes i.e. their potential oscillate
with respect to a reference electrode.
Such a reference electrode should be connected to the system via a
double junction salt bridge. To fit a double junction salt bridge into the reactor,
however, increases the reactor volume considerably.
Moreover the liquid–liquid junction of a salt bridges always a source
of contamination and “memories”.
To keep the reactor volume at a minimum and to avoid memory effects
we applied two indicator electrodes. The voltage between these electrodes
in the BR reaction was found to be still oscillatory thus the dynamic state of
the reactor can be followed by recording that voltage. Potentiometric traces
recorded this way were quite reproducible. [19]
They were connected to a PC through a PCI 6036 E data-acquisition
interface.
Tea extracts were made using boiled distilled water. Each plant (0.15 g)
was mixed with 100 mL of boiling water for 5 min, with constant shaking and
the samples were filtered through filter paper. These extracts were considered
the stock solutions, and different dilutions were made (for example 10 mL of
the stock solution was diluted to 100 mL). The concentration of the diluted
solutions –presented in table 1- is related to these ones.
181
NORBERT MUNTEAN, GABRIELLA SZABÓ
Chemicals and procedure
All chemicals were of analytical grade and were used without further
purification. Stock solutions with the following concentration were made:
[H2SO4]0=220 mM, [KIO3]0= 180 mM, [MA]0=200 mM, [MnSO4]0=260 mM,
[H2O2]0=5.28 M by using double distilled water. In the reactor they were
diluted 4 time.
The mixing order was: malonic acid, MnSO4, H2SO4, KIO3, and H2O2.
Oscillations start after the addition of H2O2. At the third oscillation 0.35 mL of
tea extract was added to the reactor using a micropipette. The experimental
dates were processed by Origin 8 software.
ACKNOWLEDGMENTS
The research was made with the financial support of: POSDRU
89/1.5/S/60189.
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