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Optimization of reactive extraction of propionic acid with ionic liquids using central composite design
Journal Pre-proof Optimization of reactive extraction of propionic acid with ionic liquids using central composite design Emine Ayan Nilay Baylan Suheyla ¨ C ¸ ehreli
PII:
S0263-8762(19)30533-7
DOI:
https://doi.org/doi:10.1016/j.cherd.2019.11.015
Reference:
CHERD 3898
To appear in:
Chemical Engineering Research and Design
Received Date:
6 July 2019
Revised Date:
30 October 2019
Accepted Date:
10 November 2019
Please cite this article as: Ayan, E., Baylan, N., C ¸ ehreli, S.,Optimization of reactive extraction of propionic acid with ionic liquids using central composite design, Chemical Engineering Research and Design (2019), doi: https://doi.org/10.1016/j.cherd.2019.11.015
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GRAPHİCAL ABSTRACT
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Highlights
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• TBP concentration is the most crucial factor on the extraction efficiency. • Ionic liquids can be used as green solvents in propionic acid reactive extraction.
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• CCD based RSM can be employed to design the reactive extraction system.
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Optimization of reactive extraction of propionic acid with ionic liquids using central composite design Emine Ayan1, Nilay Baylan1*, Süheyla Çehreli1 Department of Chemical Engineering, İstanbul University-Cerrahpaşa, Avcılar 34320, İstanbul, Turkey 1
*
Corresponding author. Tel.: +90 212 473 70 70; Fax: +90 212 473 71 80.
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E-mail address: [email protected] (N. Baylan).
ABSTRACT
Propionic acid is widely utilized in different chemical applications and industries such as
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plastic, coating, agricultural, chemical and perfume industries. However, propionic acid occurs in the waste streams of these industries and is produced in aqueous solutions by
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fermentation processes. Thus, removal of propionic acid from both waste streams and production medium is an important topic. In this experimental and optimization study, the
Imidazolium-based hexafluorophosphate
ionic
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reactive extraction of propionic acid from its aqueous solutions was investigated. liquids
([HMIM][PF6])
namely,
1-hexyl-3-methylimidazolium
and
1-hexyl-3-methylimidazolium
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bis(triflorometilsülfonil)imid ([HMIM][Tf2N]), were utilized as diluents, and tributyl phosphate (TBP) was utilized as an extractant. The effect of different factors like initial acid concentration (5-10%, w/w), initial TBP concentration in ionic liquids (0-3 mol.L-1), and aqueous/organic phase ratio (0.5-1.5) on the extraction efficiency was investigated. The optimal conditions were determined by using central composite design (CCD) based on response surface methodology (RSM). The optimization work showed that within the investigated parameters, the most effective parameter was the initial TBP concentration in ionic liquids. The optimum extraction conditions were obtained as initial propionic acid concentration of 5% (w/w), TBP concentration in ionic liquids of 3 mol.L-1 and phase ratio of 0.5. Under these conditions, the experimental extraction efficiencies were found to be 87.56% and 88.16% for [HMIM][PF6] and [HMIM][Tf2N], respectively.
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Keywords: Propionic acid, Ionic liquids, Reactive extraction, Response surface methodology. 1. Introduction Carboxylic acids are extensively utilized in the many industries such as food, pharmaceuticals, cosmetics and detergents. One of the most important and commercially valuable carboxylic acids is propionic acid (Kumar and Babu, 2008; Omar et al., 2009; Wodzki et al., 2000). Propionic acid is a saturated short-chain fatty acid containing ethane bound to the carbon of a carboxy group (Figure 1). Propionic acid is an additive that is
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usually consumed as animal feed and food preservatives. Propionic acid can be produced both chemical and fermentative processes. Due to the increasing demand of propionic acid, it is widely preferred to produce by fermentation process. According to a report released in 2017, the annual production of propionic acid in the world is reported to be 450000 tons
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with an increase of 27% (Gonzalez-Garcia et al., 2017). The increase in production and consumption led to the importance of the efficient separation and purification of propionic
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acid from the aqueous waste streams and production media. The utilization of large amounts of propionic acid requires recovery operations that will increase efficiency and decrease total
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production costs. Solvent extraction, membrane systems, electrodialysis, reverse osmosis, adsorption and ion exchange are common processes for the removal and recovery propionic
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acid from the fermentation broths and wastewaters (Keshav et al., 2008d; Kurzrock and Weuster-Botz, 2010). Reactive extraction has been recommended as an alternative method for the removal of carboxylic acids because of giving a higher distribution coefficient with the suitable extractant (Wasewar et al., 2003).
Figure 1. Structure of propionic acid. Reactive extraction is a separation process based on the reaction of a substance to be extracted with a reactant (Hong and Hong, 2000; Joglekar et al., 2006). The principal
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difference between the solvent extraction and reactive extraction is the reaction between the reactant and the solute in the organic phase. Aliphatic amines and phosphorus-containing compounds have been proposed as effective reactants in literature studies (Kertes and King, 1986). Although the reactants play an important role in the reaction, solvents, also known as diluents, have a substantial effect on the level of extraction. Solvents control the physical properties of the solvent phase and can affect the stability of the complex structure (Holten, 1971). The selection of a reactant and solvent for the reactive extraction should be made on the basis of maximum capacity and minimum toxicity. Hence, there is a need for non-toxic reactant and solvent of a combination of less toxic reactant in a nontoxic solvent that can be
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removed the acid efficiently (Kar et al., 2017; Wasewar et al., 2011). In this regard, tributyl phosphate (TBP) dissolved in green ionic liquids was used in the reactive extraction of propionic acid from the aqueous phase.
In recent years, "ionic liquids" emerges as alternative solvents because of their remarkable
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properties. Ionic liquids (IL’s) are a new group of solvents consisting of certain anions and cations (Fredlake et al., 2004; Ghandi, 2014; Mikami, 2005). Due to their non-flammable,
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non-volatile and recyclable properties, they are classified as green solvents. At the present time, the term of ionic liquid is used for salts which melt under 100 °C. When the melting
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point is under room temperature, IL is named as room temperature ionic liquid (RTIL) (Berthod et al., 2008). The improved solvent properties of these salts and their very low
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vapor pressure have made it inevitable for them to be used as solvents in many reactions (Marsh et al., 2002).
Table 1 demonstrates the literature research related to the propionic acid separation by reactive extraction. As shown in Table 1, the conventional organic solvents like hexane, toluene, kerosene, MIBK, ethyl acetate, octanol and oleyl alcohol have been used in the separation of propionic acid by reactive extraction. However, these solvents have volatile, flammable and toxic properties, so they bring about environmental pollution. That’s why, ionic liquids are being investigated as an alternative new solvent group in replacement of conventional solvents (Djas and Henczka, 2018; Sprakel and Schuur, 2018). Nevertheless, there are a limited number of extraction studies on the use of ionic liquids for the removal of carboxylic acids in the literature. Extraction and reactive extraction studies of carboxylic acids with ionic liquids reported in the literature are presented in Table 2. In this study, the use of imidazolium-based ionic liquids were examined in the reactive extraction of propionic acid.
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Table 1. Reactive extraction studies related to the separation of propionic acid reported in the literature. Reactant
Diluents (solvents)
References
Cyclohexane, hexane, toluene, MIBK and ethyl acetate
(Uslu and İnci, 2007)
TBP, TOA and Aliquat 336
1-octanol
(Keshav et al., 2008d)
TBP
Kerosene and 1-decanol
(Kumar et al., 2011)
Primary amine (N1923)
Hexane, n-octanol and butyl acetate
(Wang et al., 2009)
TOA
Heptane, petroleum ether, ethyl acetate and oleyl alcohol
(Keshav et al., 2008e)
Aliquat 336
MIBK
(Keshav et al., 2009)
TOPO
Hexane
Aliquat 336
2-octanol
Amberlite LA-2
Cyclohexane, 2-octanone, toluene, methyl isobutyl ketone, isooctane, hexane and 1-octanol
(Aşçı and İnci, 2009)
Aliquat 336
Oleyl alcohol
(Keshav et al., 2008c)
Alamine 336
Toluene
TRPO
Kerosene
TBP and TOA
Hexane
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TBP: Tributylphosphate TRPO: Trialkylphosphine oxide
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MIBK: Methyl isobutyl ketone TOPO: Tri‐n‐octylphosphine oxide
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Aliquat 336
(Keshav et al., 2008b) (Keshav et al., 2010)
(Uslu, 2006) (Wang et al., 2001) (Matsumoto et al., 2001) TOA: Trioctylamine
Table 2. Extraction and reactive extraction with ionic liquids related to the separation of carboxylic acid reported in the literature. Acid
Ionic liquids
References
Lactic acid
Tetraalkylphosphonium ionic liquid
(Marták and Schlosser, 2007)
Lactic acid
Tetrabutylphosphonium chloride, Tributyltetradecylphosphonium chloride Trihexyltetradecylphosphonium chloride
(Tonova et al., 2015)
Butyric acid
Trialkylmethylammonium bis-(2,4,4trimethylpentyl)phosphinate
(Blahušiak et al., 2011, 2013)
Butyric acid
Trihexyl-(tetradecyl)phosphonium bis 2,4,4trimethylpentylphosphinate
(Marták and Schlosser, 2008)
L-lactic acid, L-malic acid, succinic acid
Phosphonium-based ionic liquids
(Oliveira et al., 2012)
Glycolic Acid
1-Butyl-3-methylimidazolium hexafluorophosphate
(Aşçı, 2017) (AŞÇI)
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Statistical analysis is one of the first and most important steps in experimental design. In addition to experimental studies, it is important to optimize the examined systems and also to reveal the parameters affecting the system behavior. Experimental design methods are used to understand the structure of systems in different working areas, to determine effective parameters and to perform performance improvement. The aim of the statistical experiment design technique is to reach maximum information with minimum data. Response surface methods are one of the experimental design methods based on statistical basis (Açıkalın and Bolat, 2011).
