An Investigation about the Spectrophotometric and Electrochemical

Transcription

‫ﺩﺍﻧﺸﮕﺎﻩ ﺁﺯﺍﺩ ﺍﺳﻼﻣﻲ ﻭﺍﺣﺪ ﻳﺰﺩ‬
١٣٩٠ ‫ ﺍﺭﺩﻳﺒﻬﺸﺖ‬،‫ ﻳﺰﺩ‬،‫ﺳﻮﻣﻴﻦ ﮐﻨﻔﺮﺍﻧﺲ ﻣﻠﻲ ﻣﻬﻨﺪﺳﻲ ﻧﺴﺎﺟﻲ ﻭ ﭘﻮﺷﺎﮎ‬
The 3rd National Conference on Textile and Clothing Engineering- Yazd - April 2011
An Investigation about the Spectrophotometric and Electrochemical
properties of a Rutin and Studies of its Dying Conditions
Hamed Dehghanizadeh*1,2, Navid Nasirizadeh2, M. E. Yazdanshenas2, Zahra Shekari3, Sanaz
Dorostkar
1
2
Young Researchers Club, Islamic Azad University, Yazd Branch, Yazd, Iran
Department of Textile Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran
3
Nano Kimiae Kavire Yazd Co.,Yazd Science and Technology Park, Yazd, Iran
*
Email: [email protected]
ABSTRACT
Textile wastewater is in first place among industrial wastewater and causes serious
environmental problems to destroy aquatic life and consume dissolved oxygen due to its
strong color, high COD concentration, a large amount of suspended solids, highly fluctuating
pH and high temperature. Recently a revival interest in the use of natural dyes in textile
coloration has been growing. Flavonoids have the most important biological roles in plant
pigmentation, possess anti-cancer, anti–viral and anti–inflammatory properties. Rutin is a
flavonoid of widespread occurrence in nature. In this work, dyeing condition of wool fibers
with rutin as natural dye without metal mordant which are environmental pollutant has been
studied. A class of Central Composite Designs with a sub-experiment was proposed for
optimization of variance condition. The optimized factors were 5.0 for the dye bath pH, 75.0
ºC for the dyeing temperature, 1.50 g for the salt quantity of dye bath and 100.0 min for the
dyeing time as the independent variable.
Keywords: Exhaustion, Single Component, Central Composite Design, Wool Dyeing, Rutin.
1. INTRODUCTION
The worldwide demand for natural raw materials is nowadays of great interest as a result of
increased consumer awareness and a popular demand for natural products. With the
appearance of synthetic dyes the use of natural dyes for textile dyeing almost disappeared [1].
Unfortunately, many synthetic dyes are resistant to microbial degradation and some may be
carcinogenic. Today, natural colorants are emerging globally due to the fact that they are safer
and more environmentally friendly and thus the application of natural dyes should be
considered as a better alternative to synthetic dyes. Natural dyes processed for the market do
not undergo any chemical operations. Those operations involved are purely physical, such as
grinding, drying and water extractions. None of these operations create any great environment
problems [2]. Flavonoids are usually colored compounds and can be used as a natural pigment
in textile industry. They have the most important biological roles in plant pigmentation;
possess anti-cancer, anti–viral and anti–inflammatory properties. Rutin is a flavonoid of
widespread occurrence in nature [3].
Obtained results in traditional experiments which a factor is variant while the others are
constant are not precise while CCD method considers all effective factors at the same time.
Therefore, CCD method with a sub-experiment was proposed for optimization of variance
condition. In statistics methods, a central composite design is an experimental design, useful in
response surface methodology, for building a second order (quadratic) model [4]. After the
designed experiment is performed, linear regression is used, sometimes iteratively, to obtain
results [5]. Coded variables are often used when constructing this design. In this work, dyeing
condition of wool fibers with rutin as natural dye without metal mordant which are
environmental pollutant has been optimized by the Central Composite Design (CCD) method
[6].
Scheme 1. Structure of rutin.
