Solubility of Thiophene and Dibenzothiophene in Anhydrous FeCl3

Apr 8, 2014 - ACKNOWLEDGMENTS. The authors appreciate the financial support of The Research. Council and Sultan Qaboos University, Muscat Oman, ...
2 downloads 0 Views 706KB Size
Article pubs.acs.org/IECR

Solubility of Thiophene and Dibenzothiophene in Anhydrous FeCl3and ZnCl2‑Based Deep Eutectic Solvents Zaharaddeen S. Gano,† Farouq S. Mjalli,*,† Talal Al-Wahaibi,† Yahya Al-Wahaibi,† and Inas M. AlNashef‡ †

Petroleum and Chemical Engineering Department, Sultan Qaboos University, Al Khoudh, Muscat, 123, Sultanate of Oman Chemical Engineering Department, King Saud University, Riyadh 11421, Saudi Arabia



S Supporting Information *

ABSTRACT: The solubilities of some common refractory-sulfur-containing compounds, namely thiophene and dibenzothiophene, were studied and measured in anhydrous FeCl3- and ZnCl2-based deep eutectic solvents (DES) at different temperatures under atmospheric pressure. The aim of this study is to explore the behavior of DESs toward solvation of sulfurcontaining compounds so as to set a pace for the successful application of DESs into deep desulfurization of liquid fuels. The studied DESs were screened and prepared by the combination of anhydrous FeCl3 and ZnCl2 with different salts and hydrogen bond donors. High pressure liquid chromatography (HPLC) was employed for the quantitative measurements of solubilities of both thiophene and dibenzothiophene. It was found that FeCl3 based DESs exhibited higher solubilities (from 17 wt % to above 90 wt %) for dibenzothiophene as compared to the ZnCl2 based DESs (0.084−1.389 wt %). Moreover, FeCl3 based DESs exhibited complete miscibility with thiophene while ZnCl2 based DESs showed solubility values in the range of 1−10 wt % for thiophene. The experimental results obtained were further successfully modeled using the nonrandom two liquid (NRTL) model.

1. INTRODUCTION AND BACKGROUND Nowadays, it is widely accepted that sulfur compounds are undesirable in the refining processes as they tend to deactivate some catalysts used in crude oil processing and cause corrosion problems in pipeline, pumping, and refining equipment. In addition, naturally occurring sulfur compounds left in fuels lead to the emission of sulfur oxide gases. These gases react with water in the atmosphere to form sulfates and acid rain which damages buildings, destroys automotive paint finishes, acidifies soil, and ultimately leads to loss of forests and various other ecosystems.1 Moreover, sulfur emissions cause respiratory illnesses, aggravate heart disease, trigger asthma, and contribute to formation of atmospheric particulates.2 Consequently, governments all over the world are implementing stringent standards for the production of ultralow sulfur fuels from petrochemical industries. The EU legislation set the upper limit of sulfur content in diesel fuel to 10 ppm,3 and in 2010 the US Environmental Protection Agency (USEPA) reduced the SO2 emission limit to 140 ppb averaged over 24 h measurement.4 With these stringent environmental regulations in place, production of ultra-low-sulfur (ULS) fuels has become a major task for refineries and other petrochemical industries all over the world. Generally, hydrodesulphurization (HDS) is the commercial technology used in majority of refineries for the removal of sulfur from fuels.5 However, this technology requires high temperature, high pressure, and catalytic operations which make it costly for deep desulfurization applications. Moreover, hydrodesulfurization is not effective for removing refractive sulfur-containing compounds such as dibenzothiophene (DBT) and its derivatives, especially 4,6dimethyl-dibenzothiophene (4,6-DMDBT). Production of sulfur-free gasoline (97 >98 99 >99 >98 >99 >99 >99 HPLC HPLC >99 >98 >98 >98

ScPa Alfa Aesarb Alfa Aesar Aldrichc Aldrich Merckd Merck Merck Merck Fishere Merck Merck Aldrich Aldrich

a Surechem Products (ScP) limited, England. bAlfa Aesar (A John Matthey Company), Germany. cSigma-Aldrich, USA. dMerck Chemicals, Darmstadt Germany. eFisher Scientific, Loughborough UK.

