Separation of phenol from aqueous solution by 2-octanone: Phase equilibrium measurements and thermodynamic studies

Journal of Molecular Liquids 300 (2020) 112323

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Separation of phenol from aqueous solution by 2-octanone: Phase equilibrium measurements and thermodynamic studies Meiling Jiang, Shuai Shen, Yun Chen ⁎ Department of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, PR China

a r t i c l e

i n f o

Article history: Received 25 May 2019 Received in revised form 5 December 2019 Accepted 14 December 2019 Available online 16 December 2019 Keywords: Liquid liquid equilibria 2-Octanone Phenol NRTL UNIQUAC

a b s t r a c t The applicability of 2-octanone as solvent for the liquid phase extraction of phenol from aqueous solution was investigated in this work. The liquid liquid equilibrium (LLE) for the ternary systems {2-octanone + phenol + water} was experimentally determined at 298.15 K, 318.15 K and 338.15 K under atmospheric pressure. Distribution coefficients and separate factors calculated from the experimental LLE data were used to judge if 2-octanone can be used as potential solvent to extract phenol from aqueous solution. Distribution coefficients and separation factors of 2-octanone were also compared with other extractants and results show that 2-octanone has excellent extraction performance. Binary interaction parameters were regressed by the NRTL and UNIQUAC methods, and related physical meaning is explained by interaction forces. The root mean squared deviations (RMSDs) show that both models can well describe phase equilibrium behavior of ternary system {2-octanone + phenol + water}. In order to predict ternary LLE data at other temperatures, the NRTL model was used to simultaneously regress ternary experimental data at all temperatures and the largest RMSD is 0.49%. © 2018 Elsevier B.V. All rights reserved.

1. Introduction In recent years, on account of growing shortage of crude oil and increasing demand for petroleum in China, the development of coal gasification is a strategic choice for adjusting the energy structure [1]. However, the wastewater generated by the coal gasification industries will become a problem that the development of the industry has to solve [2]. This kind of wastewater consists of a series of organic pollutants, such as phenols, polycyclic aromatic hydrocarbons, fatty acids, long-chain n-alkanes, nitrogen heterocyclic compounds, cyanides, thiocyanates and ammonia compounds, among which phenols are the main pollutants [3]. Phenolics are a typical amphiphilic compound and have potentially high toxicity, hazardous properties and poor biodegradability, and must be disposed of prior to discharge [4]. Solvent extraction is a very effective method to separate phenolic compounds or other components based on their relative solubilities in two different immiscible liquids [5–7]. Solvent extraction, solvent recovery and solvent stripping are three common steps in the treatment on industrial phenol wastewater [4,8]. After the solvent extraction process, the total phenols concentration in the wastewater was generally reduced below 400 mg·L−1, followed by biochemical treatment. Phenol in the treated wastewater is lower than 50 mg·L−1. And then the concentration of the extractant ⁎ Corresponding author. E-mail address: [email protected] (Y. Chen).

https://doi.org/10.1016/j.molliq.2019.112323 0167-7322/© 2018 Elsevier B.V. All rights reserved.

in the treated water will be less than 50 mg·L−1 after stripping. Finally, extraction agent and phenols in the extract phase are separated by two different distillation columns. The recovered extractant is pumped back to the extraction column for recycle. Some organic solvents such as methyl isobutyl ketone (MIBK) [9], isopropyl acetate [10], 2-pentanone [11], methyl isopropyl ketone (MIPK) [12], mesityl oxide [13] were selected to separate phenols from coal chemical waste water because they have very efficient extracting ability in industry. However, the solubility of these conventional solvents in water at ambient temperature is greater than 1.9%. If the solvent-containing wastewater directly enters the subsequent biochemical treatment, on the one hand, the biochemical treatment load will be increased, and on the other hand, the solvent will also be extremely depleted. Therefore, it is necessary to recover the solvent by means of rectification in industrial practical applications. The solubility of 2-octanone in water is only 0.0899% at 293.15 K [14]. But there is no data available for 2-octanone to separate phenol from water so far. The LLE system of 2-octanone + phenol + water was researched in this work. The study of the LLE behavior is conducive to the promotion of improved extraction technology and plays an important role in the design and economic evaluation of industrial extraction processes [15,16]. The most commonly used models in the study of liquid-liquid extraction are Universal Quasi-Chemical (UNIQUAC) [17] and NonRandom Two-Liquid (NRTL) [18]. The UNIQUAC and NRTL models are generally used to correlate the experimental data, and the interaction