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Response Surface Methodology (RSM) is a combination of mathematical and statistical methods that develop and optimize industrial formations in different forms. The important points in the scientific studies are determining the effective internal and environmental
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factors on the process, revealing their interactions, modelling of the processes in terms of effective factors, understanding, explaining and planning the process. Optimization studies
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for these purposes are an important step. Mathematical model, which is a function of the optimization process and the variables obtained from the results, in making predictions
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before the trial about the process will shed light plays a key role in the transition to industrial systems. Considering these reasons, the necessity of optimization of a study has great importance. Some of the most practice of these methods are as follows; Central composite
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design, factorial design, Box-Behnken design, 3-level design, hybrid design, pentagonal design, D-optimal design etc.(Baylan and Çehreli, 2018, 2019; Granato and de Araújo Calado, 2014; Turan, 2018).
In this work, the reactive extraction of propionic acid from its aqueous solutions by using ionic liquids was investigated. Firstly, different factors like initial acid concentration, initial TBP concentration in ionic liquids, and water/organic phase ratio affecting on the reactive extraction process were examined experimentally. Then, central composite design (CCD) was also applied to investigate the effect of these factors on the extraction efficiency. The mathematical model equation was derived for extraction efficiency. The experimental data were evaluated by analysis of variance (ANOVA). Finally, optimal reactive extraction conditions were determined by using CCD.
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2. Material and Methods 2.1. Material Propionic acid (PA) is a transparent, uncolored and soluble in water and was supplied by Merck (>99%). Distilled water was utilized to prepare the aqueous solutions of propionic acid in different concentrations. The initial concentrations of propionic acid were varied from 5 to 10 % (w/w). The values of acid concentration in this study were chosen because of the typical acid concentration in fermentation broths. Usually, the fermentation broths include low concentrations of carboxylic acids (less than 10%, w/w). Tributyl phosphate (TBP), was utilized as a reactant, purchased from Sigma-Aldrich (>99%). 1-Hexyl-3-
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methylimidazolium hexafluorophosphate [HMIM][PF6] and 1-Hexyl-3- methylimidazolium bis(trifluoromethylsulfonyl)imide [HMIM][Tf2N] were utilized as diluents, purchased from Iolitec (>99%). The initial concentrations of TBP were varied in the range of 0-3 mol.L-1 in ionic liquids.
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2.2. Methods
The volumes of aqueous solutions (propionic acid+water) and organic solutions (TBP+ionic
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liquid) were 2 mL. The extraction experiments were executed by shaking in a water bath (Nüve ST 30) at room temperature and 150 rpm for predetermined optimum time (1 h).
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Samples were centrifuged at 3000 rpm for 10 min to separate the aqueous and organic phases. The acid concentrations in the aqueous solutions were detected by the Schott
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Titroline automatic titrator by using 0.1 N sodium hydroxide. The acid concentrations in the organic phase were specified from the material balance. A few experiments were repeated and the data were obtained to be within ±2% of accuracy. The experimental data were appreciated by using the extraction efficiency (E), distribution coefficient (d) and loading factor (Z). These parameters were calculated by means of the following equations (İnci, 2007):
The extraction efficiency (E) is characterized as the proportion of the concentration of extracted acid to concentration of initial acid. It is remarked as following equation: (1) The distribution coefficient (d) is explained as the acid extracted from water into organic phase. It is written as:
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(2) The loading of factor (Z), is expressed as the concentration of acid in the organic phase divided by the concentration of reactant in the organic phase
. It can be
signified as:
Z=
(3)
In these equations, CA,0 is the initial acid concentration in the aqueous phase (mol.L-1), CA is
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the acid concentration in the aqueous phase at the end of the extraction (mol.L-1), CA,org is the acid concentration in the organic phase at the end of the extraction (mol.L-1) and CR,org is the reactant concentration in the organic phase (mol.L-1). 2.3. Experimental Design
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CCD (face-centered) was employed to optimize the reactive extraction process, reveal a correlation between independent variables (factors) and dependent variable (response) and
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obtain the model equation representing the extraction system. CCD was designed on considering the different parameters on affecting reactive extraction explained in Section
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3.2. For these purposes, the software Design-Expert® 11.0 Trial Version, (Stat-Ease, Inc., Minneapolis, USA) was used. The initial propionic acid concentration (X1), initial TBP
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concentration in ionic liquid (X2), and phase ratio (aqueous phase volume:organic phase volume, X3) were chosen as the independent variables, and extraction efficiency (Y) was selected as the dependent variable in this design study. The aqueous phase volume:organic phase volume (phase ratio) was studied as 2 mL:4 mL (phase ratio:0.5), 2 mL:2 mL (phase ratio:1) and 3 mL:2 mL (phase ratio:1.5). The independent variables were presented in Table 3 together with their symbols and levels. Table 3. Independent variables and their levels in CCD. Levels Independent variables
Symbols -1
0
1
Initial acid concentration (%)
X1
5
7.5
10
Initial TBP concentration (mol/L)
X2
0
1.5
3
Phase ratio
X3
0.5
1
1.5
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The relation between the chosen independent variables and the dependent variable is written as: Y=f (X1, X2,…..,,Xn)+ ℇ
(4)
For CCD, the model equation is transformed into a second-order polynomial, and the response value is calculated depending on the factors in the second-order model. The model equation representing response can be written in the form (Cho and Zoh, 2007):
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(5)
In these equations, Y is dependent variable or response, X1, X2,..,Xn are the factors or independent variables, f is the function of dependent variable, ε is an error, β0 is the constant
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coefficient, βi, βii, βij are the coefficient of each variable and k is the number of variable. 3. Results and Discussion
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3.1. Determination of the optimum extraction time
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Various experiments were performed to determine the optimum extraction time. For the optimum time determination experiments, 10% by weight of propionic acid and an ionic liquid [HMIM][PF6] was utilized. In addition, in order to examine the effect of addition of
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TBP on the extraction time, TBP concentration in ionic liquid was adjusted to 3 mol/L and the experiments were performed. The results of these experiments were shown in Figure 2. According to the experimental results indicated in Figure 2, the optimum extraction time was determined as an hour.
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Figure 2. The effect of time on propionic acid reactive extraction. 3.2. Effect of different parameters on reactive extraction
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The effect of different factors like initial propionic acid concentration, initial TBP concentration in ionic liquid and phase ratio (aqueous phase volume/organic phase volume)
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on the reactive extraction were investigated. In the literature survey, the most-examined factors in the reactive extraction such as reactant concentration, acid concentration were
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reported (Asçı and İncı̇ , 2009; Datta and Kumar, 2011). Firstly, various experiments were performed to specify the effect of the initial concentration of propionic acid. In these experiments, initial propionic acid concentrations of 5%, 7.5% and 10% (w/w) were used. The
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initial TBP concentrations were varied 0 to 3 mol/L in [HMIM][PF6], and phase ratio is 1. Using the experimental data, the distribution coefficient (d), loading factor (Z) and extraction efficiency (% E) were calculated using Equations 1-3. Figure 3 depicts the distribution coefficient (d), loading ratio (Z) and extraction efficiency (E) values for the different initial acid concentration.
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Figure 3. The effect of initial propionic acid concentration on the distribution coefficient (d), loading factor (Z) and extraction efficiency (E) □ 5% ♦7.5% ▲10%. (phase ratio:1).
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Figure 4. The effect of phase ratio on the distribution coefficient (d), loading factor (Z) and extraction efficiency (E) ♦Phase ratio:0.5 □ Phase ratio:1 ▲Phase ratio:1.5 (Initial propionic acid concentration:10% w/w).
From Figure 3, it was analyzed that the initial acid concentration had no significant effect on both distribution coefficient (d) and extraction efficiency (E) over the investigated acid concentration range. In the literature, İnci and Uslu (İnci and Uslu, 2005) examined the reactive extraction of citric acid using trioctyl methyl ammonium chloride and they reported that the distribution coefficient increased from 0.16 to 0.23 and the extraction efficiency increased from 14.29% to 19.05% with increasing initial acid concentration from 0.105 mol.L-1 to 0.210 mol.L-1, and also, the distribution coefficient increased slightly from 0.23 to 0.26 and the extraction efficiency increased from 19.05% to 20.63% with increasing initial acid concentration from 0.210 mol.L-1 to 0.315 mol.L-1. Kumar et al. (Kumar et al., 2006)
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examined the recovery of propionic acid using reactive extraction and they observed that the distribution coefficient decreased slightly from 2.30 to 2.14 with increasing initial propionic acid concentration from 0.675 to 1.35 g mol.L-1. In the reactive extraction process, the concentration of the extractant is key factor. So, TBP concentration in the organic phase is more effective parameter than the initial acid concentration. Figure 3 also showed that the extraction efficiencies and distribution coefficients were increased significantly with increasing TBP concentration in [HMIM][PF6]. These results were further confirmed by observations from similar reactive extraction studies (Keshav et al., 2008a; Uslu and İnci, 2007). Furthermore, Figure 3 indicated that, the values of loading factor varied from 0.19 to
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0.69 with increasing the TBP concentration in [HMIM][PF6] and initial propionic acid concentration, meaning that complexes contain more than one phosphate per complex. Overloading, loading factor greater than unity, represents that the complexes with more than one acid molecule per phosphate are created (Aşçı and İncı̇ , 2010).
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To examine the effect of phase ratio on the reactive extraction, the experiments were carried out by using the concentration of propionic acid of 10% w/w, TBP concentration in
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[HMIM][PF6] of 0-3 mol/L and phase ratio of 0.5-1.5. The values of distribution coefficient (d), loading ratio (Z) and extraction efficiency (E) at different phase ratios were illustrated in
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Figure 4. As shown in Figure 4, as the phase ratio increased, the values of extraction efficiency, distribution coefficient and loading factor decreased. Chawong, and Rattanaphanee
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(Chawong and Rattanaphanee, 2011) studied n-butanol as an extractant for lactic acid recovery and they found that the extraction efficiency decreased from 96.97 to 51.01 with increasing phase ratio from 0.25 to 1. Kahya et al. (Kahya et al., 2001) investigated the reactive extraction of lactic acid by using Alamine 336 diluted with oleyl alcohol. The distribution coefficient decreased with increasing aqueous volume (Vaq)/organic volume (Vorg) ratio.