Table 2. Summary of Synthesized DESs, Their Appearance at Room Temperature, Freezing Points, and Their Corresponding Abbreviations Used in This Work DES combination

molar ratio

FeCl3:[CH3(CH2)3]4PBr FeCl3:[CH3(CH2)3]4PBr FeCl3:C22H24PBr FeCl3:C22H24PBr FeCl3:C9H14NCl FeCl3:C9H14NCl FeCl3:[(C6H5)3C2H5]PBr FeCl3:[(C6H5)3C2H5]PBr FeCl3:C22H24PBr FeCl3:C22H24PBr FeCl3:C22H24PBr ZnCl2:HOCH2CH2OH ZnCl2:HOCH2CH2OH ZnCl2:HOCH2CH2OH ZnCl2:HOCH2CH2OH ZnCl2:(CH3CH2CH2CH2)4N(Br) ZnCl2:(CH3CH2CH2CH2)4N(Br) ZnCl2:(CH3CH2CH2CH2)4N(Br) ZnCl2:(CH3CH2CH2CH2)4N(Br) ZnCl2:(CH3CH2CH2CH2)4N(Br) ZnCl2:(CH3)3N(Br)C6H5 ZnCl2:(CH3)3N(Br)C6H5 ZnCl2:(CH3)3N(Br)C6H5 ZnCl2:(CH3)3N(Br)C6H5 ZnCl2:(CH3)3N(Br)C6H5 ZnCl2:C22H24PBr ZnCl2:C22H24PBr ZnCl2:C22H24PBr ZnCl2:C22H24PBr ZnCl2:C22H24PBr

1:2 1:1.5 1:1 1.5:1 1:2 1:1.5 1:2 1:1.5 1:3 1:2.5 1:2 1:3 1:4 1:5 1:6 1:2 1:1.5 1:1 1.5:1 2:1 1:2 1:1.5 1:1 1.5:1 2:1 1:2 1:1.5 1:1 1.5:1 2:1

appearance at room temperature homogenous dark brown solids homogeneous reddish brown solids brown solid mixtures

colorless liquids

white solid mixtures

freezing point (°C) 40.97 41.35 57.01 52.52

−24.73 −31.13 −24.43 −16.70

abbreviation DES1 DES2 DES3 DES4 DES5 DES6 DES7 DES8 DES9 DES10 DES11 DES12 DES13 DES14 DES15 DES16 DES17 DES18 DES19 DES20 DES21 DES22 DES23 DES24 DES25 DES26 DES27 DES28 DES29 DES30

DESs have found applications in various fields as reported by Zhang et al.15 Most of the DESs studied for the various applications have in most cases dallied around quaternary ammonium based DESs, especially choline chloride and its likes, with little attention paid to other quaternary salt based DESs, e.g. phosphonium. However, it has been reported that phosphonium based DESs are moisture stable and have shown

hydrogen bond donor (HBD) or a complexing agent which results in a liquid medium with a freezing point lower than the freezing points of the constituting compounds.15 DESs are advantageous in comparison to ILs because they are easily synthesized and their component salts are much cheaper than those of ILs. In addition, their components can be selected to be biodegradable and nontoxic.16 Depending on the nature of their component salts, DESs are generally moisture stable. 6816

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

2.3. Solubility Experiments. The conventional shake flask method of determining the equilibrium solubility of any solute in solvents at any given temperature, which is the most accurate method for solubility determination,21 was adopted for this work. In this method, the solute is added to the solvent and shaken for specified period of time usually determined by the nature of the systems under study. The saturation is reached and confirmed by observing the presence of undissolved solute in the solvent. In this work, a known mass and volume of DBT and thiophene were respectively added in excess to a known volume of the synthesized DESs in a test tube. The mixtures were shaken vigorously at a speed of 300−500 rpm and constant temperature for 48 h in a temperature controlled thermomixer (Cooling ThermoMixer MKR 13, with specifications shown in Table 3) to saturation. This was followed by 12 h settling time

promising performance in their application for the removal of glycerol from palm-oil-based biodiesel.17 Nevertheless, to the best of our knowledge, up to this moment, DESs have virtually little or no application in the field of deep desulfurization of liquid fuels. This could be due to among other facts, the deficiency in the knowledge of the behavior of DESs toward solvation of sulfur-containing compounds. But from the antecedents of the behavior of DESs in the field of extraction,18,19 much could be drawn and serve as a guide in further extending the application of DESs to the field of desulfurization of liquid fuels. In this work, the solubility of DBT and thiophene, some common refractive sulfur-containing compounds, were studied in anhydrous ferric chloride and zinc chloride based DESs at different temperatures. The main aim of the work is to explore the behavior of DESs toward solvation of sulfur-containing compound so as to set the pace in the application of DESs in the field of deep desulfurization of liquid fuels and further model the solubility results using thermodynamic and optimization technique.

