Thermodynamic Study of Binary Mixtures of 1-Butyl-1

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Thermodynamic Study of Binary Mixtures of 1-Butyl-1-Methylpyrrolidinium Dicyanamide Ionic Liquid with Molecular Solvents - New Experimental Data and Modeling with PC-SAFT Equation of State Kamil Paduszy#ski, Elena Vadimovna Lukoshko, Marek Królikowski, Urszula Maria Domanska, and Jerzy Szydlowski J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/jp511621j • Publication Date (Web): 16 Dec 2014 Downloaded from http://pubs.acs.org on December 26, 2014

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The Journal of Physical Chemistry

Thermodynamic Study of Binary Mixtures of 1-Butyl-1-Methylpyrrolidinium Dicyanamide Ionic Liquid with Molecular Solvents – New Experimental Data and Modeling with PC-SAFT Equation of State ∗,† Elena Vadimovna Lukoshko,† Marek Królikowski,† Urszula ´ Kamil Paduszynski, † and Jerzy Szydłowski‡ ´ Domanska,

Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland, and ˙ Faculty of Chemistry, University of Warsaw, Zwirki i Wigury 101, 02-089 Warsaw, Poland E-mail: [email protected]

KEYWORDS: Ionic liquids, Liquid-Liquid Equilibrium, Excess Enthalpy, PC-SAFT

∗ To

whom correspondence should be addressed University of Technology ‡ University of Warsaw † Warsaw

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Abstract This paper is concerned with thermodynamic properties of binary mixtures composed of 1-butyl-1-methylpyrrolidinium dicyanamide ionic liquid (IL) and the following molecular solvents: n-heptane, benzene, toluene, ethylbenzene, thiophene, 1-butanol, 1-hexanol and 1-octanol. This is the very first time, when experimental data on liquid-liquid equilibrium (LLE) phase diagrams and excess enthalpies of mixing (H E ) for these systems are reported. An impact of the molecular solvent structure on LLE and H E is discussed. Furthermore, modeling of the properties under study is presented by using perturbed-chain statistical associating fluid theory (PC-SAFT). The equation of state is used in purely predictive and semi-predictive mode. The latter one involve temperature-dependent binary corrections to combining rules employed in the PC-SAFT model determined on the basis on infinite dilution activity coefficients. The results shown indicate that such an approach can serve as an interesting modern thermodynamic tool for representation of thermodynamic data for complex ILs-based systems.


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Introduction Nowadays, the term “ionic liquids” (commonly abbreviated by ILs) is commonly assigned to organic molten salts. 1 The compounds classified as ILs are usually based on a large, asymmetric, quaternized and/or functionalized organic cation derived from aliphatic or aromatic amine, accompanied by inorganic/organic anion, which is in most cases smaller than cation and exhibits higher degree of symmetry. It has been turned out that such cation-anion combinations may result in salts having relatively low melting temperature at normal pressure. Besides an experimental evidence of this fact, the phenomenon was nicely explained by Krossing and co-workers. 2 On the basis of some simple thermochemical consideration they showed that common ILs (i.e. those incorporating 1,3dialkylimidazolium, 1,1-dialkylpyrrolidinium and tertaalkylammonium cations) are characterized by negative value of fusion Gibbs energy at room temperature, thus thermodynamically instable solid phase. 2 Since the beginning of 1990s ILs have been an object of numerous investigations, including theoretical and experimental ones. 3–8 Most of the studies have been focused on elucidating mutual relationship between molecular characteristics of ions (like symmetry, kind of heteroatoms, aromaticity, size/type of task-specific functional groups attached to the cation core or anion) and different properties observed by means of direct or indirect measurements. In particular, a vast amount of phase equilibrium data for binary and ternary {IL + molecular solvent(s)} systems have been reported so far, including vapor-liquid equilibria (VLE), vapor-liquid-liquid equilibria (VLLE), liquid-liquid equilibria (LLE), solid-liquid equilibria (SLE) and solid-liquid-liquid equilibria (SLLE). Besides, infinite dilution activity coefficients of various molecular compounds in ILs (γ∞ ) and excess enthalpies of mixing (H E ) data have been intensively measured and published in the last two and a half decades. A comprehensive summary of a large part of experimental data published in open literature can be found in ILThermo database project by NIST available online at http://ilthermo.boulder.nist.gov/. What is considerably important, all these thermodynamic data can give some physical insight into mutual structure-property relationships in the system under consideration. For example, conclusions on the strength of molecular interactions IL-solute can be 3 ACS Paragon Plus Environment