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M. Jiang et al. / Journal of Molecular Liquids 300 (2020) 112323

parameters of components were obtained. These interaction parameters are essential for extraction process simulation [19]. This work focuses on exploring the phase equilibrium behavior for 2-octanone to extract phenol from aqueous solution. The tie-line data of ternary systems {2-octanone + phenol + water} were investigated at different temperatures and atmospheric pressure. Distribution coefficients (D) and separation factors (S) were calculated to evaluate the extraction ability of 2-octanone. All experimental LLE data were correlated by the NRTL and UNIQUAC models.

shown that the 2-octanone can separate the phenol from aqueous solution. As the phenol concentration increases, the slope of the tie-line increases. This is the reason that the amount of phenol is increased in each experiment, the increasing amount of phenol in the organic phase is greater than that in the aqueous phase when equilibrium is reached. To evaluate the extraction capacity of 2-octanone to separate phenol from aqueous solution, the distribution coefficients (D) and separation factors (S) were calculated by the following equations: D¼

wO2 wW 2

ð1Þ

S¼

wO2 =wO3 W wW 2 =w3

ð2Þ

2. Experimental 2.1. Chemicals All chemicals used in this work were chromatographic grade. The chemicals were supplied by Xiya reagent Co., Ltd. and were used as purchased. In the experiments, distilled water was used to prepare all solutions. The details of the chemicals are given in Table 1. 2.2. Procedure Mixture of 2-octanone + phenol + water at 298.15,318.15 and 338.15 K was put into the 100 ml self-design glass cell [20]. The mixture was vigorously agitated by a magnetic stirrer for 2 h and then left to settle for at least 20 h to reach phase equilibrium. A series of tie-line data were determined by gradually altering the concentration of the phenol. The samples were weighed by mass using an analytical balance (Shimadzu AUW220D, accuracy to 0.00001 g). The organic component of the sample was measured using a gas chromatography (GC-6820, Agilent Technologies), equipped with flame ionization detectors (FID). 3,4-Xylenol and 2-heptanone were used as internal standards for phenol and 2-octanone, respectively. The separation of each component relies on a capillary column Agilent DB-5MS with a 30 m × 320 μm × 0.25 μm. The head pressure of the carrier nitrogen gas was 0.5 MPa, and the temperatures of the injector and detector were set to 523.15 K and 543.15 K, separately. The oven temperature was kept at 313.15 K for 2 min, followed by a constant heating rate of 20 K·min−1 until a final temperature of 453.15 K. The final temperature was kept for 5 min. The mass fraction of water in the sample was directly determined by Karl Fischer titration using a ZSD-2 automatic moisture titrator. The deviation is within 0.01%. Every sample was analyzed at least three times, and the mean value was used.

where w2 and w3 are defined as the mass fraction of phenol and water in the organic phase or the aqueous phase, individually; the superscript W and O represent the organic phase and the aqueous phase, respectively. The calculation results of D and S were shown in Table 2 and were plotted in Fig. 2. In the experimental range, the D is between 16.69 and 118.04; The maximum of S is 8811.36 and its minimum is 259.78. Both show that 2-octanone is an excellent extractant for phenol. Due to the different concentrations of the components in Table 2, it is inconvenient to compare D and S; Fig. 2 can be observed to investigate the effect of temperature and phenol concentration on D and S. The results show that the distribution coefficient (D) and separation factor (S) decrease slightly with the increase of temperature. It indicated that the high temperature goes against the extraction of phenol by using 2-octanone. The temperature is more effective in promoting the solubility of phenol in 2-octanone than that of phenol in water. And at the lower concentration of phenol (wW 2 in the range of 0.0005–0.005), as the phenol content in the aqueous solution increases, the decline of

Table 2 Experimental LLE data in mass fraction for 2-octanone (1) + phenol (2) + water (3) system at 298.15, 318.15, 338.15 K under atmospheric pressurea, together with the distribution coefficient D and separation factor S. T/K

298.15

3. Results and discussions 3.1. LLE experimental data The ternary equilibrium tie-line data for the 2octanone + phenol + water system was surveyed at T = (298.15, 318.15, and 338.15) K under atmospheric pressure. Ternary tie-line data at each temperature are given in Table 2. The corresponding triangular phase diagrams for these ternary systems at different temperatures are shown in Fig. 1. In these figures, the slope of tie-lines is

Table 1 Details of the chemical reagents used in this work.