Table 3. Thermomixer Specifications

2. EXPERIMENTAL METHODOLOGY As a general guide toward achieving good and reliable results in measuring the solubility in this work, three important factors were adhered to throughout the course of this work. First, it was ensured that both the solute and the solvent were of high purity because any small amount of impurities would affect the measured solubility. Second, it was also ensured that samples taken from the saturated solution contained no precipitated solute which could overestimate the measured solubility value, and finally, the temperature at which the solubility was measured was monitored and controlled. 2.1. Chemicals. Table 1 shows the list of chemicals used in this work, alongside their specifications and supplier. All chemicals were used without further purification except for the hygroscopic ones which were dried overnight in a vacuum oven prior to use. 2.2. Synthesis of DES and Freezing Point Determination. DES samples were synthesized with various combinations of salts and metal halides/hydrogen bond donor at different molar ratios as shown in Table 2. In the course of the synthesis, anhydrous ferric chloride and zinc chloride were mixed with various salts and hydrogen bond donors at different molar ratios, as shown in Table 2, in an incubator shaker (Brunswick Scientific Model INNOVA 40R) operated at 270 rpm and 80 °C for 2 h. The mixtures were shaken until a homogeneous solution was obtained with no visible precipitate.20 All DES samples were synthesized at atmospheric pressure and under tight control of moisture content and also kept in well-capped vials for storage in a moisture controlled desiccator. For each of the tests a DES would undergo, fresh samples were withdrawn from the stock vial to avoid any prior contamination/structural readjustment and to avoid humidity effects from the environment which may affect the results of the test. The freezing point of each of the DESs mentioned in Table 2 was determined by the differential scanning calorimetry (DSC) technique using a machine from TA Instruments (Q20 DSC) equipped with an RCS90 cooling accessory, and nitrogen gas (99.999% pure) was used as the purge gas at 50 mL/min flow rate.

parameter

specification

temperature work range temperature adjustable range accuracy/resolution maximum heating time maximum cooling time shaking frequency orbit dimensions (W × D × H) capacity weight (without block/blocks) electrical heating/cooling power electrical supply

−16 to +100 °C −10 to +105 °C ±0.1/0.1 °C 6.0 °C/min 12 °C/min 200−1500 rpm 3 mm orbital 220 × 330 × 144 mm 1 thermoblock 9 kg 130 W 115 V/230 V, 50−60 Hz

at the same temperature to allow for the settling of undissolved DBT in the mixture and thiophene emulsions formed in the matrix of the DESs. A known volume of the saturated solution was drawn from the matrix of the DESs for subsequent quantitative analysis with utmost care taken to ensure that no undissolved DBT and thiophene emulsions were drawn along with the saturated solution. Due to the fact that some of the DESs are solid at room temperature while others are liquid at room temperature, the selected range of temperatures for which the solubility experiments were carried out on the DESs was not the same. A temperature range of 65 to 90 °C in a 5 °C step interval was selected for those DESs whose melting temperature is above ambient (FeCl3-based DESs) while 30−90 °C in a 10 °C step interval was selected for those whose melting temperature is close to ambient or less (ZnCl2-based DESs). However, the same DESs samples were maintained in the analysis over the range of temperatures with additional DBT/thiophene added to those samples that have completely dissolved their initial content. This would ensure consistency in experimental results. 2.4. Chemical Analyses of Samples. For the quantitative solubility measurements, analyses were performed on an Agilent 1260 infinity series HPLC (HP1260 infinity, Agilent, USA) with detailed specifications shown in Table 4. The type of mobile phase used in the analysis varied for the different DESs studied. While HPLC grade methanol (100% v/v) gave a distinctive separation of peaks in the chromatograms of DES1− DES4, the same separation could not be achieved with DES12− DES15; instead, HPLC grade acetonitrile (100% v/v) was used and similar separation was achieved. Table 4 also shows the 6817

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

Table 4. HPLC Specifications and Experimental Conditions Specifications equipment model column detector pump autosampler

Agilent (1260 Infinity Series) reversed-phase ZORBAX extended C18, 4.6 × 150 mm, 5 μm variable wavelength detector (VWD) quaternary pump equipped Experimental Conditions

for the DES1−DES4 systems

for the DES12−DES15 systems

mobile phase: methanol at 1 mL/min injection volume: 1 μL column temperature: 35 °C detection wavelength: 234 nm6 R2: 0.99978 mobile phase: acetonitrile at 1 mL/min injection volume: 1 μL column temperature: 30 °C detection wavelength: 280 nm6 R2: 0.99969