3.3. Central Composite Design Study In CCD study, the variables and levels given in Table 3 were entered into the Design Expert® program and 20 different reactive extraction systems as shown in Table 4 were obtained. These systems were studied experimentally for two ionic liquids ([HMIM][PF6] and [HMIM][Tf2N]) to determine the effect of ionic liquid type. The obtained experimental results were analyzed statistically using ANOVA. ANOVA results obtained for extraction efficiency (Y) for [HMIM][PF6] and [HMIM][Tf2N] were presented in
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Table 5, respectively. In ANOVA results, F-value or Prob>F and p-value of the model give information about whether the model is important or not (Chen et al., 2011). When the Fvalue (98.72) and p-value (<0.0001) in Table 5 model were examined, it was seen that the model is important for the response. Table 4. CCD layout and experimental results. TBP concentration X2
Phase ratio X3
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
5 5 5 5 5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 10 10 10 10 10
0 0 1.5 3 3 0 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 3 0 0 1.5 3 3
0.5 1.5 1 0.5 1.5 1 0.5 1 1 1 1 1 1 1.5 1 0.5 1.5 1 0.5 1.5
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Extraction efficiency (%) Y [HMIM][PF6] 37.87 19.51 65.29 87.56 68.33 25.81 77.38 63.54 62.81 63.79 63.30 63.32 64.28 45.38 79.62 41.95 20.12 60.74 87.30 64.66
[HMIM][Tf2N] 47.42 25.88 45.83 88.16 72.29 31.45 78.66 44.11 42.98 43.27 44.75 44.41 45.14 52.62 74.40 50.20 27.03 48.47 87.00 62.55
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Initial acid concentration X1
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Experiment number
The significance of model terms is analyzed by means of p-value. The p-value lower than 0.05 of the model terms indicates that the model terms are meaningful and have a substantial effect on the response (Baylan and Çehreli, 2018). According to p-values in Table 5, TBP concentration (X2), phase ratio (X3) and the square of the interaction of TBP concentration (X22) were substantial model terms and had a significant effect on the extraction efficiency for the reactive extraction of propionic acid with [HMIM][PF6]. Similarly, according to p-values in Table 5, TBP concentration (X2), phase ratio (X3) and the square of the interaction of phase ratio (X32) were significant model terms for the reactive extraction of propionic acid with [HMIM][Tf2N]. In other words, the model equation representing the extraction efficiency consists of these model terms. X2, X3 model terms had a linear effect on the experimental
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results of two ionic liquids. X22 of model term had an exponential effect on the experimental results of [HMIM][PF6], and X32 of model terms had an exponential effect on the experimental results of [HMIM][Tf2N]. This situation can be clarified by the difference of ionic liquid type.
Table 5. ANOVA data for extraction efficiency (Y) in the reactive extraction of propionic acid with [HMIM][PF6] and [HMIM][Tf2N]. [HMIM][PF6] Sum of
Source
squares
df
[HMIM][Tf2N]
Mean
F
p-Value
square
value
Prob>F
9
849.89
98.72
X1
1.44
1
1.44
0.1669
X2
5866.57
1
5866.57
681.45
X3
1300.97
1
1300.97
151.12
X 1X 2
9.29
1
9.29
1.08
X 1X 3
5.92
1
5.92
X 2X 3
0.3528
1
1.59
<
squares
df
Mean
F
p-Value
square
value
Prob>F
<
6230.96
9
692.23
34.02
1.87
1
1.87
0.0921
4097.39
1
4097.39
201.33
1233.65
1
1233.65
60.62
0.3234
27.49
1
27.49
1.35
0.2721
0.6873
0.4264
13.03
1
13.03
0.6403
0.4422
0.3528
0.0410
0.8436
2.41
1
2.41
0.1184
0.7376
1
1.59
0.1843
0.6768
48.67
1
48.67
2.39
0.1530
250.31
1
250.31
29.07
0.0003
6.76
1
6.76
0.3323
0.5771
2.11
1
2.11
0.2448
0.6314
561.03
1
561.03
27.57
0.0004
86.09
10
8.61
203.52
10
20.35
Lack of fit
83.67
5
16.73
199.97
5
39.99
56.44
0.0002
Pure error
2.45
5
0.4898
3.54
5
0.7086
Total
7735.08
19
6434.48
19
X 32 Residual
R2
0.6915 <
0.0001 <
0.0001
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X2
2
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X1
2
0.0001
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7648.99
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Model
Sum of
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Ionic liquid
34.15
0.0007
0.9889
0.9684
R2Adj
0.9789
0.9399
R2Pred
0.9175
0.8400
AP
34.7092
20.0169
CV%
5.05
8.54
SD
2.93
4.51
0.0001 0.7677 < 0.0001 < 0.0001
*SD: Standard deviation, AP: Adequate precision CV: Coefficient of variation
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To obtain the model equation, R2 values of the candidate models such as linear, quadratic, cubic model were checked and the model with the highest R2 value was employed. As a result, second-order model equations representing the extraction efficiency (Y) for the reactive extraction of propionic acid with ionic liquids were acquired as Eqs 6 and 7: [HMIM][PF6]
Y= 62.91 + 24.22 X2 – 11.41 X3 – 9.54 X22
(6)
[HMIM][Tf2N]
Y= 47.01 + 20.24 X2 – 11.11 X3 + 14.28 X32
(7)
When the model equations were examined, it was clear that the parameters affecting the
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extraction efficiency were TBP concentration (X2) and phase ratio (X3). With the increase in the initial TBP concentration, the extraction efficiency increased. However, the extraction efficiency decreased with the increase in the phase ratio. Since it had the highest coefficient in the model equations, it can be said that TBP concentration (X2) was the most effective
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parameter on extraction efficiency. In addition to, it can be clearly seen that the initial propionic acid concentration (X1) was not an influential variable on the extraction efficiency
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in both model equations.
Table 5 also presents the statistical parameters utilized to control the adequacy and accuracy
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of the model equations. The correlation coefficient, R2, is defined as a measure of the degree of compliance. When the R2 approaches to unity, the difference between the predicted and
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experimental data is very small, and so the predicted model is better suited to the experimental data (Chen et al., 2011). In this design study, as can be seen in Table 5, the values of R2 were found to be quite high. It demonstrated that the model equations were wellsuited to the experimental data. Adjusted R2 (R2Adj) is defined as a measure of the amount of change around the mean (Chen et al., 2011). The fact that the R2 and R2Adj values are close to each other indicates that the model sufficiently represents experimental results. The difference between the predicted R2 (R2Pred) and R2Adj is less than 0.2 indicating that these values are in reasonable agreement with each other. Furthermore, adequate precision (AP) is a measure of the signal to noise ratio and is desired to be greater than 4. Coefficient of variation (CV) signifies a measure of the proportion of the standard deviation to the mean and is supposed to be quite low (Baylan and Çehreli, 2019). AP values were obtained as 34.7092 for [HMIM][PF6] and 20.0169 for [HMIM][Tf2N]. CV values were acquired as 5.05% for [HMIM][PF6] and 8.54% for [HMIM][Tf2N], respectively. These results indicated that the obtained model equations were consistent with experimental data.
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Other control points for the verification of the experimental results are the analysis of diagnostic plots (predicted vs. actual plot or residuals vs. predicted plot). The predicted vs. actual plot indicates that the points must be aligned with a straight line. The residuals vs. predicted plot shows whether the residuals are in normal distribution (Asghar et al., 2014; Rajmohan and Palanikumar, 2013). These plots were checked for the adequacy and accuracy of model equations for each ionic liquid. Diagnostic plots were illustrated in Figure 5. As illustrated in Figure 5.a, all points were within the range and showed normal distribution. As shown in Figure 5.b, the experimental values were aligned as a straight line. These results
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demonstrated that the predicted values by the model were in agreement with the experimental
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data.
[HMIM][PF6] (a)
[HMIM][PF6] (b)
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[HMIM][Tf2N] (a)
[HMIM][Tf2N] (b)
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Figure 5. Diagnostic plots of CCD model for [HMIM][PF6] and [HMIM][Tf2N]. (a) predicted vs actual plot (b) residuals vs. predicted plot.
[HMIM][PF6]
[HMIM][Tf2N] (a)
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[HMIM][Tf2N]
[HMIM][PF6]
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(b)
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[HMIM][PF6]
[HMIM][Tf2N]
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(c) Figure 6. Response surface graphs for the extraction efficiency in the reactive extraction of propionic acid with [HMIM][PF6]. (a) the effect of initial acid concentration (X1) and TBP concentration (X2) in case of phase ratio of 1. (b) the effect of TBP concentration (X2) and phase ratio (X3) in case of initial acid concentration of 7.5%. (c) the effect of initial acid concentration (X1) and phase ratio (X3) in case of TBP concentration of 1.5 mol/L.
Response surface graphs of the model equations were plotted to explain the effect of independent variables on the extraction efficiency. The response surface graphs were plotted for two selected variables while one variable was held at intermediate level. The response surface graphs of model equations were shown in Figure 6. From Figure 6, the extraction efficiency increased with increasing TBP concentration in ionic liquids, nevertheless it decreased with increase in phase ratio. As the initial propionic acid concentration was increased, the extraction efficiency did not change. When TBP concentration and phase ratio effects on the extraction efficiency were compared (Figures 6.b), it can be said that TBP concentration was more influential variable than the phase ratio.
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The final stage of the design is the determination of the criteria for optimization. Optimization criterion was the maximum extraction efficiency and all independent variables was kept within in range. These conditions was executed at Design-Expert® Software and the optimal points for the reactive extraction of propionic acid were determined as given in Table 6. Besides, under optimal points, the experiments were conducted and the experimental extraction efficiency values were also added in Table 6. As can be observed in Table 6, the predicted model values were compatible with the experimental data. Table 6. The optimal reactive extraction points for each ionic liquid. Initial acid concentration (% w/w)
TBP concentration (mol/L)
Phase ratio
Extraction efficiency (%) Predicted
Extraction efficiency (%) Experimental
Desirability
[HMIM][PF6]
5.000
3.000
0.500
89.683
87.560
1.000
[HMIM][Tf2N]
5.000
3.000
0.500
90.464
88.160
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3.4. Comparison of selectivity of ionic liquids
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Ionic liquid type
Considering the effect of parameters on propionic acid extraction as mentioned before, TBP
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concentration was the most influential parameter, whereas the initial propionic acid concentration was not efficient parameter. Additionally, taking the effect of phase ratio and the optimal extraction conditions in consideration, a comparison was made illustrated in
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Figure 7.