338.15

Chemical

Supplier

Mass fraction purity

Purity analysis method

2-Octanone 2-Heptanone Phenol 3,4-Xylenol Methanol

Xiya Reagent Ltd. Xiya Reagent Ltd. Xiya Reagent Ltd. Xiya Reagent Ltd. Xiya Reagent Ltd.

99.62% 99.52% 99.51% 99.34% 99.31%

GCa GCa GCa GCa GCa

a

Gas chromatography.

318.15

Organic phase

Aqueous phase

wO 1

wO 2

wO 3

wW 1

wW 2

wW 3

0.9899 0.9264 0.8628 0.8171 0.7533 0.6881 0.6340 0.5921 0.5486 0.9889 0.9257 0.8641 0.8211 0.7560 0.6929 0.6414 0.5956 0.5499 0.9882 0.9253 0.8694 0.8239 0.7504 0.7021 0.6353 0.5945 0.5523

0.0000 0.0602 0.1214 0.1644 0.2214 0.2786 0.3292 0.3662 0.4007 0.0000 0.0603 0.1197 0.1591 0.2185 0.2712 0.3149 0.3543 0.3921 0.0000 0.0596 0.1128 0.1554 0.2245 0.2651 0.3166 0.3533 0.3850

0.0101 0.0134 0.0159 0.0185 0.0253 0.0333 0.0368 0.0417 0.0507 0.0111 0.0141 0.0162 0.0198 0.0254 0.0360 0.0437 0.0501 0.0580 0.0118 0.0151 0.0177 0.0207 0.0250 0.0329 0.0481 0.0523 0.0627

0.0017 0.0015 0.0014 0.0013 0.0012 0.0010 0.0009 0.0007 0.0006 0.0016 0.0014 0.0013 0.0012 0.0010 0.0009 0.0008 0.0007 0.0006 0.0016 0.0014 0.0013 0.0011 0.0010 0.0009 0.0008 0.0007 0.0006

0.0000 0.0005 0.0017 0.0029 0.0051 0.0071 0.0098 0.0122 0.0152 0.0000 0.0006 0.0019 0.0035 0.0058 0.0091 0.0120 0.0144 0.0190 0.0000 0.0006 0.0021 0.0040 0.0080 0.0110 0.0152 0.0191 0.0231

0.9983 0.9980 0.9970 0.9958 0.9937 0.9918 0.9893 0.9871 0.9843 0.9984 0.9981 0.9968 0.9954 0.9932 0.9901 0.9873 0.9850 0.9804 0.9984 0.9980 0.9967 0.9949 0.9911 0.9882 0.9840 0.9802 0.9763

D

S

– 118.04 73.55 57.07 43.32 39.07 33.66 30.09 26.38 – 102.17 62.33 45.47 37.55 29.86 26.31 24.60 20.61 – 97.63 54.40 39.08 28.01 24.14 20.85 18.48 16.69

– 8811.36 4623.45 3068.81 1699.39 1162.42 904.30 711.52 512.32 – 7257.89 3837.59 2290.43 1466.49 822.00 594.50 483.72 348.45 – 6463.98 3057.15 1876.07 1108.49 726.20 426.43 346.41 259.78

a Standard uncertainties u are u(T) = 0.1 K, u(p) = 1 kPa, u(wO 1 ) = 0.0010, u O W W W (wO 2 ) = 0.0011, u(w3 ) = 0.0013, u(w1 ) = 0.0001 u(w2 ) = 0.0010, u(w2 ) = 0.0009.