Figure 1. Experimental and predicted solubility profiles of thiophene in DES12 and DES13.

conditions of experimental methods used in performing the HPLC analyses alongside the correlation coefficient obtained in the calibration of each method. Most of the time, drawn solutions contain solute concentration beyond the range of the HPLC method calibrations performed. In such situations, sample dilutions were performed with a suitable solvent in order to lower the solute concentrations to within the calibration range for better accuracy in the solute quantification. However, these dilutions were eventually accounted for in the process of evaluating the actual solute concentrations in each sample.

achievable extraction level of sulfur containing compounds but also drastically reduce the costs associated with desulfurization processes. While some of the DESs studied in this work showed partial miscibility with thiophene at all temperatures, others showed complete miscibility at all studied temperatures, thus warranting no further analysis on them. Among the studied DESs, ZnCl2 containing DESs (DES12−DES15) showed partial miscibility with thiophene. Figures 1 and 2 show the solubility profile of thiophene in these DESs. From these figures, it could be seen that the solubility of thiophene increased with increasing temperature in all the DESs. Although the effect of salt and HBD ratio is expected to affect the solubility of thiophene in the DESs at any given temperature,22 a distinctive trend as to that effect could not be established in these systems. For example, at 30 °C, DES15, with 85.71 mol % ethylene glycol as HBD, exhibited the lowest solubility value of 1.384 wt % thiophene followed by DES13 and DES12 with DES14 having the highest value of 1.977 wt %. This trend was not observed at

3. RESULTS AND DISCUSSIONS The behavior of solute in a solvent goes to a great extent in affecting the achievable extraction level of that solute by the solvent from a given mixture. A good understanding of the behavior of sulfur containing compounds and solvents combined with the tailorable properties of DESs could lead to the design of systems that would not only improve the 6818

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

Figure 2. Experimental and predicted solubility profiles of thiophene in DES14 and DES15.

higher temperatures, where DES15 exhibited the highest solubility values than its counterparts. However, all FeCl3 containing DESs (DES1−DES4) exhibited complete miscibility with thiophene at the onset of their temperatures of experiments. For the case of DBT, Figures 3 and 4 show its solubility profiles in DES1−DES4, while Figures 5 and 6 show its

Figure 4. Experimental and predicted solubility profiles of DBT in DES3 and DES4.

those obtained with thiophene in Figures 1 and 2. For example, at 30 and 80 °C, DES14 showed a solubility of 1.977 and 8.002 wt % for thiophene while the same DES14 showed a solubility value of 0.097 and 0.919 wt % for DBT at the same temperatures of 30 and 80 °C, respectively. These values clearly show that thiophene is more soluble in ZnCl2-based DESs than DBT and this could be attributed to the differences in their molar masses and structural coordination. Figures 3 and 4 also show much higher solubility values for DBT when compared with Figures 5 and 6. Moreover, the complete miscibility of DES1−DES4 with thiophene in comparison with the lower solubility values of thiophene in DES12−DES15 all indicate that there exist a stronger interaction between the Fe atom in DES1−DES4 and the S atom in the thiophene and DBT compounds than in Zn in

Figure 3. Experimental and predicted solubility profiles of DBT in DES1 and DES2.

solubility profiles in DES12−DES15, respectively. The trend observed from Figures 3 and 4 shows that the solubility increased with increasing temperature for DES1 and DES2 but started increasing from 65 °C, reached a maximum at 75 and 80 °C for DES3 and DES4, respectively, and later dropped at temperatures of 85 and 90 °C. However, Figures 5 and 6 show that the solubility generally increased with increasing temperature for all the DESs but with lesser values when compared to 6819

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

3.1. Modeling Solubility Data. The basic equation for predicting the saturation mole fraction of a solute in a solvent is given by eq 1:21,24,25 ln(x1γ1) = − −

ΔH̲ fus(Tm) ⎡ T ⎤ ⎥ ⎢1 − RT Tm ⎦ ⎣ 1 RT

∫T

T

ΔCp dT +

m

1 R

∫T

T

m

ΔCp T

dT

(1)

The subscript 1 denotes the solute, x1 and γ1 are its molar composition (solubility at equilibrium) and activity coefficient in the mixture, respectively, Tm is the melting point temperature of the solute, T is the temperature of the system at equilibrium, and ΔHfus and ΔCp are the enthalpy and heat capacity changes from the solid to the liquid state of the solute. Without introducing appreciable error, it can be assumed that ΔCp is independent of temperature. So, eq 1 becomes

Figure 5. Experimental and predicted solubility profiles of DBT in DES12 and DES13.