2. Experimental procedure
Materials and Apparatus
Mill scoured 100% wool by Pashm Gharb Co. was used. All chemical reagents used for buffer
solutions preparation and NaCl salt were reagent grade from Merck. The solutions were
prepared with doubly distilled water. The buffer solutions were made up from H3PO4 +
NaH2PO4, and then adjusting the pH with 0.1 M H3PO4 or 2.0 M NaOH. Spectrophotometric
measurements were performed on spectrophotometer Carry 100 model from Varian, using a
quartz cell. The pH was measured with a Metrohm model 691 pH/mV meters.
Dyeing procedure
Before using, the fabric was treated with a solution containing 5.0 g L-1 nonionic detergent, at
50 °C for 30 min. Then, the fabric was thoroughly washed with water and air dried at room
temperature. Dye bath containing different buffer solutions pHs (3.0-11.0), NaCl (0.0-20.0 g
L-1), times (10-120 min) and temperatures (40-100 °C) was prepared with dye liquor ratio
(40/1.5). Dye concentration in all dye baths was 5.0×10-4 mol L-1. The dyed samples were
rinsed with cold water, washed in a bath of liquor ratio 40:1 using 3.0 g L-1 nonionic detergent
at 50 °C for 30 min, then rinsed and finally dried at ambient temperature. The percentage of
dye bath exhaustion (%E) was calculated according to the following equation (1):
(1)
where C0 and CF are the concentrations of the dye bath before and after dyeing, respectively.
Experimental Design
CCD-Uniform Design with a rotatable type of axial scale was used to investigate the
significance of the effects of temperature, time, NaCl salt concentration and pH. The
experiments were designed by using the software Design Expert version 6.0.6. The lowest and
the highest levels of variables are given in Table 1. A two-level, four-factor factorial central
composite design at the center points leading to 30 runs was employed for the optimization of
the dye bath parameters.
3. Results and discussion
Effect of dyeing temperature
Figure 1 shows the exhaustion percent (%E) obtained into dye bath temperature. It is clear that
the percentage of dye bath exhaustion increases with the increase of dyeing temperature until
70 °C and after that it decreased.
Figure 1. Effect of dyeing temperature (50 0C – 100 0C) on exhaustion percent. Dyeing
condition: salt concentration=25.0 g L-1, pH=5.0, time=80 min and dye concentration=5.0 ×104
mol L-1.
Effect of salt concentration
Figure 2 shows the effect of salt concentration on the exhaustion percent obtained from
the dyeing bath. It is clearly indicated that the percentage exhaustion increases as the
salt value increases until 25.0 g L-1 and then decreases. Therefore, it is show dyeing
with salt concentration=25.0 g L-1 is the best condition.
Figure 2. Effect of salt concentration on exhaustion percent. Dyeing condition: pH=5.0, T=70
ºC, time=80 min and dye concentration=5.0×10-4 mol L-1.
Effect of dye bath pH
Figure 3. Shows that the pH values of the dye bath have a considerable effect on the dye
ability of wool fibres while using the Rutin dye. The effect of the dye bath pH can be
attributed to the correlation between dye structure and wool fibre. Since the dye used is
sparingly soluble in water, containing OH groups, it maybe would interaction dipole with the
protonated terminal amino groups of wool fibres at acidic pH via ion exchange reaction due
to the acidic character of the OH groups. It was noticed from the figure that dye ability was
higher at pH 5.0, then the dye ability decreases due to the decreasing number of protonated
terminal amino groups of wool fibres, and therefore the ionic interaction decreases.
Figure 3. Effect of dye bath pH on exhaustion percent. Dyeing condition: NaCl
concentration=25.0 g L-1, T=70 ºC, time=80 min and dye concentration=5.0×10-4 mol L-1.
Effect of dyeing time
Wool dyeing process with Rutin dye at different time under the optimum conditions (pH=5.0
salt concentration=25.0 g L-1 at 70º C) showed that exhaustion increased as the dyeing time
increased to 80 min and then decreased as shown in Figure 4. So it seems that equilibrium is
reached after 80 min of dyeing process when the exhaustion is the highest.
Figure 4. Effect of dyeing time on exhaustion percent. Dyeing condition: Salt
concentration=25.0 g L-1, pH=5.0, T=70 ºC and dye concentration=5.0×10-4 mol L-1.
Optimization by the central composite design
Effects of the four variables, including temperature, time, temperature and NaCl salt
concentration on CCD were studied. The experimental design matrix is presented in Tables 1
and 2.
