Thermodynamic study of aqueous two phase systems for some aliphatic alcohols + sodium thiosulfate + water

Fluid Phase Equilibria 321 (2012) 64–72

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Thermodynamic study of aqueous two phase systems for some aliphatic alcohols + sodium thiosulfate + water Ebrahim Nemati-Knade a , Hemayat Shekaari b,∗ , Safar A. Jafari b a b

Department of Chemistry, Faculty of Science, Parsabad Mogan Branch, Islamic Azad University, Parsabad, Iran Department of Physical Chemistry, Faculty of Science, University of Tabriz, Tabriz 51664, Iran

a r t i c l e

i n f o

Article history: Received 11 January 2012 Received in revised form 18 February 2012 Accepted 21 February 2012 Available online 3 March 2012 Keywords: Liquid–liquid equilibria Alcohol Sodium thiosulfate Cloud point ATPS, Wilson equation

a b s t r a c t The aqueous two phase systems for 1-propanol, 2-propanol, 2-methyl-2-propanol, 2-butanol or ethanol + sodium thiosulfate + water ternary systems at T = 298.15 K were studied thermodynamically, and an empirical three parameter equation was successfully used for the correlation of binodal data. The phase-separation ability of the studied systems was discussed on the basis of the solubility and boiling point of the constitutive alcohol. Furthermore, the effect of temperature on the phase-separation ability of the studied systems was discussed in terms of the experimental cloud-point data as a function of alcohol mole fraction at the temperature ranges of T = (293.15–323.15) K at 5 K intervals. Additionally, the segment based Wilson equation was generalized to represent the mixed organic–aqueous solvent electrolyte systems and successfully used for the correlation of binary and ternary data, and the restricted binary interaction parameters were also reported. The result of the correlation using generalized Wilson model was also compared with the e-NRTL model. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Study of the salt effect on the mixed aqueous–organic solvents is an attractive field in industry and academia due to its applications in the separation and purification processes [1–3]. Therefore, many research groups have focused on the theoretical and experimental study of the phase equilibrium conditions in ternary aqueous–alcohol–salt immiscible systems which are known as aqueous two phase systems (ATPSs). On the one hand, the experimental liquid–liquid equilibrium (LLE) data were reported and the special effective parameters on the LLE were studied by some researchers, and on the other hand, efforts are focused on the modeling and representation of the LLE data using reliable thermodynamic models. Chou et al. [4] and Zafarani-Moattar et al. [5] reported the effect of different salt and alcohols on the phase forming ability of the relevant ATPSs. The effect of temperature on the ATPSs composed of some aliphatic alcohols + water + potassium carbonate was discussed by Salabat et al. [6], and Shekaari et al. [7] studied the liquid–liquid equilibrium (LLE) of some aliphatic alcohols + dipotassium oxalate + water systems. Additionally, the local composition based models such as the NRTL and electrolyte-NRTL models and the group contribution based models such as UNIQUAC or UNIFAC models have been

∗ Corresponding author. Tel.: +98 411 3393139; fax: +98 411 3340191. E-mail address: [email protected] (H. Shekaari). 0378-3812/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.fluid.2012.02.015

extensively used for the correlation of the LLE data in such mixed solvent–electrolyte systems [8–13]. As van Bochove at al. [9] remarked, the correlation of the mixedsolvent systems becomes more complicated in the presence of the salts and the ionic species introduce a large deviation from ideality which have a large influence on the LLE. Also, in such systems the difference in the dielectric constants and the densities of the solvents will be large and a physically correct description will require the use of a solvent composition-dependent dielectric constant and density. Therefore, for a successful description of the LLE data the influence of electrolyte species and aqueous-organic mixed solvent should be considered. The authors of the presented paper have used the e-NRTL [14] model to represent the LLE of some alcohol + salt + water systems at previous works [13,15], in which the both mentioned problems was considered. This paper is a continuation of our studies on the ATPSs which is dealing with the LLE of 1-propanol, 2-propanol, 2-methyl-2propanol, 2-butanol or ethanol + sodium thiosulfate + water ternary systems. In this regard, the experimental binodal and tie-line data at T = 298.15 K are reported and the effect of temperature on the studied ATPSs is discussed on the basis of the cloud point data as a function of alcohol mole fractions at T = (293.15–323.15) K with 5 intervals. Moreover, the modified segment based Wilson equation of Sadeghi [16] is generalized for the thermodynamic representation of mixed solvent electrolyte systems. The presented model is also used for the correlation of the studied ATPSs, and the result of the correlation is compared with the e-NRTL model [14].

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Table 2 Values of parameters of Eq. (1), used to obtain alcohol mass fractions, for the studied alcohol (m) + sodium thiosulfate (ca) + water (w) ATPSs at T = 298.15 K and atmospheric pressure.

2. Experimental 2.1. Materials Physicochemical properties of the chemicals used in this work are described in Table 1. All the chemicals were used without further purification. 2.2. Apparatus and procedure The experimental apparatus employed in this work is essentially similar to the one used at previous works [7,15]. A double-wall glass vessel was used to carry out the binodal curve measurements on a magnetic stirrer plate. The cell temperature was controlled at a constant temperature with circulation of water using a thermostat (JULABO model ED, Germany) with an accuracy of ±0.03 K. The binodal curves were determined by the cloud-point titration method. A known concentration of aqueous sodium thiosulfate solution was titrated with alcohol until the solution was turned turbid, which indicated the formation of two-liquid phases, subsequently the solution was back-titrated by adding water until the turbidity vanished. The composition of the mixture was measured by mass using an analytical balance (Sartorius model TE214S, Switzerland) with a precision of ±1.10−7 kg. For the determination of the tie-lines of the studied systems, feed samples (less than 10 cm3 ) were prepared by mixing appropriate amounts of alcohol, salt, and water in the glass cells. Once the samples were shaken vigorously (2400 cycles min−1 ) for 3 min using a shaker (Labtron model LS-100, Iran), the glass cells were placed in a water bath thermostatted at T = 298.15 K for (6–8) h. Once again, the samples were shaken thoroughly about an hour being immersed in the thermostatted bath. After the necessary rest time, the mixture was split into clear and transparent liquid phases with a well-defined interface, and equilibrium state was achieved. The samples were carefully withdrawn using long needle syringes. Then both phases were diluted with double distilled deionized water by a mass factor of about 1–10 for refractive index measurements. After the separation of the two-phases, the concentrations of sodium thiosulfate in the top (alcohol-rich) and bottom (waterrich) phases were determined by flame photometry (JENWAY model PFP7, U.K.). The concentration of alcohol in both phases was determined by refractive index measurements performed at T = 298.15 K using a refractometer (Atago, model DR-A1, Japan). The uncertainty in the measurement of the refractive index was found to be ±0.0002. The mass fraction of alcohol in both phases in the diluted region, which are at equilibrium, was calculated from the refractive index measurements using the following equation: nD = n0w + am wm + aca wca