As can be observed in Figure 7, in the event of purely ionic liquids in the organic phase (5-00.5 and 5-0-1.5 experiment systems), the values of extraction efficiency acquired for both ionic liquids were very close to each other, but relatively [HMIM][Tf2N] can be said to be more selective. In the event of using TBP in ionic liquids (5-3-0.5 and 5-3-1.5 experiment systems), the values of extraction efficiency were almost same, the effect of the ionic liquid type did not obviously observed for the reactive extraction of propionic acid. This result implied that TBP effect was more dominant than the type of ionic liquid. This work also showed that these imidazolium-based ionic liquids can be utilized as extraction solvents in the removal of propionic acid.
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Figure 7. The selectivity of ionic liquids in different systems.
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4. Conclusion
In this research, imidazolium-based ionic liquids namely [HMIM][PF6] and [HMIM][Tf2N]
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were tested in the reactive extraction of propionic acid by using TBP. CCD was employed to investigate the effect of different factors like initial acid concentration, TBP concentration in ionic liquids, and aqueous/organic phase ratio on the extraction efficiency. The experimental
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data were appreciated statistically by ANOVA. Model equations were derived for the extraction efficiency. The adequacy and accuracy of model equations was confirmed by means of graphical analysis and statistical parameters. This design study was concluded that the obtained model equations were in good agreement with the experimental data. The factors affecting the extraction efficiency were detected as TBP concentration and phase ratio. The extraction efficiency increased with increasing TBP concentration, and also it decreased with the increase in the phase ratio. Initial TBP concentration in ionic liquids had the most crucial parameter on the extraction efficiency. However, the initial propionic acid concentration was not an influential factor on the extraction efficiency. Finally, the optimal extraction conditions for both ionic liquids were detected. The optimum conditions were obtained as initial propionic acid concentration of 5% (w/w), TBP concentration in ionic liquids of 3 mol.L-1, phase ratio of 0.5. The extraction efficiency values for both ionic liquids were acquired very close to each other. This investigation has also indicated that ionic liquids [HMIM][PF6] and
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[HMIM][Tf2N] as green extraction solvents can be successfully employed in the reactive extraction of propionic acid. References Açıkalın, K., Bolat, E., 2011. Modelling of pyrolysis yields of pistachio shells by using various experimental design methods. Sigma 29, 52-64. Asghar, A., Raman, A., Aziz, A., Daud, W.M.A.W., 2014. A comparison of central composite design and Taguchi method for optimizing Fenton process. The Scientific World Journal 2014, 1-14. Aşçı, Y.S., 2017. Examination of the efficiency of ionic liquids in glycolic acid separation from
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aqueous solution by using reactive extraction method. Journal of the Turkish Chemical Society, Section A: Chemistry 4, 981-992.
Aşçı, Y.S., İncı̇ , İ, 2009. Extraction of glycolic acid from aqueous solutions by Amberlite LA2 in different diluent solvents. Journal of Chemical & Engineering Data 54, 2791-2794. Aşçı, Y.S., İnci, İ., 2009. Extraction equilibria of propionic acid from aqueous solutions by Amberlite
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LA-2 in diluent solvents. Chemical Engineering Journal 155, 784-788.
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Aşçı, Y.S., İncı̇ , İ., 2010. Extraction equilibria of acrylic acid from aqueous solutions by amberlite LA-2 in various diluents. Journal of Chemical & Engineering Data 55, 2385-2389.
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Baylan, N., Çehreli, S., 2018. Ionic liquids as bulk liquid membranes on levulinic acid removal: A design study. Journal of Molecular Liquids 266, 299-308. Baylan, N., Çehreli, S., 2019. Removal of acetic acid from aqueous solutions using bulk ionic liquid
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Berthod, A., Ruiz-Angel, M., Carda-Broch, S., 2008. Ionic liquids in separation techniques. Journal of Chromatography A 1184, 6-18.
Blahušiak, M., Schlosser, Š., Marták, J., 2011. Extraction of butyric acid by a solvent impregnated resin containing ionic liquid. Reactive and Functional Polymers 71, 736-744. Blahušiak, M., Schlosser, Š., Marták, J., 2013. Extraction of butyric acid with a solvent containing ammonium ionic liquid. Separation and Purification Technology 119, 102-111. Chawong, K., Rattanaphanee, P., 2011. n-Butanol as an extractant for lactic acid recovery. World Academy of Science, Engineering and Technology 80, 239-242. Chen, C.-C., Chiang, K.-T., Chou, C.-C., Liao, Y.-C., 2011. The use of D-optimal design for modeling and analyzing the vibration and surface roughness in the precision turning with a diamond cutting tool. The International Journal of Advanced Manufacturing Technology 54, 465-478.
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Cho, I.-H., Zoh, K.-D., 2007. Photocatalytic degradation of azo dye (Reactive Red 120) in TiO2/UV system: Optimization and modeling using a response surface methodology (RSM) based on the central composite design. Dyes and Pigments 75, 533-543. Datta, D., Kumar, S., 2011. Reactive extraction of glycolic acid using tri-n-butyl phosphate and tri-noctylamine in six different diluents: Experimental data and theoretical predictions. Industrial & Engineering Chemistry Research 50, 3041-3048. Djas, M., Henczka, M., 2018. Reactive extraction of carboxylic acids using organic solvents and supercritical fluids: A review. Separation and Purification Technology 201, 106-119. Fredlake, C.P., Crosthwaite, J.M., Hert, D.G., Aki, S.N., Brennecke, J.F., 2004. Thermophysical
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properties of imidazolium-based ionic liquids. Journal of Chemical & Engineering Data 49, 954-964. Ghandi, K., 2014. A review of ionic liquids, their limits and applications. Green and sustainable chemistry 4, 44-53.
Gonzalez-Garcia, R., McCubbin, T., Navone, L., Stowers, C., Nielsen, L., Marcellin, E., 2017.
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Granato, D., de Araújo Calado, V.M., 2014. The use and importance of design of experiments (DOE)
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Holten, C.H., 1971. Lactic acid. Properties and chemistry of lactic acid and derivatives. Weinheim/Bergstr., W. Germany, Verlag Chemie GmbH.
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Hong, Y., Hong, W.-H., 2000. Reactive extraction of succinic acid with tripropylamine (TPA) in various diluents. Bioprocess Engineering 22, 281-284. İnci, İ., 2007. Linear solvation energy relationship modeling and kinetic studies on reactive extraction of succinic acid by tridodecylamine dissolved in MIBK. Biotechnology Progress 23, 1171-1179. İnci, İ., Uslu, H., 2005. Investigation of diluent effect on extraction of citric acid by trioctyl methyl ammonium chloride+ organic solutions. Journal of Chemical & Engineering Data 50, 1103-1107. Joglekar, H., Rahman, I., Babu, S., Kulkarni, B., Joshi, A., 2006. Comparative assessment of downstream processing options for lactic acid. Separation and Purification Technology 52, 1-17. Kahya, E., Bayraktar, E., Mehmetoğlu, Ü., 2001. Optimization of process parameters for reactive lactic acid extraction. Turkish Journal of Chemistry 25, 223-230. Kar, A., Bagde, A., Athankar, K.K., Wasewar, K.L., Shende, D.Z., 2017. Reactive extraction of acrylic acid with tri‐n‐butyl phosphate in natural oils. Journal of Chemical Technology & Biotechnology 92, 2825-2834.
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Kertes, A., King, C.J., 1986. Extraction chemistry of fermentation product carboxylic acids. Biotechnology and Bioengineering 28, 269-282. Keshav, A., Chand, S., Wasewar, K.L., 2008a. Equilibrium studies for extraction of propionic acid using tri-n-butyl phosphate in different solvents. Journal of Chemical & Engineering Data 53, 14241430. Keshav, A., Wasewar, K., Chand, S., Uslu, H., 2010. Reactive extraction of propionic acid using Aliquat-336 in 2-octanol: Linear solvation energy relationship (LSER) modeling and kinetics study. Chemical and Biochemical Engineering Quarterly 24, 67-73. Keshav, A., Wasewar, K.L., Chand, S., 2008b. Equilibrium and Kinetics of the Extraction of
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Propionic Acid Using Tri‐n‐Octylphosphineoxide. Chemical Engineering & Technology: Industrial Chemistry‐Plant Equipment‐Process Engineering‐Biotechnology 31, 1290-1295.
Keshav, A., Wasewar, K.L., Chand, S., 2008c. Extraction of acrylic, propionic, and butyric acid using Aliquat 336 in oleyl alcohol: Equilibria and effect of temperature. Industrial & Engineering Chemistry
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Research 48, 888-893.
Keshav, A., Wasewar, K.L., Chand, S., 2008d. Extraction of propionic acid using different extractants
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(tri-n-butylphosphate, tri-n-octylamine, and Aliquat 336). Industrial & Engineering Chemistry Research 47, 6192-6196.
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Keshav, A., Wasewar, K.L., Chand, S., 2008e. Extraction of propionic acid with tri-n-octyl amine in different diluents. Separation and Purification Technology 63, 179-183.
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Keshav, A., Wasewar, K.L., Chand, S., 2009. Reactive extraction of propionic acid using Aliquat 336 in MIBK: Linear solvation energy relationship (LSER) modeling and kinetics study. Journal of Scientific and Industrial Research 68, 708-713. Kumar, S., Babu, B., Wasewer, K., 2006. Recovery of propionic acid using reactive extraction, Proceedings of International Symposium & 59th Annual Session of IIChE. Citeseer, 27-30. Kumar, S., Babu, B., 2008. Process intensification for separation of carboxylic acids from fermentation broths using reactive extraction. Journal on Future Engineering & Technology 3, 19-26. Kumar, S., Datta, D., Babu, B., 2011. Differential evolution approach for reactive extraction of propionic acid using tri-n-butyl phosphate (TBP) in kerosene and 1-decanol. Materials and Manufacturing Processes 26, 1222-1228. Kurzrock, T., Weuster-Botz, D., 2010. Recovery of succinic acid from fermentation broth. Biotechnology Letters 32, 331-339.