Table 1. Variables and experimental design levels
Level
Variable
-α
-1
0
+1
+α
X1(NaCl) (g)
0.00
0.50
1.00
1.50
2.00
X2 (pH)
4.00
4.75
5.50
6.25
7.00
X3 (T)(°C)
50.00
62.50
75.00
87.5
100.00
X4 (t) (min)
0.00
20.00
40.00
60.00
80.00
Table 2. Composition of the various runs of the central composite design, actual and predicted
responses
Run
1
2
3
NaCl (g)
pH
Temp(°C
Time
%E1
0.5
1.5
1
4.75
4.75
5.5
87.5
62.5
75
60
20
40
41.90
8.40
66.06
%E2
89.75
89.7566
89.75
8
89.75
89.7566
8
89.7566
8
89.7377
3
89.7377
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
1
0
0.5
1
1
1
1
1.5
1.5
2
1
0.5
1
0.5
0.5
1
1.5
1.5
1.5
1
0.5
1.5
1.5
1
1
0.5
0.5
5.5
5.5
6.25
4
5.5
5.5
7
4.75
6.25
5.5
5.5
6.25
5.5
6.25
4.75
5.5
6.25
6.25
4.75
5.5
4.75
6.25
4.75
5.5
5.5
4.75
6.25
75
75
62.5
75
50
75
75
87.5
87.5
75
75
87.5
75
87.5
87.5
75
87.5
62.5
62.5
100
62.5
62.5
87.5
75
75
62.5
62.5
40
40
20
40
40
0
40
20
20
40
40
20
80
60
20
40
60
20
60
40
20
60
60
40
40
60
60
65.62
55.18
32.49
32.71
39.44
0.959
13.07
39.09
37.87
67.29
55.40
39.36
65.07
36.08
44.20
68.49
36.51
19.63
41.65
50.23
36.45
51.28
44.79
68.96
67.23
54.86
46.82
89.75
89.73
89.73
89.71
89.68
89.68
89.66
89.66
89.64
89.6
89.6
89.6
89.52
89.52
89.52
89.51
89.47
89.43
89.43
89.39
89.37
89.26
89.24
89.18
89.15
88.92
88.9
All experiments were carried out and data were expressed as a consequence, the best
adsorption conditions for wool dyeing were obtained at 5.53 for the dye bath pH, 1.5 g.L-1 for
the salt concentration, 60.0 min for the dyeing time and 70.24 °C for temprature. CCD was
selected as the response to different cycles of the runs. The results of the second-order
response surface models for the CCD in the form of analysis of variance are given in Tables 3,
respectively. Using the designed experimental data (Table 2), the second-order polynomial
model for the yield of CES in terms of coded factors is shown as the following equation 2:
Y(Sqrt(%E))=+8.08-0.53A+0.19B+0.22C+1.77D+0.20AB-0.18AC-0.11AD+0.3BC+0.28BD0.56CD-0.82A2-0.037B2-0.32C2-0.86D2-0.19ABC-0.19BCD-0.53A2B-1.23A2D+0.51AB2 (2)
Table 3. ANOVA for response surface quadratic model.
Source
Sum of
Squares
DF
Mean of
squares
F Value
Prob > F
Significant
Model80.79
19
4.25
56.74
< 0.0001
A-pH2.21
1
2.21
29.51
0.0003
B-NaCl
0.30
1
0.3
4.01
0.0732
C-Temp
1.14
1
1.14
15.18
0.0030
D-Time
25.12
1
25.12
335.17
< 0.0001
AB0.65
1
0.65
8.72
0.0145
AC0.54
1
0.54
7.15
0.0233
AC0.18
1
0.18
2.39
0.1529
BC1.43
1
1.43
19.06
0.0014
BD1.29
1
1.29
17.22
0.0020
CD4.96
1
4.96
66.22
< 0.0001
A218.60
1
18.60
248.24
< 0.0001
B 0.037
1
0.037
0.49
0.5005
C22.80
1
2.80
37.36
0.0001
D220.27
1
20.27
270.56
< 0.0001
ABC0.58
1
0.58
7.75
0.0193
BCD0.56
1
0.56
7.51
0.0208
A2B1.47
1
1.47
19.62
0.0013
A2D8.06
1
8.06
107.53
< 0.0001
AB 1.39
1
1.39
18.51
0.0016
Residual
0.75
10
0.075
2
2
Lack of Fit
0.24
5
0.048
Pure Error
0.51
5
0.10
Cor Total
81.54
29
0.47
0.7891
2
CV= 4.25 %; R =0.9908; Pred R2=0.822; Adj R2=0.9733; Adeq precision=32.3
As shown in Table 3, the “Model F value” of <0.0001 implies that the model is significant.