(1)

System

n0w

am

103 sdm

aca

103 sdm

1-Propanol + ca + w 2-Propanol + ca + w 2-Methyl-2-propanol + ca + w 2-Butanol + ca + w Ethanol + ca + w

1.3325 1.3325 1.3325 1.3325 1.3325

0.0884 0.0851 0.1005 0.1106 0.0650

2.90 3.10 5.51 1.54 1.53

0.2048 0.2055 0.2006 0.2098 0.2021

1.28 1.37 3.75 6.78 3.74

sdj is the standard deviation between the calculated, cal, and experimental, exp, values of mass fraction, w, for component j (i.e. alcohol (m) or salt (ca)) and calculated using sdj =



i

exp

1/2

cal (wj,i − wj,i )/n

. Moreover, n is the number of measured

refractive indices data for the ternary standard solution.

where n0w is the refractive index of pure water, which is set to 1.3325 at 298.15 K. Also, wm and wca are the mass fractions of alcohol and sodium thiosulfate salt, respectively. Moreover, am and aca are the constants of alcohol and salt, respectively, and obtained from the simultaneous correlation of the experimental refractive indices of the ternary standard solution to Eq. (1). These constants along with the relative standard deviations (sd) are reported in Table 2. It should be noted that, our prepared ternary standard solutions for the calibration curves are in the mass fraction range of 0 ≤ wm ≤ 0.1 and 0 ≤ wca ≤ 0.05, and therefore, Eq. (1) is valid only for the mentioned mass fraction range. Therefore, before refractive index measurements, it was necessary to dilute the samples to be in the mentioned concentration range. The uncertainty of the mass fraction of alcohols achieved using Eq. (1) was better than ±0.003. For the study of the effect of temperature on the cloud-point, a known concentration of aqueous sodium thiosulfate solution was titrated with alcohol, until the solution turned turbid, and then temperature was decreased (or increased) at 5 K intervals until the turbidity vanished, and the addition of alcohol repeated until the solution turned turbid again. In this work, the relative mole fraction of two components (water and salt) remained constant, and the mole fraction of the third component (alcohol) was changed. 3. Results and discussion 3.1. Experimental binodal curve, tie-line and cloud-point data The experimental binodal curve data, tie-line compositions and cloud-point data for the studied ATPSs at T = 298.15 are listed in Tables 3–5 respectively. Additionally, the phase diagrams of the studied ATPSs are shown in Figs. 1–5.

Table 1 Physicochemical properties of the pure chemicals used in this work. Chemical 1-Propanol 2-Propanol 2-Methyl-2-propanol 2-Butanol Ethanol Na2 S2 O3 ·5H2 O H2 Og a b c d e f g

Cass No. 71-23-8 67-63-0 75-65-0 78-92-2 64-17-5 7772-98-7 7732-18-5

Source Rankem (India) Rankem (India) Lobachemie (India) Lobachemie (India) Merck (Germany) Lobachemie (India) Ghatreh (Iran)

Purity (in mass fraction %) >99.5 >99.7 >99 >99 >99.5 >99 >99.9

Taken from [25]. Taken from [26]. Taken from [27]. Taken from [28]. Taken from [19]. The molar mass of anhydrous sodium thiosulfate. The specific conductance of the double-distilled deionized water was about 0.70 ␮S cm−1 .

M (g mol−1 ) 60.096 60.096 74.123 74.123 46.069 158.11f 18.015

d (kg m−3 ) a

799.54 781.10a 784.30b 803.35c 785.10d – 997.04e

ε (C2 J−1 m−1 )e 20.18 19.85 12.47 15.90 25.08 – 78.30

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Table 3 Binodal curve data for the studied alcohols (m) + sodium thiosulfate (ca) + water (w) ternary systems as a function of alcohol mass fraction (wm ) and salt mass fraction (wca ) at T = 298.15 K and atmospheric pressure.a 100 wm

100 wca

100 wm

1-Propanol (m) + sodium thiosulfate (ca) + water (w) 12.70 18.22 8.25 11.48 19.11 10.02 10.87 20.30 10.98 10.22 21.73 12.31 23.07 13.76 9.31 15.34 8.58 24.74 17.53 7.78 26.35 2-Propanol (m) + sodium thiosulfate (ca) + water (w) 22.75 17.98 4.43 6.91 19.94 19.31 9.84 17.32 20.14 12.48 15.44 20.96 13.76 14.71 21.84 15.46 13.76 22.76 16.67 13.02 23.61 2-Methyl-2-propanol (m) + sodium thiosulfate (ca) + water (w) 5.67 10.51 16.37 15.30 6.43 10.08 14.24 7.15 9.35 12.79 8.22 8.69 11.37 9.52 8.25 2-Butanol (m) + sodium thiosulfate (ca) + water (w) 6.68 3.62 15.48 4.27 13.52 7.32 11.70 8.11 4.97 10.28 8.57 5.53 9.18 9.24 6.10 Ethanol (m) + sodium thiosulfate (ca) + water (w) 18.97 26.02 19.18 26.89 20.49 17.86 21.85 16.90 28.35 16.25 29.11 22.71 23.77 15.39 30.36 24.57 14.89 31.87 a