⎧ ΔH̲ fus(T ) ⎡ T ⎤ ΔCp m ln(x1γ1) = −⎨ ⎥− ⎢1 − RT Tm ⎦ RT ⎣ ⎩ ⎪



⎡ ⎛ T ⎞⎤⎫ Tm + ln⎜ m ⎟⎥⎬ ⎢1 − ⎝ T ⎠⎦⎭ ⎣ T ⎪



(2)

This equation can be used based on the assumption of simple eutectic mixtures with complete miscibility in the liquid and immiscibility in the solid phases. Because of their close values, it is safe to assume that for most solid species, the melting point temperature (Tm) is equal to the triple point temperature (Tr). Hence Tm can be replaced by Tr. Then, eq 2 will be then written as ⎧ ΔH̲ fus(T ) ⎡ T ⎤ ΔCp r ln x1 = −ln γ1 − ⎨ ⎢1 − ⎥ − Tr ⎦ RT ⎩ RT ⎣ ⎪



⎡ ⎛ T ⎞⎤⎫ Tr + ln⎜ r ⎟⎥⎬ ⎢1 − ⎝ T ⎠⎦⎭ ⎣ T



Figure 6. Experimental and predicted solubility profiles of DBT in DES14 and DES15.



(3)

If the liquid mixture is ideal, γ1 = 1 and the solubility can be computed from the thermodynamic data (ΔH̲ fus and ΔCp) for the solid species near the melting point. For nonideal solutions, γ1 must be estimated from either experimental data or liquid solution models, like the nonrandom two liquid (NRTL) or UNIFAC models. A similar modeling approach has been adopted for other solubility measurements data.21,26 The NRTL model27 was used to calculate the activity coefficient at equilibrium. The NRTL model predicts the activity coefficient as a function of three parameters, τij, τji, and αij, for each pair of components in the multicomponent mixture. The general NRTL model is given in eq 4.

DES12−DES15, thus increasing the solubility of the sulfuric compounds significantly.23 Due to the observed nature of the curves for DES3 and DES4, the experiments were repeated with extra caution and similar results were obtained, thus ruling out the doubt of false results from erroneous experiments. A possible explanation to this phenomenon suggests that the initial rise in solubility values for these DESs was as a result of the dominating interaction between the sulfuric compounds and the Lewis acid donor present in the DESs (FeCl3-based) over that between the sulfuric compounds and the salt (C22H24PBr). These interactions are perceived to go in opposite directions to each other due to the presence of Br which serves as the Lewis base donor in the formation of the DES. As the temperature increased, the interaction from the side of Lewis acid donor in the DESs became weakened and overtaken by the interaction from the side of the salt, which consequently gave rise to the sudden drop in the measured solubility values. It should be noted that the standard uncertainty in mass, temperature measurements (u), and relative standard uncertainty in solubility measurements (ur) are 0.001 g, 0.5 °C, and 0.07 wt %, respectively.

ln γi =

ΣjτjiGjixj ΣjGjixj

+

∑ j

Gijxj ⎛ Στ G x ⎞ ⎜⎜τij − k kj kj k ⎟⎟ ΣkGkjxk ⎠ ΣkGkjxk ⎝

(4)

with Gij = exp(−αijτij), αij = αji, τii = 0. The values of α12 and α21 were assumed to be equal. Thus, for a binary system like the one considered in this work, eq 4 reduces to eq 5: ⎞ ⎛ ⎛ ⎞2 G21 τ12G12 ⎟ ln γ1 = x 2 2⎜⎜τ21⎜ ⎟ + 2⎟ x x G + x x G ( + ) ⎠ ⎝ 1 2 21 2 1 12 ⎠ ⎝ 6820

(5)