M. Jiang et al. / Journal of Molecular Liquids 300 (2020) 112323

3

alcohol solvent in Table 3 is not good, because the solubility of alcohol in water is relatively large. The ketones have the best extraction performance compared with other solvents. Their D and S are up to 164.59 and 8811.36. The extraction efficiency of ether and ester solvents is worse than that of ketone solvents. It may be because the oxygen group of the former is in the carbon chain, and the ability to form hydrogen bonds with phenol is weaker than that of ketone solvents whose oxygen group is outside the carbon chain. Thus, there are many studies on the extraction of phenol with ketones. From Table 3 [22–33], it can be observed that the longer the carbon chain, the lower the solubility; the more the branched chain, the higher the solubility in water. In order to compare the extraction performance of various extractants for phenol in more detail, the variation of D and S of different solvents at 298.15 K with the mass fraction of phenol in aqueous phase is shown in Figs. 3 and 4. When mass fraction of phenol in the aqueous solution is from 0.005 to 0.0152, distribution coefficient of 2-octanone to extract phenol from water is from118.04 to 26.38. Distribution coefficient gradually decreased with the increasing of phenol concentration in the aqueous solution. Distribution coefficient of 2-octanone is close to that of most ketones such as methyl butyl ketone, methyl isobutyl ketone, mesityl oxide and methyl isopropyl ketone, and it is slightly smaller than that of 2-pentanone. Distribution coefficients of ketones is obviously better than those of alkanes and alcohols such as cineole, 2-methoxy-2methylpropane, 1-dodecanol, toluene, m-xylene and propan-2-yl benzene. As can be seen from Table 3, the solubility of alkane in water is the lowest and distributon coefficient of alkane to extract phenol from water is the smallest in three solvents including ketones, alcohols and alkane. The solubilities of alcohols and ketones in water are generally higher, and distribution coefficients of ketones are higher than those of alcohols. Solubility of 2-octanone in water is 899 mg·L−1 and the lowest in all ketones. Its distribution coefficient is close to those of other ketones. From Fig. 4, separation factor of 2-octanone is the largest in all researched extractants and between 8811.36 and 512.32 within the scope of the study. Its separation factor is gradually reduced along with its distribution coefficient when phenol concentration in water rises. For ketones, alcohols, and alkane extractants, separation coefficient of ketones is greater than that of alcohols, and alcohols are larger than alkanes, which has a similar change with distribution coefficient.

Fig. 1. Experimental and calculated LLE results in mass fraction for the system 2octanone + phenol + water at different temperatures. (*) experimental value; (△) calculated value by single temperature regression of NRTL model; (○) calculated value by UNIQUAC model; (□) calculated value by single temperature regression of NRTL model.

D and S is sharp, and then tend to be gentle as the phenol concentration continues (wW 2 in the range of 0.005–0.025) to increase. This is because the extractant can extract more phenol at a lower concentration of phenol, but as the phenol content increases, the amount of phenol in the solvent is becoming more and more saturated, the extraction ability decreases. Comparison of similar systems with different kinds of solvents is given in Table 3. Obviously, distribution coefficient and separation factor of hydrocarbon solvents are generally smaller than other kinds of solvents and their values is between 1.49 and 15.7 and between 10.3 and 560, respectively. This may be because the polarity of hydrocarbon solvents is lower than that of esters, alcohols, ethers and ketones, and phenols containing hydroxyl groups are polar substances. Therefore, based on the principle of similarly compatible principles, it may be difficult for hydrocarbon solvents to separate phenols. The extraction efficiency of

Fig. 2. The distribution coefficient(D) and separation factor(S) versus mass fraction of phenol in aqueous phase for 2-octanone + phenol + water system, (solid symbol) D W versus wW 2 ; (hollow symbol) S versus w2 .

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M. Jiang et al. / Journal of Molecular Liquids 300 (2020) 112323

Table 3 The distribution coefficients and separation factors for the (solvent + phenol + water) systems. Solvent

Chemical formula

Solubility (mg·L−1)25 °C

Solvent type

T/K

wW 2

D

S

Lit

Toluene

C7H8

526

Hydrocarbon

m-Xylene

C8H10

160

Hydrocarbon

(Propan-2-yl) Benzene

C9H12

61.3

Hydrocarbon

2-Methoxy-2-methylpropane

C5H12O

51,000

Ether

Isopropyl Ether

C6H14O

8800(20 °C)

Ether

Cineole

C10H18O

3500(21 °C)

Ether

Dimethyl Carbonate Isopropyl acetate Methylphenyl Carbonate Diphenyl Carbonate 2-Propanol 1-Butanol