100 wca

100 wm

100 wca

100 wm

100 wca

7.59 7.16 6.84 6.41 6.07 5.69 5.35

27.55 28.42 30.67 32.05 33.44 34.43 35.59

5.10 4.95 4.50 4.24 3.96 3.82 3.64

38.02 38.57 40.22 43.63 45.36 49.04

3.19 3.10 2.81 2.40 2.19 1.71

12.26 11.60 11.17 10.80 10.39 9.98 9.62

24.74 26.03 27.44 29.13 30.30 31.60 32.32

9.11 8.50 7.96 7.29 6.82 6.34 6.04

33.86 34.84 35.92 36.81 37.97

5.50 5.16 4.83 4.56 4.18

10.55 11.19 12.17 13.23 13.93

7.80 7.29 6.73 6.36 5.95

14.46 15.60 17.12 17.90 19.50

5.40 5.16 4.86 4.46 4.18

21.30 22.36 23.53 25.04 26.84

8.15 7.14 6.03 5.45 4.67

9.24 9.58 9.84 10.71 11.53

4.67 4.30 4.03 3.22 2.48

12.21 13.01

1.87 1.39

13.87 13.26 12.32 11.80 11.01 10.06

32.86 33.82 35.42 37.08 38.84 39.83

9.45 9.03 8.05 7.19 6.43 5.99

40.85 42.05 43.68 44.48

5.42 4.90 4.18 3.91

Standard uncertainties for mass fraction and temperature were found to be better than ±0.002 and ±0.03 K, respectively.

Fig. 1. Experimental and calculated phase diagram for 1-propanol (m) + sodium thiosulfate (ca) + water (w) system at T = 298.15 K. (䊉) Experimental binodal data; ) calculated binodal curve from Eq. (2); (——) experimental tie-line data; ( ) calculated tie-lines data using generalized Wilson model; ( ) cal( culated tie-lines data using e-NRTL model; () initial total compositions.

Fig. 2. Experimental and calculated phase diagram for 2-propanol (m) + sodium thiosulfate (ca) + water (w) system at T = 298.15 K. (䊉) Experimental binodal data; ) calculated binodal curve from Eq. (2); (——) experimental tie-line data; ( ) calculated tie-lines data using generalized Wilson model; ( ) cal( culated tie-lines data using e-NRTL model; () initial total compositions.

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Table 4 Tie-line data for the studied alcohols (m)a + sodium thiosulfate (ca)b + water (w) ATPSs as a function of alcohol mass fraction (wm ) and salt mass fraction (wca ) at T = 298.15 Kc and atmospheric pressure. Total composition 100 wm

Top (alcohol-rich) phase 100 wca

1-Propanol (m) + sodium thiosulfate (ca) + water (w) 26.38 6.63 27.67 7.35 28.43 8.54 9.50 29.62 10.52 30.53 11.51 31.46 2-Propanol (m) + sodium thiosulfate (ca)+ water (w) 28.43 8.72 29.58 9.63 10.52 30.52 11.49 31.48 12.42 32.46 13.33 33.50 2-Methyl-2-propanol (m) + sodium thiosulfate (ca) + water (w) 6.32 30.74 7.23 32.03 32.89 8.21 34.16 8.88 35.08 9.62 36.21 10.72 2-Butanol (m) + sodium thiosulfate (ca) + water (w) 6.21 30.74 7.19 32.00 33.11 7.97 33.73 8.78 35.16 9.79 36.24 10.64 Ethanol (m) + sodium thiosulfate (ca) + water (w) 32.04 11.41 32.68 12.55 33.49 13.53 34.27 14.24 15.23 35.45 16.28 36.74 a b c

Bottom (water-rich) phase

100 wm

100 wca

100 wm

100 wca

54.93 59.99 64.49 67.59 69.44 71.23

1.19 0.88 0.69 0.55 0.45 0.39

15.02 11.70 8.01 6.69 5.91 5.00

8.84 10.61 13.03 14.85 16.91 19.02

41.14 48.03 52.52 57.45 62.06 64.36

3.47 2.20 1.50 1.05 0.66 0.57

14.81 17.62 19.79 21.94 23.42 26.07

13.87 9.51 7.73 5.68 4.94 2.70

61.09 64.43 67.21 68.92 70.41 72.46

0.43 0.36 0.27 0.23 0.18 0.17

10.35 8.48 6.39 5.35 4.34 2.67

10.13 12.18 14.42 16.04 17.75 20.33

78.23 79.15 79.94 80.36 81.09 81.30

0.04 0.05 0.05 0.04 0.04 0.04

6.93 5.52 4.38 4.07 3.14 2.43

9.29 10.99 13.05 14.28 16.54 18.62

39.57 44.91 49.13 52.27 56.39 59.65

6.19 4.15 3.21 2.54 1.92 1.64

12.08 8.43 6.02 4.64 3.36 2.54

25.46 28.98 31.72 33.74 36.04 38.21

Standard uncertainty of the mass fraction of alcohols using Eq. (1) was better than ±0.003. Standard uncertainty of the mass fraction of sodium thiosulfate was better than ±0.002. The uncertainty of temperature control was better than ±0.03 K.

3.2. Phase separation ability of the different alcohols Comparison between the binodal curves of studied systems at T = 298.15 K are plotted in Fig. 6. As can be seen from Fig. 6 the area of the two-phase region has the following order: 2-butanol > 2methyl-2-propanol > 1-propanol > 2-propanol > ethanol, and therefore, phase separation ability of the studied alcohols is in the same order. This observation can be interpreted in terms of the concept of the kosmotropicity of salts. As discussed by Zafarani-Moattar et al. [17], when the salt and the nonionic component such as alcohol are mixed together in an aqueous solution, the salt and the alcohol compete with each other for the water molecules.