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Marsh, K.N., Deev, A., Wu, A.C., Tran, E., Klamt, A., 2002. Room temperature ionic liquids as replacements for conventional solvents–A review. Korean Journal of Chemical Engineering 19, 357362. Marták, J., Schlosser, Š., 2007. Extraction of lactic acid by phosphonium ionic liquids. Separation and Purification Technology 57, 483-494. Marták, J., Schlosser, Š., 2008. Liquid-liquid equilibria of butyric acid for solvents containing a phosphonium ionic liquid. Chemical Papers 62, 42-50. Matsumoto, M., Otono, T., Kondo, K., 2001. Synergistic extraction of organic acids with tri-noctylamine and tri-n-butylphosphate. Separation and Purification Technology 24, 337-342.
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Mikami, K., 2005. Green reaction media in organic synthesis. Wiley Online Library.
Oliveira, F.S., Araújo, J.M., Ferreira, R., Rebelo, L.P.N., Marrucho, I.M., 2012. Extraction of L-lactic, L-malic, and succinic acids using phosphonium-based ionic liquids. Separation and Purification
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Omar, F.N., Rahman, N., Hafid, H.S., Yee, P.L., Hassan, M.A., 2009. Separation and recovery of organic acids from fermented kitchen waste by an integrated process. African Journal of
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Rajmohan, T., Palanikumar, K., 2013. Modeling and analysis of performances in drilling hybrid metal matrix composites using D-optimal design. The International Journal of Advanced Manufacturing Technology 64, 1249-1261.
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Sprakel, L., Schuur, B., 2018. Solvent developments for liquid-liquid extraction of carboxylic acids in perspective. Separation and Purification Technology 211, 935-957. Tonova, K., Svinyarov, I., Bogdanov, M.G., 2015. Biocompatible ionic liquids in liquid–liquid extraction of lactic acid: A comparative study. Int. J. Chem. Nuclear Mater. Metallurgical Eng 9, 526530.
Turan, M.D., 2018. Statistical Approach to Mineral Engineering and Optimization, Contributions to Mineralization. IntechOpen.
Uslu, H., 2006. Linear solvation energy relationship (LSER) Modeling and kinetic studies on propionic acid reactive extraction using alamine 336 in a toluene solution. Industrial & Engineering Chemistry Research 45, 5788-5795. Uslu, H., İnci, İ., 2007. (Liquid+ liquid) equilibria of the (water+ propionic acid+ Aliquat 336+ organic solvents) at T= 298.15 K. The Journal of Chemical Thermodynamics 39, 804-809.
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Wang, K., Chang, Z., Ma, Y., Lei, C., Jin, S., Wu, Y., Mahmood, I., Hua, C., Liu, H., 2009. Equilibrium study on reactive extraction of propionic acid with N1923 in different diluents. Fluid Phase Equilibria 278, 103-108. Wang, Y., Li, Y., Li, Y., Wang, J., Li, Z., Dai, Y., 2001. Extraction equilibria of monocarboxylic acids with trialkylphosphine oxide. Journal of Chemical & Engineering Data 46, 831-837. Wasewar, K.L., Pangarkar, V.G., Heesink, A.B.M., Versteeg, G.F., 2003. Intensification of enzymatic conversion of glucose to lactic acid by reactive extraction. Chemical Engineering Science 58, 33853393. Wodzki, R., Nowaczyk, J., Kujawski, M., 2000. Separation of propionic and acetic acid by pertraction
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PII:
S0263-8762(19)30533-7
DOI:
https://doi.org/doi:10.1016/j.cherd.2019.11.015
Reference:
CHERD 3898
To appear in:
Chemical Engineering Research and Design
Received Date:
6 July 2019
Revised Date:
30 October 2019
Accepted Date:
10 November 2019
Please cite this article as: Ayan, E., Baylan, N., C ¸ ehreli, S.,Optimization of reactive extraction of propionic acid with ionic liquids using central composite design, Chemical Engineering Research and Design (2019), doi: https://doi.org/10.1016/j.cherd.2019.11.015
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.
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GRAPHİCAL ABSTRACT
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Highlights
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• TBP concentration is the most crucial factor on the extraction efficiency. • Ionic liquids can be used as green solvents in propionic acid reactive extraction.
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• CCD based RSM can be employed to design the reactive extraction system.
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Optimization of reactive extraction of propionic acid with ionic liquids using central composite design Emine Ayan1, Nilay Baylan1*, Süheyla Çehreli1 Department of Chemical Engineering, İstanbul University-Cerrahpaşa, Avcılar 34320, İstanbul, Turkey 1
*
Corresponding author. Tel.: +90 212 473 70 70; Fax: +90 212 473 71 80.
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E-mail address: [email protected] (N. Baylan).
ABSTRACT
Propionic acid is widely utilized in different chemical applications and industries such as
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plastic, coating, agricultural, chemical and perfume industries. However, propionic acid occurs in the waste streams of these industries and is produced in aqueous solutions by
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fermentation processes. Thus, removal of propionic acid from both waste streams and production medium is an important topic. In this experimental and optimization study, the
Imidazolium-based hexafluorophosphate
ionic
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reactive extraction of propionic acid from its aqueous solutions was investigated. liquids
([HMIM][PF6])
namely,
1-hexyl-3-methylimidazolium
and
1-hexyl-3-methylimidazolium
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bis(triflorometilsülfonil)imid ([HMIM][Tf2N]), were utilized as diluents, and tributyl phosphate (TBP) was utilized as an extractant. The effect of different factors like initial acid concentration (5-10%, w/w), initial TBP concentration in ionic liquids (0-3 mol.L-1), and aqueous/organic phase ratio (0.5-1.5) on the extraction efficiency was investigated. The optimal conditions were determined by using central composite design (CCD) based on response surface methodology (RSM). The optimization work showed that within the investigated parameters, the most effective parameter was the initial TBP concentration in ionic liquids. The optimum extraction conditions were obtained as initial propionic acid concentration of 5% (w/w), TBP concentration in ionic liquids of 3 mol.L-1 and phase ratio of 0.5. Under these conditions, the experimental extraction efficiencies were found to be 87.56% and 88.16% for [HMIM][PF6] and [HMIM][Tf2N], respectively.
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Keywords: Propionic acid, Ionic liquids, Reactive extraction, Response surface methodology. 1. Introduction Carboxylic acids are extensively utilized in the many industries such as food, pharmaceuticals, cosmetics and detergents. One of the most important and commercially valuable carboxylic acids is propionic acid (Kumar and Babu, 2008; Omar et al., 2009; Wodzki et al., 2000). Propionic acid is a saturated short-chain fatty acid containing ethane bound to the carbon of a carboxy group (Figure 1). Propionic acid is an additive that is
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usually consumed as animal feed and food preservatives. Propionic acid can be produced both chemical and fermentative processes. Due to the increasing demand of propionic acid, it is widely preferred to produce by fermentation process. According to a report released in 2017, the annual production of propionic acid in the world is reported to be 450000 tons
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with an increase of 27% (Gonzalez-Garcia et al., 2017). The increase in production and consumption led to the importance of the efficient separation and purification of propionic
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acid from the aqueous waste streams and production media. The utilization of large amounts of propionic acid requires recovery operations that will increase efficiency and decrease total
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production costs. Solvent extraction, membrane systems, electrodialysis, reverse osmosis, adsorption and ion exchange are common processes for the removal and recovery propionic
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acid from the fermentation broths and wastewaters (Keshav et al., 2008d; Kurzrock and Weuster-Botz, 2010). Reactive extraction has been recommended as an alternative method for the removal of carboxylic acids because of giving a higher distribution coefficient with the suitable extractant (Wasewar et al., 2003).
Figure 1. Structure of propionic acid. Reactive extraction is a separation process based on the reaction of a substance to be extracted with a reactant (Hong and Hong, 2000; Joglekar et al., 2006). The principal
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difference between the solvent extraction and reactive extraction is the reaction between the reactant and the solute in the organic phase. Aliphatic amines and phosphorus-containing compounds have been proposed as effective reactants in literature studies (Kertes and King, 1986). Although the reactants play an important role in the reaction, solvents, also known as diluents, have a substantial effect on the level of extraction. Solvents control the physical properties of the solvent phase and can affect the stability of the complex structure (Holten, 1971). The selection of a reactant and solvent for the reactive extraction should be made on the basis of maximum capacity and minimum toxicity. Hence, there is a need for non-toxic reactant and solvent of a combination of less toxic reactant in a nontoxic solvent that can be
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removed the acid efficiently (Kar et al., 2017; Wasewar et al., 2011). In this regard, tributyl phosphate (TBP) dissolved in green ionic liquids was used in the reactive extraction of propionic acid from the aqueous phase.
In recent years, "ionic liquids" emerges as alternative solvents because of their remarkable
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properties. Ionic liquids (IL’s) are a new group of solvents consisting of certain anions and cations (Fredlake et al., 2004; Ghandi, 2014; Mikami, 2005). Due to their non-flammable,
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non-volatile and recyclable properties, they are classified as green solvents. At the present time, the term of ionic liquid is used for salts which melt under 100 °C. When the melting
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point is under room temperature, IL is named as room temperature ionic liquid (RTIL) (Berthod et al., 2008). The improved solvent properties of these salts and their very low
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vapor pressure have made it inevitable for them to be used as solvents in many reactions (Marsh et al., 2002).
Table 1 demonstrates the literature research related to the propionic acid separation by reactive extraction. As shown in Table 1, the conventional organic solvents like hexane, toluene, kerosene, MIBK, ethyl acetate, octanol and oleyl alcohol have been used in the separation of propionic acid by reactive extraction. However, these solvents have volatile, flammable and toxic properties, so they bring about environmental pollution. That’s why, ionic liquids are being investigated as an alternative new solvent group in replacement of conventional solvents (Djas and Henczka, 2018; Sprakel and Schuur, 2018). Nevertheless, there are a limited number of extraction studies on the use of ionic liquids for the removal of carboxylic acids in the literature. Extraction and reactive extraction studies of carboxylic acids with ionic liquids reported in the literature are presented in Table 2. In this study, the use of imidazolium-based ionic liquids were examined in the reactive extraction of propionic acid.