C3H6O3 C5H10O2 C8H8O3 C13H10O3 C3H8O C4H10O

138,000 29,000 – Insoluble 1,000,000 63,200

Ester Ester Ester Ester Alcohol Alcohol

2-Butanol

C4H10O

181,000

Alcohol

tert-Butanol Isobutanol

C4H10O C4H10O

1,000,000 85,000

Alcohol Alcohol

1-Dodecanol

C12H26O

4

Alcohol

2-Butanone Methyl Isopropyl Ketone

C4H8O C5H10O

223,000 52,370(20 °C)

Ketone Ketone

2-Pentanone

C5H10O

43,000

Ketone

Methyl Butyl Ketone

C6H12O

17,200(20 °C)

Ketone

Mesityl Oxide

C6H10O

28,900(20 °C)

Ketone

Methyl Isobutyl Ketone

C6H12O

19,000

Ketone

2-Octanone

C8H16O

899(20 °C)

Ketone

298.15 303.15 298.15 303.15 293.2 298.2 308.2 298.15 313.15 323.15 319.15 329.15 283.15 298.15 313.15 358.15 323.15 318.15 358.15 298.15 298.15 313.15 298.15 313.15 298.15 319.15 333.15 298.15 313.15 323.15 333.15 343.15 298.15 298.15 313.15 323.15 298.15 313.15 323.15 298.15 323.15 298.15 313.15 323.15 298.15 313.15 323.15 298.15 318.15 338.15

0.012–0.033 0.001–0.023 0.01.-0.034 0.007–0.036 0.0191–0.0549 0.010–0.065 0.0162–0.0637 0.000076–0.001085 0.000053–0.002521 0.000118–0.001711 0.0019–0.5 0.0011–0.169 0.00000666–0.00179 0.00000839–0.00245 0.00001230–0.00367 0.0066–0.1580 0.0007–0.0154 0.0010–0.1236 0.0010–0.0809 0.063–0.087 0.0014–0.0622 0.0008–0.00746 0.0080–0.0631 0.0114–0.0829 0.0333–0.0560 0.0066–0.0720 0.0036–0.0777 0.00150–0.05101 0.00259–0.05217 0.00151–0.04796 0.00296–0.06135 0.00318–0.068183 0.002–0.067 0.00034–0.00505 0.00024–0.00449 0.00024–0.00515 0.00022–0.00748 0.00051–0.00583 0.00031–0.00926 0.00016–0.00107 0.00026–0.00507 0.00023–0.00608 0.00029–0.00771 0.00035–0.00877 0.000031–0.001581 0.000044–0.002246 0.000046–0.002721 0.00051–0.01519 0.00059–0.01902 0.00061–0.02307

6.9–10.8 6.6–15.7 1.6–13.4 6.8–12.7 1.79–3.23 1.87–2.72 1.49–2.75 62.21–54.19 50.26–49.26 27.45–40.01 1.84–121.95 21.51–72.82 55.21–50.85 41.65–36.40 27.94–23.93 27.66–3.61 29.29–9.12 35.65–5.38 40.16–7.79 10.57–3.58 46.57–10.86 69–9.01 7.14–10.81 11.13–8.02 14.89–12.55 4.98–35.98 3.24–22.22 24.53–8.69 21.58–8.05 21.13–8.18 18.68–7.59 17.61–7.04 31.5–10.7 155.88–66.67 122.92–64.48 92.92–60.02 164.59–56.00 145.88–47.46 122.52–44.68 112.5–91.78 76.15–47.50 105.4–52.1 90.2–41.5 75.3–36.7 103.23–84.44 65.91–59.57 63.04–49.06 118.04–26.38 102.17–20.61 97.63–16.69

22.0–60.5 15.9–68.6 10.3–560.0 39.4–247.0 300.24–139.85 240.58–93.41 172.49–82.06 4754.27–1252.43 3165.78–974.83 1693.98–1036.88 4.86–835.34 96.40–3034.40 7237.2–2883.08 5190.23–2003.95 3321.38–1271.84 187.97–9.21 1101.53–36.38 1756.86–23.89 2277.30–37.06 36.79–7.06 243.66–52.44 336.81–32.67 22.17–48.95 42.00–25.64 70.80–44.21 7.65–207.94 4.64–199.20 1569.20–207.98 1187.46–165.06 1021.99–159.00 859.94–142.18 658.14–120.88 220.5–45.6 3751.52–872.19 2718.08–858.12 1890.82–718.90 4094.87–714.31 3245.68–557.17 2561.15–507.87 4255–2390 2312–797.3 2599–1007 1803–642.2 1497–536 5049.03–2258.31 2577.03–1414.75 2204.23–1219.33 8811.36–512.32 7257.89–348.45 6463.98–259.78