The competition is won by the one that has a stronger intermolecular interaction with water (i.e. kosmotropic ions) and those of the alcohol lose, which has the weaker affinity to water, and as a result the alcohol–alcohol self-intermolecular interactions increased. Subsequently, at the specific threshold concentrations, the alcohol is “salted-out” and excluded from the rest of the solution as a separated phase. In the case of the studied ATPSs in this work, all systems have same salt (i.e. sodium thiosulfate), and it seems the intermolecular interaction between the alcohol–water and alcohol–alcohol self-interactions (including Van der Waals and hydrogen-bonding forces) should be considered, to understand the ability of different solvents in the formation of ATPSs.

Table 5 Cloud-point (CP) data for the studied alcohols (m) + sodium thiosulfate (ca) + water (w) systems at constant salt to water mole fraction rations (xca /xw )a and different alcohol mole fractions (xm )b at temperature range of T = (293.15–328.15) Kc in 5 K intervals at atmospheric pressure. xm

1-Propanol + sodium thiosulfate + water (xca /xw = 0.00892) 2-Propanol (m) + sodium thiosulfate (ca) + water (w) (xca /xw = 0.00896) 2-Methyl-2-propanol (m) + sodium thiosulfate (ca) + water (w) (xca /xw = 0.00891) 2-Butanol (m) + sodium thiosulfate (ca) + water (w) (xca /xw = 0.00890) Ethanol (m) + sodium thiosulfate (ca) + water (w) (xca /xw = 0.00894) a b c

T (K) 293.15

298.15

303.15

308.15

313.15

318.15

323.15

328.15

0.108 0.199 0.071 0.026 0.255

0.103 0.199 0.066 0.026 0.264

0.100 0.199 0.057 0.022 0.274

0.098 0.199 0.050 0.022 0.281

0.098 0.199 0.045 0.022 0.290

0.098 0.199 0.043 0.022 0.296

0.098 0.199 0.040 0.022 0.303

0.098 0.196 0.038 0.022 0.311

Standard uncertainty of the salt to water mole fraction rations (xca /xw ) was found to be better than ±0.00004. Standard uncertainty of alcohol mole fractions (xm ) was found to be better than ±0.001. The uncertainty of temperature control was better than ±0.03 K.

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Fig. 3. Experimental and calculated phase diagram for 2-methyl-2-propanol (m) + sodium thiosulfate (ca) + water (w) system at T = 298.15 K. (䊉) Experimental ) calculated binodal curve from Eq. (2); (——) experimental binodal data; ( tie-line data; ( ) calculated tie-lines data using generalized Wilson model; ) calculated tie-lines data using e-NRTL model; () initial total compositions. (

On the one hand, the solubility of an alcohol in water is a decisive factor to demonstrate the alcohol–water intermolecular interactions (i.e. the stronger alcohol–water intermolecular interaction results in the more solubility of alcohol). On the basis of the solubility data for the alcohols of the studied systems, we can classify these alcohols in two categories; (I): 2-butanol and 2-methyl-2propanol are slightly soluble alcohols with solubility of 29 [18] and 12 (reported by supplier) g/(100 ml of water) at T = 298.15 K, respectively, (II): ethanol, 1-propanol and 2-propanol are completely soluble in water, which can dissolve in water in any proportion [19]. Fig. 6 demonstrates that the order of the phase-separation ability of the studied ATPSs is in consistence with the solubility of the relevant alcohol. On the other hand, completely miscible alcohols (i.e. ethanol, 1-propanol or 2-propanol) can strongly compete with kosmotropic salt to achieve more water molecules, and more salt concentration needs to salt-out these alcohols as a separated phase. Whereas, the alcohols with the lower solubility

Fig. 4. Experimental and calculated phase diagram for 2-butanol (m) + sodium thio) sulfate (ca) + water (w) system at T = 298.15 K. (䊉) Experimental binodal data; ( calculated binodal curve from Eq. (2); (——) experimental tie-line data; ( ) calculated tie-lines data using generalized Wilson model; ( ) calculated tie-lines data using e-NRTL model; () initial total compositions.

Fig. 5. Experimental and calculated phase diagram for ethanol (m) + sodium thio) sulfate (ca) + water (w) system at T = 298.15 K. (䊉) Experimental binodal data; ( calculated binodal curve from Eq. (2); (——) experimental tie-line data; ( ) calculated tie-lines data using generalized Wilson model; ( ) calculated tie-lines data using e-NRTL model; () initial total compositions.

(i.e. 2-butanol or 2-methyl-2-propanol) at the lower concentration of salt lose competition against kosmotropic ions, and more readily salted-out. On the other point of view, boiling-point may be considered as an efficient criterion to represent the self-interaction forces between alcohol molecules, as pointed out by Wang et al. [20,21]. Therefore, the phase-separation ability of the studied ATPSs in each category (I or II) can be discussed on the basis of the boilingpoint of the alcohols. In the case of the class (I) ATPSs (with completely miscible alcohols) the boiling points are in order of 1-propanol (370.35) > 2-propanol (355.45 K) > ethanol (351.44 K). Also, in the case of the class (II) ATPSs (with completely miscible alcohols) the boiling points are in order of 2-butanol (372.66 K) >

Fig. 6. Comparison between the binodal data for the alcohols (m) + sodium thiosulfate (ca) + water (w) system as a function of mass fraction of alcohol and salt at T = 298.15 K. () Ethanol; () 2-propanol; (䊉) 1-propanol; (), 2-methyl-2propanol; (), 2-butanol. The two-phase region is the upper the binodal curve and the one phase region is the lower the same curves.

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Table 6 Values of the parameters of Eq. (2) used for the correlation of experimental binodal curves of the studied alcohol (m) + sodium thiosulfate (ca) + water (w) ATPSs at T = 298.15 K and atmospheric pressure. System

a

b

c

sda

1-Propanol + ca + w 2-Propanol + ca + w 2-Methyl-2-propanol + ca + w 2-Butanol + ca + w Ethanol + ca + w

−0.0471 0.0634 −0.1922 −0.3222 −0.037

−0.0687 −0.0558 −0.1186 −0.1395 −0.1501

0.0329 −0.2026 0.2925 0.3948 −0.1049

0.07 0.06 0.07 0.04 0.07

a

sd =



i

exp

 0.5

cal (100wm,i − 100wm,i ) /N

, where wm represent the mass fraction

of relevant alcohol, N is the number of binodal data, and also superscripts exp and cal stand for the experimental and calculated values, respectively.