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

The binary interaction parameters (τij and τji) are functions of temperature. This relationship can be expressed as a linear temperature dependent relation using the correlation in eq 6: tij = tij 0 + tijT(T − 273.15)

an optimization method based on the genetic algorithm (GA).30−32 An evolution based optimization algorithm like the GA was used in order to avoid the problem of divergence due to improper initial guesses for the model parameters solution vector. The GA implementation used in this work is the augmented Lagrangian genetic algorithm (ALGA).33 The Matlab optimization toolbox was used to code and solve the problem.32 The basic implementation of the GA starts by creating a random initial population. New sequences of populations are then created iteratively. Individuals are scored and scaled based on the problem fitness function. Best individuals having lower fitness are passed to the next population. A mutation (making random changes to a single parent) or crossover (combining the vector entries of a pair of parents) technique is used to evolve children individuals. The newly generated children will form the new population by replacing the current one. This evolution approach is repeated until the objective function is satisfied. The diversity of the population was selected by defining an initial range of [−1 10] which gives good search performance for the problem in hand. A population size of 5 (same as number of NRTL model parameters) was used, and a crossover fraction of 0.6 was selected for all optimization runs. The parameter estimation was carried out by minimizing an objective function value given in eq 7, which minimizes the deviation between the experimental and calculated solubility weight fractions of the two components.

(6)

With the introduction of and a total of five model parameters need to be evaluated for each experiment. For the systems under consideration, the solvents represented by the different DESs were assumed to be of complete miscibility in the liquid phase while immiscible in the solid phase. Heat capacity data for DBT and thiophene were used from the literature.28,29 The graphs representing Cp as a function of temperature for DBT and thiophene are shown in Figures 7 and 8, respectively. The difference in the heat tij0

tijT,

2⎞ ⎛ ⎡ exp (S − Sk pred) ⎤ ⎟ ⎥ minimize⎜⎜∑ ⎢ k ⎢ ⎥⎦ ⎟ Sk exp ⎝ k ⎣ ⎠

Figure 7. Heat capacity as a function of temperature for DBT. Data taken from ref 28.

(7)

Subject to parameter bounds −100 ≤ τ12 0 ≤ 1000, −100 ≤ τ12T ≤ 10 −100 ≤ τ210 ≤ 1000, −100 ≤ τ21T ≤ 10, 0.2 ≤ α ≤ 0.47

Where, Skexp = experimental solubility, Skpred = predicted solubility, and k = counter representing temperatures (30, 40, 50, 60, 70, 80, 90 °C). The binary interaction parameters, predicted solubility results, and the average relative errors (ARE) between the experimental and predicted solubility results for each of the set of DESs are summarized in Supporting Information Tables 5− 13. The AREs for all NRTL predictions were calculated based on eq 8. ARE =

Figure 8. Heat capacity as a function of temperature for thiophene. Data taken from ref 29.

S exp − Spred S exp

(8)

The average AREs values for the thiophene solubility predictions for the ZnCl2-based DESs (DES12−DES15) were 0.0222, 0.0533, 0.0382, and 0.1428, respectively. On the other hand, the average AREs values for the DBT prediction for the same DESs were 0.1097, 0.0652, 0.0472, and 0.1144, respectively. In general the NRTL predictions for these DESs are of high quality. The DBT solubility predictions for the FeCl3-based DESs (DES1−DES4) attained average AREs of 0.0032, 0.0163, 0.0008, and 0.0031, respectively. Despite the low AREs in all cases, these indicators show that the NRTL is more capable for predicting the DBT solubility than that for thiophene.

capacities of the solute in the solid and liquid states (ΔCp) can be estimated from the data. The value of ΔCp/R is estimated to be 4.1806 and 3.278 for DBT and thiophene, respectively. The latent heat of fusion of these compounds in their pure states and their corresponding melting temperatures are, for DBT, ΔH̲ fus = 21.728 kJ/mol and Tm = 371.821 K and, for thiophene, ΔH̲ fus = 5.086 kJ/mol and Tm = 234.95 K.28,29 The binary interaction parameters were estimated from the N experimental data points at each temperature for each of thiophene with DESs 12−15 and DBT for DESs 1−4 and DESs 12−15, respectively. These parameters were determined using 6821