[22] [22] [22] [22] [23] [23] [23] [24] [24] [24] [25] [25] [26] [26] [26] [27] [10] [28] [27] [29] [30] [30] [30] [30] [30] [25] [25] [31] [31] [31] [31] [31] [29] [12] [12] [12] [11] [11] [11] [32] [32] [13] [13] [13] [33] [33] [33] This work. This work This work

UNIQUAC model:

3.2. Correlation of LLE data The most commonly used models in the study of liquid-liquid extraction are Non-Random Two-Liquid (NRTL) [18] and Universal Quasi-Chemical (UNIQUAC) [17], which are expressed as follows: NRTL model:

X ln γi ¼

τ ji  Gji  x j

j

X

ðGki  xk Þ



2

3 τmj  Gmi  xm X Gij  x j 6 7 m 7 6 þ 4τ ij − X G  x  5 G  x kj k kj k j

k

  g ij −g jj bij Gij ¼ exp −α ij  τij ; τij ¼ ¼ RT T

X

ð3Þ

k

ð4Þ

 φi z θ φ X þ  qi  ln i þ li − i xi  l j −qi  xi 2 φi xi j 2 3 X X θ j  τ ij  4 P ln θ j  τ ji 5 þ qi −qi  θk  τkj j j

ln γi ¼ ln

   u −u  bij ij jj ¼ exp − τij ¼ exp − RT T

ð5Þ

ð6Þ

where the parameters τji indicates the characteristic energy of the interaction between i-type and j-type molecules. gij, gji and uij, uji refer to the intermolecular attractive energy (J·mol−1). bij and bji obtained by regression of measured LLE data at each temperature represent binary parameters, individually. For the NRTL model, the fixed non-randomness parameter (αij) was set as 0.2 or 0.3. For UNIQUAC model, the structural

M. Jiang et al. / Journal of Molecular Liquids 300 (2020) 112323

5

Table 4 The UNIQUAC structural parameters (r and q) for pure components. Component

ri

qi

Water Phenol 2-Octanone

0.9200 3.5517 5.9455

1.400 2.680 5.036

where wijk represents the mass fraction of component i in the j phase of the kth tie-line. n is the number of data points. The superscript exp and cal represent experimental data and calculates data, separately. And all the calculated parameters and RMSD values were given in Table 5. The ternary data calculated at different temperatures are plotted in Fig. 1 (a,b,c). All RMSDs are lower than 0.0067, and it indicates that the NRTL and UNIQUAC models are suitable for describing phase behavior of the studied system (2-octanone + phenol + water). According to the average values of RMSD in the two models, it can be observed that the accuracy of NRTL is slightly higher than that of UNIQUAC. τij and τji were added into Eq. (6) to obtain the following equation:

Fig. 3. Comparison of distribution coefficient D of extracting phenol with different extractants at 298.15 K.

parameters of each component are calculated by the literature [21] which were presented in Table 4. The binary interaction parameters in the NRTL and UNIQUAC models were correlated by Aspen Plus 8.4 software. The fitting parameters were obtained by minimizing the objective function (OF), which was defined as:

OF ¼

3 X 2 X n  X

wexp −wcal ijk ijk

2

ð7Þ

i¼1 j¼1 k¼1

In order to verify the consistency of the models and experimental data, a relative root mean square deviation (RMSD) is proposed, which was calculated by the following expression: 2  2 31=2 3 2 n exp cal ∑ ∑ ∑ w −w i¼1 j¼1 k¼1 ijk ijk 6 7 RMSD ¼ 4 5 6n

ð8Þ

    g ij þ g ji − gii þ g jj g ij −g jj g ji −g ii bji þ bij ¼ þ ¼ τij þ τji ¼ RT RT RT T