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Table 1. Reactive extraction studies related to the separation of propionic acid reported in the literature. Reactant
Diluents (solvents)
References
Cyclohexane, hexane, toluene, MIBK and ethyl acetate
(Uslu and İnci, 2007)
TBP, TOA and Aliquat 336
1-octanol
(Keshav et al., 2008d)
TBP
Kerosene and 1-decanol
(Kumar et al., 2011)
Primary amine (N1923)
Hexane, n-octanol and butyl acetate
(Wang et al., 2009)
TOA
Heptane, petroleum ether, ethyl acetate and oleyl alcohol
(Keshav et al., 2008e)
Aliquat 336
MIBK
(Keshav et al., 2009)
TOPO
Hexane
Aliquat 336
2-octanol
Amberlite LA-2
Cyclohexane, 2-octanone, toluene, methyl isobutyl ketone, isooctane, hexane and 1-octanol
(Aşçı and İnci, 2009)
Aliquat 336
Oleyl alcohol
(Keshav et al., 2008c)
Alamine 336
Toluene
TRPO
Kerosene
TBP and TOA
Hexane
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TBP: Tributylphosphate TRPO: Trialkylphosphine oxide
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MIBK: Methyl isobutyl ketone TOPO: Tri‐n‐octylphosphine oxide
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Aliquat 336
(Keshav et al., 2008b) (Keshav et al., 2010)
(Uslu, 2006) (Wang et al., 2001) (Matsumoto et al., 2001) TOA: Trioctylamine
Table 2. Extraction and reactive extraction with ionic liquids related to the separation of carboxylic acid reported in the literature. Acid
Ionic liquids
References
Lactic acid
Tetraalkylphosphonium ionic liquid
(Marták and Schlosser, 2007)
Lactic acid
Tetrabutylphosphonium chloride, Tributyltetradecylphosphonium chloride Trihexyltetradecylphosphonium chloride
(Tonova et al., 2015)
Butyric acid
Trialkylmethylammonium bis-(2,4,4trimethylpentyl)phosphinate
(Blahušiak et al., 2011, 2013)
Butyric acid
Trihexyl-(tetradecyl)phosphonium bis 2,4,4trimethylpentylphosphinate
(Marták and Schlosser, 2008)
L-lactic acid, L-malic acid, succinic acid
Phosphonium-based ionic liquids
(Oliveira et al., 2012)
Glycolic Acid
1-Butyl-3-methylimidazolium hexafluorophosphate
(Aşçı, 2017) (AŞÇI)
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Statistical analysis is one of the first and most important steps in experimental design. In addition to experimental studies, it is important to optimize the examined systems and also to reveal the parameters affecting the system behavior. Experimental design methods are used to understand the structure of systems in different working areas, to determine effective parameters and to perform performance improvement. The aim of the statistical experiment design technique is to reach maximum information with minimum data. Response surface methods are one of the experimental design methods based on statistical basis (Açıkalın and Bolat, 2011).
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Response Surface Methodology (RSM) is a combination of mathematical and statistical methods that develop and optimize industrial formations in different forms. The important points in the scientific studies are determining the effective internal and environmental
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factors on the process, revealing their interactions, modelling of the processes in terms of effective factors, understanding, explaining and planning the process. Optimization studies
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for these purposes are an important step. Mathematical model, which is a function of the optimization process and the variables obtained from the results, in making predictions
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before the trial about the process will shed light plays a key role in the transition to industrial systems. Considering these reasons, the necessity of optimization of a study has great importance. Some of the most practice of these methods are as follows; Central composite
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design, factorial design, Box-Behnken design, 3-level design, hybrid design, pentagonal design, D-optimal design etc.(Baylan and Çehreli, 2018, 2019; Granato and de Araújo Calado, 2014; Turan, 2018).
In this work, the reactive extraction of propionic acid from its aqueous solutions by using ionic liquids was investigated. Firstly, different factors like initial acid concentration, initial TBP concentration in ionic liquids, and water/organic phase ratio affecting on the reactive extraction process were examined experimentally. Then, central composite design (CCD) was also applied to investigate the effect of these factors on the extraction efficiency. The mathematical model equation was derived for extraction efficiency. The experimental data were evaluated by analysis of variance (ANOVA). Finally, optimal reactive extraction conditions were determined by using CCD.
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2. Material and Methods 2.1. Material Propionic acid (PA) is a transparent, uncolored and soluble in water and was supplied by Merck (>99%). Distilled water was utilized to prepare the aqueous solutions of propionic acid in different concentrations. The initial concentrations of propionic acid were varied from 5 to 10 % (w/w). The values of acid concentration in this study were chosen because of the typical acid concentration in fermentation broths. Usually, the fermentation broths include low concentrations of carboxylic acids (less than 10%, w/w). Tributyl phosphate (TBP), was utilized as a reactant, purchased from Sigma-Aldrich (>99%). 1-Hexyl-3-
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methylimidazolium hexafluorophosphate [HMIM][PF6] and 1-Hexyl-3- methylimidazolium bis(trifluoromethylsulfonyl)imide [HMIM][Tf2N] were utilized as diluents, purchased from Iolitec (>99%). The initial concentrations of TBP were varied in the range of 0-3 mol.L-1 in ionic liquids.
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2.2. Methods
The volumes of aqueous solutions (propionic acid+water) and organic solutions (TBP+ionic
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liquid) were 2 mL. The extraction experiments were executed by shaking in a water bath (Nüve ST 30) at room temperature and 150 rpm for predetermined optimum time (1 h).
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Samples were centrifuged at 3000 rpm for 10 min to separate the aqueous and organic phases. The acid concentrations in the aqueous solutions were detected by the Schott
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Titroline automatic titrator by using 0.1 N sodium hydroxide. The acid concentrations in the organic phase were specified from the material balance. A few experiments were repeated and the data were obtained to be within ±2% of accuracy. The experimental data were appreciated by using the extraction efficiency (E), distribution coefficient (d) and loading factor (Z). These parameters were calculated by means of the following equations (İnci, 2007):
The extraction efficiency (E) is characterized as the proportion of the concentration of extracted acid to concentration of initial acid. It is remarked as following equation: (1) The distribution coefficient (d) is explained as the acid extracted from water into organic phase. It is written as:
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(2) The loading of factor (Z), is expressed as the concentration of acid in the organic phase divided by the concentration of reactant in the organic phase
. It can be
signified as:
Z=
(3)
In these equations, CA,0 is the initial acid concentration in the aqueous phase (mol.L-1), CA is
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the acid concentration in the aqueous phase at the end of the extraction (mol.L-1), CA,org is the acid concentration in the organic phase at the end of the extraction (mol.L-1) and CR,org is the reactant concentration in the organic phase (mol.L-1). 2.3. Experimental Design
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CCD (face-centered) was employed to optimize the reactive extraction process, reveal a correlation between independent variables (factors) and dependent variable (response) and
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obtain the model equation representing the extraction system. CCD was designed on considering the different parameters on affecting reactive extraction explained in Section
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3.2. For these purposes, the software Design-Expert® 11.0 Trial Version, (Stat-Ease, Inc., Minneapolis, USA) was used. The initial propionic acid concentration (X1), initial TBP
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concentration in ionic liquid (X2), and phase ratio (aqueous phase volume:organic phase volume, X3) were chosen as the independent variables, and extraction efficiency (Y) was selected as the dependent variable in this design study. The aqueous phase volume:organic phase volume (phase ratio) was studied as 2 mL:4 mL (phase ratio:0.5), 2 mL:2 mL (phase ratio:1) and 3 mL:2 mL (phase ratio:1.5). The independent variables were presented in Table 3 together with their symbols and levels. Table 3. Independent variables and their levels in CCD. Levels Independent variables
Symbols -1
0
1
Initial acid concentration (%)
X1
5
7.5
10
Initial TBP concentration (mol/L)
X2
0
1.5
3
Phase ratio
X3
0.5
1
1.5
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The relation between the chosen independent variables and the dependent variable is written as: Y=f (X1, X2,…..,,Xn)+ ℇ
(4)
For CCD, the model equation is transformed into a second-order polynomial, and the response value is calculated depending on the factors in the second-order model. The model equation representing response can be written in the form (Cho and Zoh, 2007):
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(5)
In these equations, Y is dependent variable or response, X1, X2,..,Xn are the factors or independent variables, f is the function of dependent variable, ε is an error, β0 is the constant
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coefficient, βi, βii, βij are the coefficient of each variable and k is the number of variable. 3. Results and Discussion
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3.1. Determination of the optimum extraction time
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Various experiments were performed to determine the optimum extraction time. For the optimum time determination experiments, 10% by weight of propionic acid and an ionic liquid [HMIM][PF6] was utilized. In addition, in order to examine the effect of addition of
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TBP on the extraction time, TBP concentration in ionic liquid was adjusted to 3 mol/L and the experiments were performed. The results of these experiments were shown in Figure 2. According to the experimental results indicated in Figure 2, the optimum extraction time was determined as an hour.
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Figure 2. The effect of time on propionic acid reactive extraction. 3.2. Effect of different parameters on reactive extraction
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The effect of different factors like initial propionic acid concentration, initial TBP concentration in ionic liquid and phase ratio (aqueous phase volume/organic phase volume)
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on the reactive extraction were investigated. In the literature survey, the most-examined factors in the reactive extraction such as reactant concentration, acid concentration were
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reported (Asçı and İncı̇ , 2009; Datta and Kumar, 2011). Firstly, various experiments were performed to specify the effect of the initial concentration of propionic acid. In these experiments, initial propionic acid concentrations of 5%, 7.5% and 10% (w/w) were used. The
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initial TBP concentrations were varied 0 to 3 mol/L in [HMIM][PF6], and phase ratio is 1. Using the experimental data, the distribution coefficient (d), loading factor (Z) and extraction efficiency (% E) were calculated using Equations 1-3. Figure 3 depicts the distribution coefficient (d), loading ratio (Z) and extraction efficiency (E) values for the different initial acid concentration.