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

(9) Dharaskar, S. A.; Wasewar, K. L.; Varma, M. N.; Shende, D. Z. Extractive Deep Desulfurization of Liquid Fuels Using Lewis-Based Ionic Liquids. J. Energy 2013, 581723, 1−4. (10) Bosmann, A.; Datsevich, L.; Jess, A.; Lauter, A.; Schmitz, C.; Wasserscheid, P. Deep desulfurization of diesel fuel by extraction with ionic liquids. Chem. Commun. 2001, 2494−2495. (11) Diallo, A. O.; Len, C.; Morgan, A. B.; Marlair, G. Revisiting physico-chemical hazards of ionic liquids. Sep. Purif. Technol. 2012, 97, 228−234. (12) Abbott, A. P.; Boothby, D.; Capper, G.; Davies, D. L.; Rasheed, R. K. Deep Eutectic Solvents Formed between Choline Chloride and Carboxylic Acids: Versatile Alternatives to Ionic Liquids. J. Am. Chem. Soc. 2004, 126, 9142−9147. (13) Kareem, M. A.; Mjalli, S. F.; Hasheem, A. M.; AlNashef, I. M. Phosphonium-Based Ionic Liquids Analogues and Their Physical Properties. J. Chem. Eng. Data 2010, 55, 4632−4637. (14) Abbott, A. P.; Capper, G.; Davies, D. L.; Rasheed, R. K.; Tambyrajah, V. Novel solvent properties of choline chloride/urea mixtures. Chem. Commun. 2003, 70−71. (15) Zhang, Q.; Vigier, K. D. O.; Royer, S.; Jerome, F. Deep eutectic solvent: syntheses, properties and applications. Chem. Soc. Rev. 2012, 41, 7108−7146. (16) Hayyan, M.; Hashim, M. A.; Hayyan, A.; Al-Saadi, M. A.; AlNashef, I. M.; Mirghani, M. S.; Saheed, O. K. Short Communication: Are deep eutectic solvents benign or toxic? Chemosphere 2013, 90, 2193−2195. (17) Shahbaz, K.; Mjalli, F. S.; Hashim, M. A.; AlNashef, I. M. Using Deep Eutectic Solvents Based on Methyl Triphenyl Phosphunium Bromide for the Removal of Glycerol from Palm-Oil-Based Biodiesel. Energy Fuels 2011, 25, 2671−2678. (18) Abbott, A. P.; Cullis, P. M.; Gibson, M. J.; Harris, R. C.; Raven, E. Extraction of glycerol from biodiesel into a eutectic based ionic liquid. Green Chem. 2007, 9, 868−872. (19) Hayyan, M.; Mjalli, F. S.; Hashim, M. A.; AlNashef, I. M. A novel technique for separating glycerine from palm oil-based biodiesel using ionic liquids. Fuel Process. Technol. 2010, 91, 116−120. (20) Hayyan, A.; Mjalli, F. S.; AlNashef, I. M.; Al-Wahaibi, T.; AlWahaibi, Y. M.; Hashim, M. A. Fruit sugar-based deep eutectic solvents and their physical properties. Thermochem. Acta 2012, 541, 70−75. (21) Bagh, F. S. G.; Mjalli, F. S.; Hashim, M. A.; Hadj-Kali, M. K. O.; AlNashef, I. M. Solubility of Sodium Salts in Ammonium-Based Deep Eutectic Solvents. J. Chem. Eng. Data 2013, 58 (8), 2154−2162. (22) Li, F.-t.; Liu, R.-h.; Wen, J.-h.; Zhao, D.-s.; Sun, Z.-m.; Liu, Y. Desulfurization of dibenzothiophene by chemical oxidation and solvent extraction with Me3NCH2C6H5Cl·2ZnCl2 ionic liquid. Green Chem. 2009, 11, 883−888. (23) Ko, N. H.; Lee, J. S.; Huh, E. S.; Lee, H.; Jung, K. D.; Kim, H. S.; Cheong, M. Extractive Desulfurization Using Fe-Containing Ionic Liquids. Energy Fuels 2008, 22, 1687−1690. (24) Prausnitz, J. M.; Lichtenthaler, R. N.; de Azevedo, E. G. Molecular Thermodynamics of Fluid-Phase Equilibria; Prentice Hall International: Englewood Cliffs, NJ, 1999. (25) Sandler, S. L. Chemical and Engineering Thermodynamics; John Wiley & Sons: New York, 1999. (26) Bagh, F. S. G.; Mjalli, F. S.; Hashim, M. A.; Hadj-Kali, M. K. O.; AlNashef, I. M. Solubility of Sodium Chloride in Ionic Liquids. Ind. Eng. Chem. Res. 2013, 52 (33), 11488−11493. (27) Renon, H.; Prausnitz, J. M. Local compositions in thermodynamic excess functions for liquid mixtures. AIChE J. 1968, 14 (3), 135−144. (28) Chirico, R. D.; Knipmeyer, S. E.; Nguyen, a.; Steele, w. V. The thermodynamic properties of dibenzothiophene. J. Chem. Thermodyn. 1991, 23, 431−450. (29) Waddington, G.; Knowlton, J. W.; Scott, D. W.; Oliver, G. D.; Todd, S. S.; Hubbard, W. N.; Smith, J. C.; Huffman, H. M. Thermodynamic Properties of Thiophene. J. Am. Chem. Soc. 1949, 71 (3), 797−808.