ð9Þ

Here, g is specified as a negative value. If the interaction force of the same molecule is greater than that of different molecules, the result of bij + bji is positive; Instead, if the interaction force of the same molecule is less than that of the different molecules, the result of bij + bji is negative. And the more negative bij + bji, the stronger the interaction between different molecules. bij + bji at different temperatures was plotted in Fig. 5. As seen from this figure, values of b12 + b21 are negative; values of b23 + b32 and b13 + b31 are positive. These results indicate that the interaction between 2-octanone and phenol is greater than that of water and phenol. And as the temperature rises, b12 + b21 slightly increases, and it means that the interaction of 2-octanone and phenol decreases with the increasing of temperature. It also shows from another aspect that an increase in temperature is not conducive to the progress of the extraction. The regression of the NRTL model mentioned above only correlated the LLE data at a single temperature. The single temperature regression uses only two parameters bij and bji, and the regressed binary interaction parameters can only be used for the specified temperature. In order to predict the LLE data in the universal temperatures. Eq. (6) is modified as follows: τij ¼ Aij þ

Bij Bji ; τji ¼ Aji þ T T

ð10Þ

This regression was called as multiple temperature regression which correlates LLE data at all temperatures. The regression parameters are given in Table 6. The RMSD values are shown in Table 7 and were compared with RMSD values for single temperature regression. The mean RMSD of muti-temperature NRTL regression is closer to that of single temperature NRTL regression and the maximum RMSD value for the muti-temperature NRTL regression is 0.0049. The results demonstrate that the muti-temperature NRTL regression is also in good agreement with the experimental data. The biggest advantage of multitemperature regression is that its binary interaction parameters can predict values in the temperature range of 298.15 K to 338.15 K. 4. Conclusion

Fig. 4. Comparison of separation factor S of extracting phenol with different extractants at 298.15 K.

The liquid-liquid equilibrium data of 2-octanone + phenol + water ternary system at 298.15, 318.15 and 338.15 K under atmospheric pressure were experimentally determined. The extraction performance of 2octanone was evaluated by the distribution coefficient (D) and the separation factor (S). Compared with other solvents, the extraction

6

M. Jiang et al. / Journal of Molecular Liquids 300 (2020) 112323

Table 5 NRTL and UNIQUAC binary interaction parameters at different temperatures. T/K

298.15

318.15

338.15

Components

NRTL

i-j

bij/K

bji/K

αij

RMSD

bij/K

UNIQUAC bji/K

RMSD

1–2 1–3 2–3 1–2 1–3 2–3 1–2 1–3 2–3

337.97 397.67 −201.31 441.73 433.61 −268.26 561.29 429.40 −241.99

−598.64 2148.92 1607.09 −687.01 2323.48 1689.33 −789.56 2500.87 1657.08

0.3 0.2 0.2 0.3 0.2 0.2 0.3 0.2 0.2

0.0048

−331.99 −543.07 75.68 −364.48 −578.92 114.52 −399.44 −572.32 79.28

326.22 −136.29 −276.92 361.45 −151.62 −297.86 402.50 −168.46 −218.59

0.0042

Average

0.0039

0.0041

0.0043

0.0050

0.0065

0.0052

regression model parameters can be used as a basis for the design calculation of the phenol-containing wastewater extraction. CRediT authorship contribution statement Meiling Jiang:Conceptualization, Methodology, Writing - original draft.Shuai Shen:Data curation, Investigation, Validation.Yun Chen:Supervision, Resources, Writing - review & editing. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.molliq.2019.112323. References

Fig. 5. Plotting bij + bji vs. T.

Table 6 The binary interaction parameters of multiple temperature NRTL regression. i-j

Aij

Aji

Bij/K

Bji/K

αij

1–2 1–3 2–3

1.852 0.754 −1.115

−3.419 8.597 1.335

−152.116 179.285 117.072

399.682 −413.526 1228.431

0.3 0.2 0.2

performance of 2-octanone was excellent. The experimental data at each temperature were correlated using the NRTL and UNIQUAC models, and the binary interaction parameters could be regressed. After the physical meaning of the interaction parameters was analyzed, it was found that the interaction between 2-octanone and phenol is stronger than that of water and phenol in this study. The experimental data at all temperatures were regressed using a four-parameter NRTL model. The results show that both NRTL model and UNIQUAC model can correlate the experimental data well, and the RMSD between the calculated data and the experimental values is below 0.49%. The

Table 7 RMSD values for the ternary system of single temperature regression and multiple temperature regression by the NRTL model. T/K

Single temperature regression

Multiple temperature regression

298.15 318.15 338.15 Average

0.0048 0.0039 0.0041 0.0043

0.0049 0.0042 0.0041 0.0044

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