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Figure 3. The effect of initial propionic acid concentration on the distribution coefficient (d), loading factor (Z) and extraction efficiency (E) □ 5% ♦7.5% ▲10%. (phase ratio:1).
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Figure 4. The effect of phase ratio on the distribution coefficient (d), loading factor (Z) and extraction efficiency (E) ♦Phase ratio:0.5 □ Phase ratio:1 ▲Phase ratio:1.5 (Initial propionic acid concentration:10% w/w).
From Figure 3, it was analyzed that the initial acid concentration had no significant effect on both distribution coefficient (d) and extraction efficiency (E) over the investigated acid concentration range. In the literature, İnci and Uslu (İnci and Uslu, 2005) examined the reactive extraction of citric acid using trioctyl methyl ammonium chloride and they reported that the distribution coefficient increased from 0.16 to 0.23 and the extraction efficiency increased from 14.29% to 19.05% with increasing initial acid concentration from 0.105 mol.L-1 to 0.210 mol.L-1, and also, the distribution coefficient increased slightly from 0.23 to 0.26 and the extraction efficiency increased from 19.05% to 20.63% with increasing initial acid concentration from 0.210 mol.L-1 to 0.315 mol.L-1. Kumar et al. (Kumar et al., 2006)
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examined the recovery of propionic acid using reactive extraction and they observed that the distribution coefficient decreased slightly from 2.30 to 2.14 with increasing initial propionic acid concentration from 0.675 to 1.35 g mol.L-1. In the reactive extraction process, the concentration of the extractant is key factor. So, TBP concentration in the organic phase is more effective parameter than the initial acid concentration. Figure 3 also showed that the extraction efficiencies and distribution coefficients were increased significantly with increasing TBP concentration in [HMIM][PF6]. These results were further confirmed by observations from similar reactive extraction studies (Keshav et al., 2008a; Uslu and İnci, 2007). Furthermore, Figure 3 indicated that, the values of loading factor varied from 0.19 to
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0.69 with increasing the TBP concentration in [HMIM][PF6] and initial propionic acid concentration, meaning that complexes contain more than one phosphate per complex. Overloading, loading factor greater than unity, represents that the complexes with more than one acid molecule per phosphate are created (Aşçı and İncı̇ , 2010).
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To examine the effect of phase ratio on the reactive extraction, the experiments were carried out by using the concentration of propionic acid of 10% w/w, TBP concentration in
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[HMIM][PF6] of 0-3 mol/L and phase ratio of 0.5-1.5. The values of distribution coefficient (d), loading ratio (Z) and extraction efficiency (E) at different phase ratios were illustrated in
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Figure 4. As shown in Figure 4, as the phase ratio increased, the values of extraction efficiency, distribution coefficient and loading factor decreased. Chawong, and Rattanaphanee
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(Chawong and Rattanaphanee, 2011) studied n-butanol as an extractant for lactic acid recovery and they found that the extraction efficiency decreased from 96.97 to 51.01 with increasing phase ratio from 0.25 to 1. Kahya et al. (Kahya et al., 2001) investigated the reactive extraction of lactic acid by using Alamine 336 diluted with oleyl alcohol. The distribution coefficient decreased with increasing aqueous volume (Vaq)/organic volume (Vorg) ratio.
3.3. Central Composite Design Study In CCD study, the variables and levels given in Table 3 were entered into the Design Expert® program and 20 different reactive extraction systems as shown in Table 4 were obtained. These systems were studied experimentally for two ionic liquids ([HMIM][PF6] and [HMIM][Tf2N]) to determine the effect of ionic liquid type. The obtained experimental results were analyzed statistically using ANOVA. ANOVA results obtained for extraction efficiency (Y) for [HMIM][PF6] and [HMIM][Tf2N] were presented in
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Table 5, respectively. In ANOVA results, F-value or Prob>F and p-value of the model give information about whether the model is important or not (Chen et al., 2011). When the Fvalue (98.72) and p-value (<0.0001) in Table 5 model were examined, it was seen that the model is important for the response. Table 4. CCD layout and experimental results. TBP concentration X2
Phase ratio X3
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
5 5 5 5 5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 10 10 10 10 10
0 0 1.5 3 3 0 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 3 0 0 1.5 3 3
0.5 1.5 1 0.5 1.5 1 0.5 1 1 1 1 1 1 1.5 1 0.5 1.5 1 0.5 1.5
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Extraction efficiency (%) Y [HMIM][PF6] 37.87 19.51 65.29 87.56 68.33 25.81 77.38 63.54 62.81 63.79 63.30 63.32 64.28 45.38 79.62 41.95 20.12 60.74 87.30 64.66
[HMIM][Tf2N] 47.42 25.88 45.83 88.16 72.29 31.45 78.66 44.11 42.98 43.27 44.75 44.41 45.14 52.62 74.40 50.20 27.03 48.47 87.00 62.55
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Initial acid concentration X1
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Experiment number
The significance of model terms is analyzed by means of p-value. The p-value lower than 0.05 of the model terms indicates that the model terms are meaningful and have a substantial effect on the response (Baylan and Çehreli, 2018). According to p-values in Table 5, TBP concentration (X2), phase ratio (X3) and the square of the interaction of TBP concentration (X22) were substantial model terms and had a significant effect on the extraction efficiency for the reactive extraction of propionic acid with [HMIM][PF6]. Similarly, according to p-values in Table 5, TBP concentration (X2), phase ratio (X3) and the square of the interaction of phase ratio (X32) were significant model terms for the reactive extraction of propionic acid with [HMIM][Tf2N]. In other words, the model equation representing the extraction efficiency consists of these model terms. X2, X3 model terms had a linear effect on the experimental
Page 15 of 27
results of two ionic liquids. X22 of model term had an exponential effect on the experimental results of [HMIM][PF6], and X32 of model terms had an exponential effect on the experimental results of [HMIM][Tf2N]. This situation can be clarified by the difference of ionic liquid type.
Table 5. ANOVA data for extraction efficiency (Y) in the reactive extraction of propionic acid with [HMIM][PF6] and [HMIM][Tf2N]. [HMIM][PF6] Sum of
Source
squares
df
[HMIM][Tf2N]
Mean
F
p-Value
square
value
Prob>F
9
849.89
98.72
X1
1.44
1
1.44
0.1669
X2
5866.57
1
5866.57
681.45
X3
1300.97
1
1300.97
151.12
X 1X 2
9.29
1
9.29
1.08
X 1X 3
5.92
1
5.92
X 2X 3
0.3528
1
1.59
<
squares
df
Mean
F
p-Value
square
value
Prob>F
<
6230.96
9
692.23
34.02
1.87
1
1.87
0.0921
4097.39
1
4097.39
201.33
1233.65
1
1233.65
60.62
0.3234
27.49
1
27.49
1.35
0.2721
0.6873
0.4264
13.03
1
13.03
0.6403
0.4422
0.3528
0.0410
0.8436
2.41
1
2.41
0.1184
0.7376
1
1.59
0.1843
0.6768
48.67
1
48.67
2.39
0.1530
250.31
1
250.31
29.07
0.0003
6.76
1
6.76
0.3323
0.5771
2.11
1
2.11
0.2448
0.6314
561.03
1
561.03
27.57
0.0004
86.09
10
8.61
203.52
10
20.35
Lack of fit
83.67
5
16.73
199.97
5
39.99
56.44
0.0002
Pure error
2.45
5
0.4898
3.54
5
0.7086
Total
7735.08
19
6434.48
19
X 32 Residual
R2
0.6915 <
0.0001 <
0.0001
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X2
2
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X1
2
0.0001
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7648.99
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Model
Sum of
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Ionic liquid
34.15
0.0007
0.9889
0.9684
R2Adj
0.9789
0.9399
R2Pred
0.9175
0.8400
AP
34.7092
20.0169
CV%
5.05
8.54
SD
2.93
4.51
0.0001 0.7677 < 0.0001 < 0.0001
*SD: Standard deviation, AP: Adequate precision CV: Coefficient of variation
Page 16 of 27
To obtain the model equation, R2 values of the candidate models such as linear, quadratic, cubic model were checked and the model with the highest R2 value was employed. As a result, second-order model equations representing the extraction efficiency (Y) for the reactive extraction of propionic acid with ionic liquids were acquired as Eqs 6 and 7: [HMIM][PF6]
Y= 62.91 + 24.22 X2 – 11.41 X3 – 9.54 X22
(6)
[HMIM][Tf2N]
Y= 47.01 + 20.24 X2 – 11.11 X3 + 14.28 X32
(7)
When the model equations were examined, it was clear that the parameters affecting the
ro of
extraction efficiency were TBP concentration (X2) and phase ratio (X3). With the increase in the initial TBP concentration, the extraction efficiency increased. However, the extraction efficiency decreased with the increase in the phase ratio. Since it had the highest coefficient in the model equations, it can be said that TBP concentration (X2) was the most effective
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parameter on extraction efficiency. In addition to, it can be clearly seen that the initial propionic acid concentration (X1) was not an influential variable on the extraction efficiency
re
in both model equations.
Table 5 also presents the statistical parameters utilized to control the adequacy and accuracy
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of the model equations. The correlation coefficient, R2, is defined as a measure of the degree of compliance. When the R2 approaches to unity, the difference between the predicted and
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experimental data is very small, and so the predicted model is better suited to the experimental data (Chen et al., 2011). In this design study, as can be seen in Table 5, the values of R2 were found to be quite high. It demonstrated that the model equations were wellsuited to the experimental data. Adjusted R2 (R2Adj) is defined as a measure of the amount of change around the mean (Chen et al., 2011). The fact that the R2 and R2Adj values are close to each other indicates that the model sufficiently represents experimental results. The difference between the predicted R2 (R2Pred) and R2Adj is less than 0.2 indicating that these values are in reasonable agreement with each other. Furthermore, adequate precision (AP) is a measure of the signal to noise ratio and is desired to be greater than 4. Coefficient of variation (CV) signifies a measure of the proportion of the standard deviation to the mean and is supposed to be quite low (Baylan and Çehreli, 2019). AP values were obtained as 34.7092 for [HMIM][PF6] and 20.0169 for [HMIM][Tf2N]. CV values were acquired as 5.05% for [HMIM][PF6] and 8.54% for [HMIM][Tf2N], respectively. These results indicated that the obtained model equations were consistent with experimental data.