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drawn on the basis of either activity coefficients derived from phase equilibrium data or γ∞ values, or the sign and magnitude of H E . Apart from their unquestionable value for fundamental studies of solutions, the data are essential from the purely utilitarian point of view. In fact, design and optimization procedures for material and energy balances in chemical technology and engineering requires some thermodynamic knowledge of phase behavior of mixtures considered at any stage of a given chemical plant process, e.g. separation units involving extraction requires at least accurate LLE data preferably at wide range of temperature, while those units emplying extraction distillation use VLE and VLLE data. Measuring and accessing the thermodynamic data for ILs and their systems is particularly important, because ILs have been seriously considered as “green” media for modern and sustainable chemical engineering, in particular clean and environmentally friendly separations. 9 This is due to their interesting and unique properties like non-volatility 10 (normal boiling point of any IL is a non-measurable property; vapor pressure at the level of 10−5 bar at T ≈ 500 K), a wide liquid range and good thermal stability and other properties that can be easily tuned depending on particular tasks and applications. Nevertheless, the feature of ILs which makes those chemicals so attractive for separations is that they can dissolve a great variety of materials ranging from greenhouse gases 8 and inorganic salts 11 to small biomolecules, 12 pharmaceuticals 13 and renewable biomass feedstocks. 14–16 Besides numerous reports on the experimental data for {IL + molecular solvents} mixtures, a huge amount of work have been done in the field of modeling of these systems by using a great variety of theoretical and computational tools. Besides physically founded computer simulations 17,18 and quantum-chemical models like COSMO-RS, 19–21 several tools rooted in thermodynamics have been applied to model phase equilibria of ILs-based systems, varying from simple correlative activity coefficients models like non-random two-liquid (NRTL) model, or universal quasi-chemical approach (UNIQUAC), 22 or universal functional groups activity coefficients (UNIFAC) 23 to more sophisticated molecular-based equations of state allowing to obtain more general thermodynamic description as well as displaying enhanced predictive capacity. Lattice theory-based models like non-random hydrogen-bond (NRHB), 24,25 “cubic + association” (CPA) model 26 and statistical as-


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sociating fluid theory (SAFT) are the most comprehensively studied approaches of this kind. In particular, different versions of SAFT methodology have recently become very popular tools for modeling phase equilibria and derived properties of systems involving ILs: perturbed-chain SAFT (PC-SAFT), 24,25,27–34 soft-SAFT, 35–42 generalized SAFT + Cubic. 43 Nevertheless, only the PCSAFT and soft-SAFT seem to be models that have attracted most of the attention of ILs community. Since this paper deals with PC-SAFT we briefly review some recent contributions concerned only with this model. Details on the applications of the remaining versions of SAFT can be found in the original papers cited. An interested reader is also referred to excellent review papers published recently. 26,44 In last few years our group carried out a systematic study of applications of PC-SAFT to ionic liquid systems. We used PC-SAFT model to reproduce phase diagrams and other relevant thermodynamic properties (γ∞ and H E ) for diverse binary systems composed of ILs based on imidazolium, pyridinium, quinolinium, pyrrolidinium and piperidinium cations and different anions, mainly bistriflamide, in literature commonly denoted by [NTf2 ]. 24,25,27–31 Across the pages of this journal, in 2012 we reported a novel PC-SAFT-UNIFAC methodology, which combines advantages of both PC-SAFT equation of state and modified UNIFAC (Dortmund) activity coefficient model. In 2013, we published two papers 30,31 demonstrating that PC-SAFT may serve as an effective tool for solubility calculations in extremely complex “sweet-in-green” biorefinery systems {IL + mono- or disaccharide, or sugar alcohol}. We showed that the model is capable of capturing phase behavior of pure ILs accurately as well as it predicts an impact of both cation and anion structure on solubility. Similar investigations have been performed simultaneously (concurrently) by the collaborative group of Sadowski and Macedo, 33,34 who additionally used the PC-SAFT model to reproduce volumetric properties of {IL + sugar} systems. 34 Furthermore, the PC-SAFT was also employed in the calculations reported recently by Mutelet et al. 45,46 These authors applied this methodology to represent binary VLE data for {IL + CO2 , thiophene, pyridine, toluene, water} systems, relevant from the point of view of key ILs applications, i.e. CO2 capture and gasoline desulfurization. Furthermore, very interesting papers on PC-SAFT applications for {IL +