3.4. Modeling

Fig. 7. Effect of temperature on cloud point, CP, as a function of alcohol (m) mole fraction, in the presence of aqueous solution of sodium thiosulfate (ca) salt: (——) ethanol; (——) 2-propanol; (——) 1-propanol; (——) 2-methyl-2propanol; (—䊉—) 2-butanol.

2-methyl-2-propanol (355.55 K). Therefore, the boiling-point data demonstrate that, in both classes, the alcohol with the higher boiling-point has more self-interaction forces between alcohol molecules and easily can be excluded from the rest of the solution as a separated phase. It should be noted that, a similar conclusion has been made by Wang et al. [20] only about ATPSs composed of completely miscible alcohols (i.e. 1-propanol and 2-propanol).

3.3. Effect of temperature on the phase-separation ability of the ATPS To study the effect of temperature on the investigated systems, the cloud-point (CP) temperature as a function of the alcohol mole fractions at temperature range T = (293.15–328.15) K at 5 K intervals was measured. The experimental CP data reported in Table 5 and plotted in Fig. 7 show the alcohol concentration dependence of CP for the same concentration of aqueous sodium thiosulfate solution for each of the studied systems. As shown in Fig. 7, in the case of ATPSs composed of 1-propanol or 2-methyl-2-propanol, the concentration of alcohol required to achieve a phase separation slightly decreases with increasing temperature, while in the case of ATPS composed of ethanol, the increase of the temperature was reflected by decreasing the concentration of required alcohol. On the other word, the phase-separation ability of the systems composed of 1-propanol or 2-methyl-2-propanol + sodium thiosulfate + water increased with increasing the temperature, whereas inversely the salting-out ability of the two-phase system composed of ethanol + sodium thiosulfate + water decreased with increasing the temperature. It should be noted that, in the case of the ATPSs composed of 2-butanol and 2-propanol the temperature did not affect in any sensible change on the alcohol mole fraction at the measured temperature range. Furthermore, the results show that the alcohol mole fraction required for phase-separation in the temperature range (293.15–328.15) K is in the order of: ethanol > 2-propanol > 1-propanol > 2-methyl2-propanol > 2-butanol, which is in agreement with hydrophilic series. This trend is similar to the one reported previously [7] for 1-propanol, 2-propanol, 2-methyl-2-propanol or 2butanol + dipotassium oxalate + water systems.

3.4.1. Correlation of the binodal data For the correlation of the binodal data a simple empirical three parameter equation was used. wca = a + b ln(wm ) + cwm

(2)

where wca and wm denote the mass fraction of salt and alcohol in the binodal curve, and a, b and c are fitting parameters. The experimental binodal curves were correlated to Eq. (2), and the obtained parameters along with the corresponding standard deviations (sd) are reported in Table 6. Also, Figs. 1–5 compare the experimental and calculated binodal curves for the studied ATPSs. On the basis of the standard deviations reported in Table 6 and the results shown in Figs. 1–5 it can be concluded that, Eq. (2) can successfully correlate the binodal curves of the investigated systems. 3.4.2. Correlation of the tie-lines data For the correlation of phase equilibrium of ATPSs several models have been developed. Also, at previous works [13,15], we successfully used the e-NRTL [14] model to correlate the LLE of some alcohol + salt + water systems. In this work we attempt to correlate the experimental tie-line data to the e-NRTL model. However, the obtained results show that the performance of the e-NRTL model in the correlation of the tie-line compositions is not good in some cases; especially when the binary interaction parameters were obtained using the binary osmotic coefficient data. More precisely, we realized that the nonrandomness factors should be treated as adjustable parameters to obtain the better results. However, the nine adjustable parameters of the e-NRTL model encouraged us to use a simpler equation. Therefore, we decided to generalize the segment based Wilson model, which has only six interaction parameters, to represent the LLE of the mixed solvent electrolyte systems obtained in this work. The model development for the eNRTL model was discussed in detail by Chen and Song [14]. Here we introduced the generalized Wilson model for the mixed-solvent electrolyte systems. 3.4.2.1. Generalized Wilson model for mixed solvent electrolyte systems. The generalized Wilson model for the excess Gibbs energy, GE , is built up from two contributions: a segment based local composition contribution to account the short-range interaction contribution, GE,SR , and a Pitzer–Debye–Hückel (PDH) contribution to account the long-range interaction contribution, GE,LR , GE = GE,SR + GE,LR

(3)

Accordingly, the activity coefficient of any component can be calculated as follows: ln j =

1 RT



ex ∂Gm ∂nj



(4) T,P,ni = / j

70

E. Nemati-Knade et al. / Fluid Phase Equilibria 321 (2012) 64–72

where j denotes any component (electrolyte or non-electrolyte). 3.4.2.2. Short range interaction contribution. Sadeghi [16] extended the Wilson equation to express the short-range interaction for saltcontaining polymer solutions, by applying the local composition concept to the individual segments, ions, and solvent molecule, rather than polymer, salt, and solvent and by incorporating the two assumptions of local electroneutrality and like ion repulsion proposed by Chen [22] and Chen and Evans [23]. Sadeghi [16] assumed the existence of four types of local cells, namely, cells with a central segment, cells with a central cation, cells with a central anion and cells with a central solvent molecule and obtained the following expression for GE,SR :



rXs + (Xc + Xa )Hca,s + Xw Hws GE,SR = − rnp ln CRT rXs + Xc + Xa + Xw − nc zc ln − na za ln − nw ln



rX H + X + X H

s s,ca a w w,ca rXs + Xa + Xw

rX H + X + X H

s s,ca c w w,ca rXs + Xc + Xw

rX H + (X + X )H

s sw c a ca,w + Xw rXs + Xc + Xa + Xw

.