Page 17 of 27
Other control points for the verification of the experimental results are the analysis of diagnostic plots (predicted vs. actual plot or residuals vs. predicted plot). The predicted vs. actual plot indicates that the points must be aligned with a straight line. The residuals vs. predicted plot shows whether the residuals are in normal distribution (Asghar et al., 2014; Rajmohan and Palanikumar, 2013). These plots were checked for the adequacy and accuracy of model equations for each ionic liquid. Diagnostic plots were illustrated in Figure 5. As illustrated in Figure 5.a, all points were within the range and showed normal distribution. As shown in Figure 5.b, the experimental values were aligned as a straight line. These results
ro of
demonstrated that the predicted values by the model were in agreement with the experimental
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data.
[HMIM][PF6] (a)
[HMIM][PF6] (b)
Page 18 of 27
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[HMIM][Tf2N] (a)
[HMIM][Tf2N] (b)
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Figure 5. Diagnostic plots of CCD model for [HMIM][PF6] and [HMIM][Tf2N]. (a) predicted vs actual plot (b) residuals vs. predicted plot.
[HMIM][PF6]
[HMIM][Tf2N] (a)
Page 19 of 27
[HMIM][Tf2N]
[HMIM][PF6]
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(b)
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[HMIM][PF6]
[HMIM][Tf2N]
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(c) Figure 6. Response surface graphs for the extraction efficiency in the reactive extraction of propionic acid with [HMIM][PF6]. (a) the effect of initial acid concentration (X1) and TBP concentration (X2) in case of phase ratio of 1. (b) the effect of TBP concentration (X2) and phase ratio (X3) in case of initial acid concentration of 7.5%. (c) the effect of initial acid concentration (X1) and phase ratio (X3) in case of TBP concentration of 1.5 mol/L.
Response surface graphs of the model equations were plotted to explain the effect of independent variables on the extraction efficiency. The response surface graphs were plotted for two selected variables while one variable was held at intermediate level. The response surface graphs of model equations were shown in Figure 6. From Figure 6, the extraction efficiency increased with increasing TBP concentration in ionic liquids, nevertheless it decreased with increase in phase ratio. As the initial propionic acid concentration was increased, the extraction efficiency did not change. When TBP concentration and phase ratio effects on the extraction efficiency were compared (Figures 6.b), it can be said that TBP concentration was more influential variable than the phase ratio.
Page 20 of 27
The final stage of the design is the determination of the criteria for optimization. Optimization criterion was the maximum extraction efficiency and all independent variables was kept within in range. These conditions was executed at Design-Expert® Software and the optimal points for the reactive extraction of propionic acid were determined as given in Table 6. Besides, under optimal points, the experiments were conducted and the experimental extraction efficiency values were also added in Table 6. As can be observed in Table 6, the predicted model values were compatible with the experimental data. Table 6. The optimal reactive extraction points for each ionic liquid. Initial acid concentration (% w/w)
TBP concentration (mol/L)
Phase ratio
Extraction efficiency (%) Predicted
Extraction efficiency (%) Experimental
Desirability
[HMIM][PF6]
5.000
3.000
0.500
89.683
87.560
1.000
[HMIM][Tf2N]
5.000
3.000
0.500
90.464
88.160
1.000
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3.4. Comparison of selectivity of ionic liquids
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Ionic liquid type
Considering the effect of parameters on propionic acid extraction as mentioned before, TBP
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concentration was the most influential parameter, whereas the initial propionic acid concentration was not efficient parameter. Additionally, taking the effect of phase ratio and the optimal extraction conditions in consideration, a comparison was made illustrated in
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Figure 7.
As can be observed in Figure 7, in the event of purely ionic liquids in the organic phase (5-00.5 and 5-0-1.5 experiment systems), the values of extraction efficiency acquired for both ionic liquids were very close to each other, but relatively [HMIM][Tf2N] can be said to be more selective. In the event of using TBP in ionic liquids (5-3-0.5 and 5-3-1.5 experiment systems), the values of extraction efficiency were almost same, the effect of the ionic liquid type did not obviously observed for the reactive extraction of propionic acid. This result implied that TBP effect was more dominant than the type of ionic liquid. This work also showed that these imidazolium-based ionic liquids can be utilized as extraction solvents in the removal of propionic acid.
Page 21 of 27
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Figure 7. The selectivity of ionic liquids in different systems.
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4. Conclusion
In this research, imidazolium-based ionic liquids namely [HMIM][PF6] and [HMIM][Tf2N]
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were tested in the reactive extraction of propionic acid by using TBP. CCD was employed to investigate the effect of different factors like initial acid concentration, TBP concentration in ionic liquids, and aqueous/organic phase ratio on the extraction efficiency. The experimental
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data were appreciated statistically by ANOVA. Model equations were derived for the extraction efficiency. The adequacy and accuracy of model equations was confirmed by means of graphical analysis and statistical parameters. This design study was concluded that the obtained model equations were in good agreement with the experimental data. The factors affecting the extraction efficiency were detected as TBP concentration and phase ratio. The extraction efficiency increased with increasing TBP concentration, and also it decreased with the increase in the phase ratio. Initial TBP concentration in ionic liquids had the most crucial parameter on the extraction efficiency. However, the initial propionic acid concentration was not an influential factor on the extraction efficiency. Finally, the optimal extraction conditions for both ionic liquids were detected. The optimum conditions were obtained as initial propionic acid concentration of 5% (w/w), TBP concentration in ionic liquids of 3 mol.L-1, phase ratio of 0.5. The extraction efficiency values for both ionic liquids were acquired very close to each other. This investigation has also indicated that ionic liquids [HMIM][PF6] and
Page 22 of 27
[HMIM][Tf2N] as green extraction solvents can be successfully employed in the reactive extraction of propionic acid. References Açıkalın, K., Bolat, E., 2011. Modelling of pyrolysis yields of pistachio shells by using various experimental design methods. Sigma 29, 52-64. Asghar, A., Raman, A., Aziz, A., Daud, W.M.A.W., 2014. A comparison of central composite design and Taguchi method for optimizing Fenton process. The Scientific World Journal 2014, 1-14. Aşçı, Y.S., 2017. Examination of the efficiency of ionic liquids in glycolic acid separation from
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aqueous solution by using reactive extraction method. Journal of the Turkish Chemical Society, Section A: Chemistry 4, 981-992.
Aşçı, Y.S., İncı̇ , İ, 2009. Extraction of glycolic acid from aqueous solutions by Amberlite LA2 in different diluent solvents. Journal of Chemical & Engineering Data 54, 2791-2794. Aşçı, Y.S., İnci, İ., 2009. Extraction equilibria of propionic acid from aqueous solutions by Amberlite
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LA-2 in diluent solvents. Chemical Engineering Journal 155, 784-788.
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Aşçı, Y.S., İncı̇ , İ., 2010. Extraction equilibria of acrylic acid from aqueous solutions by amberlite LA-2 in various diluents. Journal of Chemical & Engineering Data 55, 2385-2389.
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Baylan, N., Çehreli, S., 2018. Ionic liquids as bulk liquid membranes on levulinic acid removal: A design study. Journal of Molecular Liquids 266, 299-308. Baylan, N., Çehreli, S., 2019. Removal of acetic acid from aqueous solutions using bulk ionic liquid
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Blahušiak, M., Schlosser, Š., Marták, J., 2011. Extraction of butyric acid by a solvent impregnated resin containing ionic liquid. Reactive and Functional Polymers 71, 736-744. Blahušiak, M., Schlosser, Š., Marták, J., 2013. Extraction of butyric acid with a solvent containing ammonium ionic liquid. Separation and Purification Technology 119, 102-111. Chawong, K., Rattanaphanee, P., 2011. n-Butanol as an extractant for lactic acid recovery. World Academy of Science, Engineering and Technology 80, 239-242. Chen, C.-C., Chiang, K.-T., Chou, C.-C., Liao, Y.-C., 2011. The use of D-optimal design for modeling and analyzing the vibration and surface roughness in the precision turning with a diamond cutting tool. The International Journal of Advanced Manufacturing Technology 54, 465-478.
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Cho, I.-H., Zoh, K.-D., 2007. Photocatalytic degradation of azo dye (Reactive Red 120) in TiO2/UV system: Optimization and modeling using a response surface methodology (RSM) based on the central composite design. Dyes and Pigments 75, 533-543. Datta, D., Kumar, S., 2011. Reactive extraction of glycolic acid using tri-n-butyl phosphate and tri-noctylamine in six different diluents: Experimental data and theoretical predictions. Industrial & Engineering Chemistry Research 50, 3041-3048. Djas, M., Henczka, M., 2018. Reactive extraction of carboxylic acids using organic solvents and supercritical fluids: A review. Separation and Purification Technology 201, 106-119. Fredlake, C.P., Crosthwaite, J.M., Hert, D.G., Aki, S.N., Brennecke, J.F., 2004. Thermophysical
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properties of imidazolium-based ionic liquids. Journal of Chemical & Engineering Data 49, 954-964. Ghandi, K., 2014. A review of ionic liquids, their limits and applications. Green and sustainable chemistry 4, 44-53.
Gonzalez-Garcia, R., McCubbin, T., Navone, L., Stowers, C., Nielsen, L., Marcellin, E., 2017.
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Microbial propionic acid production. Fermentation 3, 1-20.
Granato, D., de Araújo Calado, V.M., 2014. The use and importance of design of experiments (DOE)
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in process modelling in food science and technology. Mathematical And Statistical Methods In Food
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Science And Technology 1, 1-18.
Holten, C.H., 1971. Lactic acid. Properties and chemistry of lactic acid and derivatives. Weinheim/Bergstr., W. Germany, Verlag Chemie GmbH.
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