4.0. CONCLUSIONS The solubilities of thiophene and dibenzothiophene were studied and measured in anhydrous FeCl3- and ZnCl2-based DESs for different combinations of salt to HBD/Lewis acid donor at different temperatures under atmospheric pressure. In most cases, it was found that the solubility of both thiophene and DBT increased with increasing temperature. It was also found that FeCl3-based DESs showed complete miscibility with thiophene and much higher solubility for DBT when compared to their ZnCl2-based counterparts. Similarly, thiophene had higher solubility than DBT in the ZnCl2-based DESs. These results clearly indicate that the chemical nature and structure of DESs affect to a large extent their ability to dissolve sulfuric compounds. In this regard, FeCl3-based DESs showed higher solubilities as compared to their ZnCl2-based counterparts, thus implying that FeCl3-based DESs are potential candidates as solvents for deep desulfurization of liquid fuels. The experimental solubility results have been successfully modeled with NRTL thermodynamic model, and the modeled results show a satisfactory match between the two.



ASSOCIATED CONTENT

S Supporting Information *

Detailed modeling results alongside their calculated absolute relative errors (AREs). This material is available free of charge via the Internet at http://pubs.acs.org.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The authors appreciate the financial support of The Research Council and Sultan Qaboos University, Muscat Oman, under the project RC/ENG/PCED/12/02.



REFERENCES

(1) Smith, R. Chemical Process Design and Integration; John Wiley and Sons: West Sussex, 2005. (2) USEPA. National Air Quality; status and trend through 2007; United States Environmental Protection Agency: North Carolina, 2008. (3) Kulkarni, P. S.; Afonso, C. A. M. Deep desulfurization of diesel fuel using ionic liquids: current status and future challenges: Critical Review. Green Chem. 2010, 12, 1139−1149. (4) Broder, J. M. E.P.A. Tightens Sulfur Dioxide Limits. The New York Times, June 3, 2010, p A18. (5) Zhang, H.; Gao, J.; Meng, H.; Li, C.-X. Removal of Thiophenic Sulfurs Using an Extractive Oxidative Desulfurization Process with Three New Phosphotungstate Catalysts. Ind. Eng. Chem. Res. 2012, 51, 6658−6665. (6) Gao, H.; Luo, M.; Xin, J.; Wu, Y.; Li, Y.; Li, W.; Liu, Q.; Liu, H. Desulfurization of Fuel by Extraction with Pyridinium-Based Ionic Liquids. Ind. Eng. Chem. Res. 2008, 23 (5), 8384−8388. (7) Nie, Y.; Li, C.-X.; Wang, Z.-H. Extractive Desulfurization of Fuel Oil Using Alkylimidazole and Its Mixture with Dialkylphosphate Ionic Liquids. Ind. Eng. Chem. Res. 2007, 46, 5108−5112. (8) Gao, H.; Xing, J.; Li, Y.; Li, W.; Liu, Q.; Liu, H. Desulfurization of Diesel Fuel by Extraction with Lewis-Acidic Ionic Liquid. Sep. Sci. Technol. 2009, 44, 971−982. 6822

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823

Industrial & Engineering Chemistry Research

Article

(30) Storn, R.; Price, K. Differential Evolution−A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces. J. Global Optim. 1997, 11, 341−359. (31) Gujarathi, A. M.; Babu, B. V. Improved Multiobjective Differential Evolution (MODE) Approach for Purified Terephthalic Acid (PTA) Oxidation Process. Mater. Manuf. Process. 2009, 24, 303− 319. (32) Coleman, T.; Branch, M. A.; Grace, A. Optimization Toolbox for use with MATLAB−User Guide; The Math Works Inc.: Natick, MA, 1999. (33) Conn, A. R.; Gould, N.; Toint, P. L. A Globally Convergent Augmented Lagrangian Barrier Algorithm for Optimization with General Inequality Constraints and Simple Bound. Math. Comput. 1997, 66 (217), 261−288.

6823

dx.doi.org/10.1021/ie500466g | Ind. Eng. Chem. Res. 2014, 53, 6815−6823