(5)

where s, c, a, ca, p, w, r and z represent segment, cation, anion, salt, polymer, water, the number of segments and ions electric charge, respectively. Also, Hij is the binary interaction parameter between the i and j component, R is the universal gas constant, T is the absolute temperature, and C is a parameter that can be set as a fixed value or treated as an adjustable parameter to provide a better fit of the experimental values. This equation can be used to express the GE,SR of the mixed organic–aqueous solvent electrolyte systems if we consider the organic solvent (i.e. alcohol) as an individual segment, and the value of r = 1 may be used in this case (i.e. alcohol). Appropriate differentiation of Eq. (5), considering r = 1, results the expression for activity coefficient of any species. The generalized Wilson expressions for the systems containing two solvents (m) and one electrolyte (ca) are given in Appendix I. 3.4.2.3. Long range interaction contribution. The PDH equation [24] which is generalized to mixed solvents is used for the long-range contribution to the activity coefficients. The PDH equation has the following form:



ln iLR = −Aϕ

2Zj2 

1/2

1/2 ln(1 + Ix ) +

Zj2 Ix

3/2

− 2Ix 1/2

1 + Ix



(6)

where Ix is the ionic strength in mol fraction bases and Aϕ is the usual Debye–Hückel parameter: IX =

1 2 xi Zi 2 i

Aϕ =

1 1/2 (2NA ds ) 3

(7)



Qe2 εs kT

3/2 (8)

In the above relations, i refer to ions, Zi is the charge number of ion i and  is the closest distance parameter. Also, NA , k, T and Qe are Avogadro’s number, Boltzmann constant, absolute temperature and the electronic charge, respectively. Moreover, ds and εs are the mixed solvent density and dielectric constant, respectively. As mentioned above, in the case of mixed organic–aqueous solvents the difference in the dielectric constants and the densities of the solvents will be large and the solvent composition-dependent dielectric constant and density should be used [9]. In this work, a simple composition average mixing rules proposed by Chen et al.

[14] are used to calculate the dielectric constant and density of mixed solvent as follows:

xm 1 1  = ds d  x m m m

(9)

m

εs =



xm Mm

x  Mm m m

m

εm

(10)

where Mm is the molecular weight of the solvent m. 3.4.2.4. Details of correlation. For the correlation of the tie-line data, we used the value of  = 14.9 that has been frequently used for the aqueous electrolyte solutions [24]. Densities of water and alcohols were obtained from [25–28] at T = 298.15 K and reported in Table 1. Dielectric constants of the solvents were also obtained from Lide [19]. Following the Sadeghi [16] C parameter treated as a fixed value and the value of C = 10 was used. The generalized Wilson model has 6 interaction parameters. Hm,ca , Hca,m , Hw,ca , Hca,w , Hm,w and Hw,m . The four interaction parameters (Hw,ca , Hca,w , Hm,w , and Hw,m ) can be obtained from the correlation of the experimental water activity, osmotic coefficient or vapor liquid equilibrium (VLE) data for aqueous salt or alcohol solutions. The two remaining salt–alcohol, Hca,m , and alcohol–salt, Hm,ca parameters are determined from the fitting of LLE data. The salt–water, Hw,ca and water–salt, Hca,w binary interaction parameters obtained from the correlation of the osmotic coefficient data at T = 298.15 K for sodium thiosulfate + water binary systems reported in [29] using the Levenberg–Marquardt optimization algorithm. The obtained salt–water and water–salt binary interaction parameters along with the standard deviation are reported in Table 7. Also, alcohol–water, Hm,w , and water–alcohol, Hw,m , binary interaction parameters are obtained from the correlation of the binary VLE data for 1-propanol + water and 2-propanol + water at T = 298.15 K reported in Refs. [30,31], respectively, and also are given in Table 7. The reported sd values shows that generalized Wilson model can be successfully used for the correlation of the binary osmotic coefficient or VLE data. It should be noted that, we cannot access any data for the water + 2-methyl-2-propanol, 2-butanol or ethanol binary systems at T = 298.15 K and therefore, the alcohol–water and water–alcohol binary interaction parameters for these systems along with the alcohol–salt and salt–alcohol binary interaction parameters for all the studied systems are obtained from the correlation of the experimental tie-line compositions obtained in this work, using the following procedure. The requirement for thermodynamic equilibrium is that the Gibbs energy is at a minimum. It can be shown from classical thermodynamics that a two-phase system at constant pressure and temperature containing component i (alcohol, salt or water) at the alcohol-rich (top) and water-rich (bot) phases will obey the following constraints at equilibrium [32] (xj j )top = (xj j )bot

(11)

where x and  represent the mole fraction and the activity coefficient, respectively. The interaction parameters are evaluated from the fitting of experimental LLE data to Eq. (11) using the following objective function: Of =



p

l

exp

cal (xp,l,j − xp,l,j )

2

(12)

j

where xp,l,j is the mole fraction of the component j in the phase p for lth tie-line, and the superscripts cal and exp refer to the calculated and experimental values, respectively. In Eq. (12) the species j can be the alcohol, salt or solvent molecule. The mentioned procedure was also done to correlate the tie-line data using e-NRTL model. However, our main problem

E. Nemati-Knade et al. / Fluid Phase Equilibria 321 (2012) 64–72

71

Table 7 Values of restricted binary interaction parameters of generalized Wilson model and the e-NRTL model for the studied alcohol (m) + sodium thiosulfate (ca) + water (w) systems at T = 298.15 K and atmospheric pressure. The highlighted values are obtained from the correlation of the binary aqueous solutions, and other remaining parameters are obtained from the correlation of the tie-line compositions obtained in this work. Generalized Wilson model System

Hwca a

Hcaw a

104 sdb

Hwm

Hmw

103 sdb

Hcam

Hmca

Devc

1-Propanol + ca + w 2-Propanol + ca + w 2-Methyl-2-propanol + ca + w 2-Butanol + ca + w Ethanol + ca + w