The fitness of the model is examined by determination coefficient (R2= 0.9908), which implies
that the sample variation of more than 99.08 % is attributed to the variables and only 0.92% of
the total variance could not be explained by the model. The predicted determination
coefficient (Pred R2= 0.822) is in reasonable agreement with the adjusted determination
coefficient (Adj R2= 0.9733), which is also satisfactory to confirm the fitness of the model. A
lower value of coefficient of variation (CV= 4.25 %) shows the experiments conducted are
precise and reliable. “Adeq Precision” measures the signal-to-noise ratio. A ratio greater than
4 is desirable. The ratio of 32.32 indicates an adequate signal, which implies this model could
be used to navigate the design space.
Response surfaces plots to estimate wool dyeing parameters efficiency over independent
variables are presented in figure 6. Figure 6 shows the effects of the interaction between pH
and time with exhaustion when temperature and salt concentration are constant.
Design points above predicted value
Design points below predicted value
8.5
Sqrt(E%)
8
7.5
7
6.5
60.00
6.25
52.00
5.95
44.00
5.65
36.00
D: Time
5.35
28.00
5.05
20.00
4.75
A: pH
Figure 6. The effects of the interaction between pH and time value with square exhaustion.
4. Conclusions
Rutin dye can provide bright hues and colour fastness properties. It can serve as a
noteworthy source of raw material in the future. Optimized conditions were obtained
for dyeing of wool with rutin contains different range of pH, temperature, NaCl salt
concentration and time. Also, the use of CCD by determining the conditions leading to
high wool dyeing efficiency has demonstrated. The results clearly showed that
response surface methodology is one the suitable methods to optimize the best
operating conditions to maximize the exhaustion percent. A CCD is successfully
employed for experimental design and analysis of the results. The R2 value f 0.9908
indicated a good fit of the model with experimental data.
References
[1] Franzoi, A. C., Migowski, P., Dupont, J., Vieira, I. C, Development of biosensors containing laccase and
imidazolium bis(trifluoromethylsulfonyl)imide ionic liquid for the determination of rutin. Vol. 639, pp. 90-95,
Anal. Chim. Acta., 2009.
[2] Kaur, C., Kapoor, H. C, Physico-chemical diversity in fruits of wild-growing sweeet cherries (prunus
aviuml). Vol. 36, pp. 703-725, Int. J. Food Sci. Technol., 2001.
[3] Kiumarsi, A., Abomahboub, R.M., Rashedi, S., Parvinzadeh, M, Achillea Millefolium, a New Source of
Natural Dye for Wool Dyeing. Vol. 2, pp. 87-93, Color. Colorants Coat., 2009.
[4] Nasirizadeh, N., Zare, H. R, Differential pulse voltammetric simultaneous determination of noradrenalin and
acetaminophen using a hematoxylin biosensor. Vol. 80, pp. 656-663. Talanta., 2009.
[5] Qing, L., Ke-ke, C., Jian-an, Z., Jin-ping, L., Ge-hua, W, Statistical Optimization of Recycled-Paper
Enzymatic Hydrolysis for Simultaneous Saccharification and Fermentation via Central Composite Design. Vol.
160, pp. 604-612, Appl. Biochem. Biotechnol., 2010.
[6] Samanta, A.K., Agarwal, P, Application of natural dyes on textile. Indian J fibre. Vol. 34, pp. 384-399, Text.
Res., 2009.
[7] Zare, H.R., Namazian, M., Nasirizadeh, N, Electrochemical behavior of quercetin: Experimental and
theoretical studies. Vol. 584, pp. 77-83, J. Electroanal. Chem., 2005.

An Investigation about the Spectrophotometric and Electrochemical

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