5.5457

0.4393

4.38

0.4997 1.3389 0.8368 0.8432 1.3806

1.442 0.5808 0.8595 0.8517 0.0449

8.78 8.57 – – –

−0.2882 −3.8182 −0.5737 0.0558 2.4796

−6.7426 19.9556 2.4196 −4.7096 −5.5052

0.01 0.33 0.02 0.04 0.16

e-NRTL model System

w,ca

ca,w

103 sdb

w,m

m,w

103 sdb

ca,m

m,ca

Devc

1-Propanol + ca + w 2-Propanol + ca + w 2-Methyl-2-propanol + ca + w 2-Butanol + ca + w Ethanol + ca + w

2.1794

−14.8242

1.07

1.9277 1.9909 1.8720 2.2114 1.1755

−1.3613 −2.0431 2.0156 3.6574 4.3824

9.30 13.75

3.9221 85.7462 173.0511 45.5011 −2.3694

−6.6309 −5.2412 −5.4097 −4.9766 −4.8496

0.75 0.39 0.06 0.13 0.17

a

Water–salt and salt–water binary interaction parameters were calculate from the osmotic coefficient data reported in Ref. [29].

b

sd =



i

 0.5

exp

(awi

 

− awical ) /N

, where aw represent the activity of water, N is the number of data, and also superscripts exp and cal stand for the experimental and

calculated values, respectively. c

Dev =

p

l

j

exp

2

cal ((100wp,l,j,T − 100wp,l,j,T ) /6N), where wp,l,j , is the weight fraction of the component j (i.e. alcohol, salt or water) in the phase p for lth tie-line and N

represents the number of tie-line data points.

in the correlation of tie-line composition using e-NRTL model is the selection of appropriate values for the nonrandomness factors (˛ij ). The ˛ values were treated as a fixed value in most previous studies and in most cases a proper value between 0.1 and 0.3 was used for all nonrandomness factors [9,14]. However, in this study we obtained the poor quality of fitting with using the same value for all ˛ factors. Several values were examined and finally the best overall results in the correlation of the binary or ternary data were obtained when the values of ˛wm = ˛mw = 0.25, ˛caw = ˛wca = 0.1 and ˛mca = ˛cam = 0.4 were used for all the studied systems. The obtained restricted binary interaction parameters of the generalized Wilson model and e-NRTL model are reported in Table 7 along with the relative deviations (Dev). Furthermore, to show the reliability of both models in the correlation of the tieline data comparison between the experimental and calculated phase equilibrium data using the parameters reported in Table 7 are shown in Figs. 1–5. The reported Dev values in Table 7 and the results shown in Figs. 1–5, reveal that the performance of the generalized Wilson model in the correlation of the tie-line data using restricted binary interaction parameters is very good; however the performance of the e-NRTL model for the systems in which only two adjustable parameters (i.e. salt–alcohol and alcohol–salt binary parameters) are obtained from the correlation of the tieline compositions is not good (i.e. ATPSs composed of 1-propanol and 2-propanol alcohols). Furthermore, the results show that the performance of the simpler generalized Wilson model in the correlation of binary and ternary data for all of the studied systems is better than the e-NRTL model.

4. Conclusions Experimental binodal and tie-line data for 1-propanol, 2propanol, 2-methyl-2-propanol, 2-butanol or ethanol + sodium thiosulfate + water ternary systems at T = 298.15 K were reported, and it was found that the phase-separation ability of the studied alcohols is in the order of: 2-butanol > 2-methyl-2propanol > 1-propanol > 2-propanol > ethanol. Also, the obtained results confirmed that the two-phase forming ability of the slightly

soluble alcohols is more than the completely miscible alcohols due to the more weak intermolecular interactions with water molecules. Additionally, the boiling-point data demonstrate that the alcohol with higher boiling-point, in both completely miscible and slightly soluble cases, has more self-interaction forces between alcohol molecules and have more affinity to form an ATPS. Also, the obtained cloud point data shows the phase-separation ability of the systems composed of 1-propanol or 2-methyl-2propanol + sodium thiosulfate + water increased with increasing the temperature, whereas inversely in the case of ethanol + sodium thiosulfate + water system phase-separation ability was decreased. Furthermore, the temperature has no significant effect on the LLE of 2-propanol or 2-butanol + sodium thiosulfate + water ATPSs. Additionally, the segment based Wilson equation was generalized to represent the mixed organic–aqueous solvent electrolyte systems and successfully used for the correlation of binary and ternary data, and the restricted binary interaction parameters were also reported. The tie-line compositions were also correlated using e-NRTL model. Comparison between the experimental and calculated values shows that the performance of the generalized Wilson model in the correlation of the binary and ternary data is very good and better than the e-NRTL model.

List of symbols n0w Refractive index of pure water a, b, and c Parameters of empirical binodal equation Constants of Eq. (1) for nonelectrolyte am aca Constants of Eq. (1) for salt Aϕ Debye–Hückel parameter C The parameter of Wilson model ca Salt d Density (kg m−3 ) Dev Deviation Electronic charge (=1.602 × 10−19 ) (C) Qe Of Objective function Excess Gibbs energy (J mol−1 ) GE

72

Hij Ix k n NA R sd T w x Zi

E. Nemati-Knade et al. / Fluid Phase Equilibria 321 (2012) 64–72

Wilson binary interaction parameter between component i and j Ionic strength in mole fraction bases Boltzmann constant (=1.381 × 10−23 ) (J K−1 ) Mole number (mol) Avagadro’s number (=6.022 × 1023) (mol−1 ) Universal gas constant (=8.314) (J mol−1 K−1 ) Standard deviation Temperature (K) Mass fraction Mole fraction Ionic charge of ion i

The expression for water activity coefficient can be obtained by replacing the subscript of m with that of w and w with m in Eq. (A.I). −1 ln cSR Czc



Xm Hm,w

Xm + Xc + Xa + Xw  Xw + (Xc + Xa )Hca,w + Xw

+

 X (H 

a m,ca − 1) + Xw (Hm,ca − Hw,ca )

 X (H 

c m,ca − 1) + Xw (Hm,ca − Hw,ca )



Xm + Xc + Xw  Xm Xm + (Xc + Xa )Hca,m + Xw Hw,m

+

+

(A.I)

+

 (X + X )(1 − H ) + X (1 − H ) 

c a ca,m w w,m Xm + Xc + Xa + Xw

(A.II) +

.

References

Xm + Xc + Xa + Xw  Xc Xm Hm,ca + Xa + Xw Hw,ca

Xm + Xa + Xw   Xa Xm Hm,ca + Xc + Xw Hw,ca

+

The expression for anion activity coefficient can be obtained by replacing the subscript of c with that of a and a with c in Eq. (A.II).



 (X + X )(H c a m,w − Hca,w ) + Xw (Hm,w − 1) 

Xm + Xc + Xw  Xm Xm + (Xc + Xa )Hca,m + Xw Hw,m Xm + Xc + Xa + Xw

The Wilson activity coefficient expressions for the systems containing two solvents (m) and one electrolyte (ca) are as follows:



Xm + Xc + Xa + Xw  Xa Xm Hm,ca + Xc + Xw Hw,ca



 X (H m ca,m − 1) + Xw (Hca,m − Hw,m )

Appendix A.

X + (X + X )H

m c a ca,m + Xw Hw,m

+ Xm + Xa + Xw  Xw Xm Hm,w + (Xc + Xa )Hca,w + Xw

 X (1 − H ) + X (1 − H ) 

m m,ca w w,ca 

Subscripts and superscripts cal Calculated value exp Experimental value i Ion number Solvent number j, k m Solvent (water or alcohol) n Component number Alcohol-rich phase top bot Water-rich phase PDH Pitzer–Debye–Hückel contribution SR Short range interaction parameter LR Long range interaction parameter

= ln



X H

m m,ca + Xa + Xw Hw,ca



 X (H m ca,w − Hm,w ) + Xw (Hca,w − 1)

Greek letters Activity coefficient  ε Dielectric constant (=48.85 × 10–12εr ) (C2 J−1 m−1 )  Closest approach parameter Binary interaction parameters of e-NRTL model

−1 SR ln m C

= ln

.

[1] J.S. Dahyabhai, K.T. Krishna, J. Chem. Eng. Data 26 (1981) 375–378. [2] J.M. Janusz, J.D. Andrew, AIChE J. 40 (1994) 1459–1465. [3] T. Zhigang, Z. Rongqi, D. Zhanting, J. Chem. Technol. Biotechnol. 76 (2001) 757–763. [4] T.J. Chou, A. Tanioka, Ind. Eng. Chem. Res. 37 (1998) 2039–2044. [5] M.T. Zafarani-Moattar, S. Banisaeid, M.A.S. Beirami, J. Chem. Eng. Data 50 (2005) 1409–1413. [6] A. Salabat, M. Hashemi, J. Chem. Eng. Data 51 (2006) 1194–1197. [7] H. Shekaari, R. Sadeghi, S.A. Jafari, J. Chem. Eng. Data 55 (2010) 4586–4591. [8] E.A. Macedo, P. Skovborg, P. Rasmussen, Chem. Eng. Sci. 45 (1990) 875–882. [9] G.H. van Bochove, G.J.P. Krooshof, Th.W. de Loos, Fluid Phase Equilibr. 171 (2000) 45–58. [10] K. Thomsen, M.C. Iliuta, P. Rasmussen, Chem. Eng. Sci. 59 (2004) 3631–3647. [11] F. Pirahmadi, M.R. Dehghani, B. Behzadi, S.M. Seyedi, H. Rabiee, Fluid Phase Equilibr. 299 (2010) 122–126. [12] G.R. Santos, S.G. D’avila, M. Aznar, Braz. J. Chem. Eng. 17 (2000) 721–734. [13] M.T. Zafarani-Moattar, E. Nemati-Kande, A. Soleimani, Fluid Phase Equilibr. 313 (2012) 107–113. [14] C.C. Chen, Y. Song, AIChE J. 50 (2004) 1928–1941. [15] E. Nemati-Kande, H., Shekaari, J. Sol. Chem., Accepted Manuscript. [16] R. Sadeghi, J. Chem. Thermodyn. 37 (2005) 323–329. [17] M.T. Zafarani-Moattar, S. Hamzehzadeh, Fluid Phase Equilibr. 304 (2011) 110–120. [18] D.B. Alger, J. Chem. Educ. 68 (1991) 939. [19] D.R. Lide, CRC Handbook of Chemistry and Physics, 87th ed., Taylor and Francis, Boca Raton, FL, 2007. [20] Y. Wang, J. Wang, J. Han, S. Hu, Y. Yan, Cent. Eur. J. Chem. 8 (2010) 886–891. [21] Y. Wang, Y. Yan, S. Hu, X. Xu, J. Chem. Eng. Data 55 (2010) 876–881. [22] C.C. Chen, Fluid Phase Equilibr. 83 (1993) 301–312. [23] C.C. Chen, L.B. Evans, AIChE J. 32 (1986) 444–454. [24] J.M. Simonson, K.S. Pitzer, J. Phys. Chem. 90 (1986) 3009–3013. [25] F.M. Pang, C.E. Seng, T.T.M.H. Teng, J. Mol. Liq. 136 (2007) 71–78. [26] K. Rajagopal, S. Chenthilnath, Indian J. Pure. Appl. Phys. 48 (2010) 326–333. [27] J.M. Resa, C. González, M. Juez, S.O. de Landaluce, Fluid Phase Equilibr. 217 (2004) 175–180. [28] R.M. Pires, H.F. Costa, A.G.M. Ferreira, I.M.A. Fonseca, J. Chem. Eng. Data 52 (2007) 1240–1245. [29] R.A. Robinson, J.M. Wilson, R.H. Stokes, J. Am. Chem. Soc. 63 (1941) 1011–1013. [30] J. Gmehling, U. Onken, Vapor–Liquid Equilibrium Data Collection—Aqueous– Organic Systems, Chemistry Data Series, vol. 1, DECHEMA, Frankfurt, Germany, 1977. [31] T. Tsuji, K. Hasegawa, T. Hiaki, M. Hongo, J. Chem. Eng. Data 41 (1996) 956–960. [32] M.T. Zafarani-Moattar, E. Nemati-Kande, Calphad 34 (2010) 478–486.