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water} mixtures was published very recently. 32,47 This paper is a continuation of our systematic study of ILs based on perfluoroalkylphospates as well as cyano-group containing anions. In previous contributions, comprehensive thermodynamic study on tris(pentafluoroethyl)trifluorophosphates ([FAP]), 48–50 tricyanomethanides ([C(CN)3 ]), 49,51,52 and tetracyanoborates ([B(CN)4 ]) 49,53 was presented. In this contribution, the thermodynamic study is presented for 1-butyl-1-methylpyrrolidinium dicyanamide IL, henceforth referred to as [C4 C1 Pyr][N(CN)2 ]. New sets of data are reported for this IL mixed with common organic solvents: n-heptane, benzene, toluene, ethylbenzene, thiophene, 1-butanol, 1-hexanol and 1-octanol. The data reported in this work comprise ambient pressure LLE phase diagrams for systems with hydrocarbons and thiophene and H E for systems with benzene, thiophene and alcohols at T = 298.15 K. Besides being a source of some physical insight into IL-solute molecular interactions, the data may be particularly useful in evaluation of the studied IL in aliphatic/aromatic extractions as well as in gasoline desulfurization process. Analysis of all the considered systems and properties is also provided as thermodynamic modeling in terms of molecular-based PC-SAFT equation of state.

Experimental Procedures Materials The IL, namely, 1-butyl-1-methylpyrrolidinium dicyanamide ([C4 C1 Pyr][N(CN)2 ]; mass fraction purity ≥ 0.98; CAS registry number 370865-80-8), was purchased from IoLiTec (Ionic Liquids Technologies GmbH, Germany). Chemical structure of the studied IL is shown in Figure 1. Before the measurements the sample of IL was degassed and dried by applying vacuum at moderate temperature T = 323 K for 48 h. The other chemicals used are as follows: n-heptane (supplied by Avantor Performance Materials; CAS registry number 142-82-5; mass fraction purity 0.99), benzene (Avantor Performance Materials; 71-43-2; 0.997), toluene (Sigma Aldrich; 71-36-3; 0.995), ethylbenzene (Avantor Performance Materials; 100-41-4; 0.998), thiophene (Acros Organics; 1106 ACS Paragon Plus Environment

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02-1; 0.99), 1-butanol (Sigma Aldrich; 71-36-3; 0.995), 1-hexanol (Sigma Aldrich; 111-27-3; 0.99), 1-octanol (Sigma Aldrich; 111-87-5; 0.99). All solvents were fractionally distilled over different drying reagents to mass fraction purity better than 0.998 and were stored over freshly activated molecular sieves of type 4A (Union Carbide). All compounds were checked by GLC analysis and Karl Fischer (KF) titration. No significant impurities were found. KF analysis showed that the water mass fraction in the IL were below 200 × 10−6 .

Figure 1: The chemical structure of the studied IL: 1-butyl-1-methylpyrrolidinium dicyanamide, [C4 C1 Pyr][N(CN)2 ].

Liquid-Liquid Equilibria (LLE) Phase diagrams were determined using visual cloud-point method based on appearance of turbidity in slowly cooled solution. All samples have been prepared gravimetrically in special, very tight glass cell equipped with Rotaflow needle valve at atmospheric pressure. Uncertainty in the mole fraction composition was better than ±0.0005. The cells were immersed in appropriate bath in mixture of ethylene glycol with water, or in glycerol or in oil bath. Mixtures were stirrer and heated. All mixtures were heating about 5 K above the expected phase transition temperature to obtain homogenous system. After about 10 min of thermostating, the system was cooling slowly (with a rate about 0.1 K · min−1), until turbidity of solution appeared or disappeared depending 7 ACS Paragon Plus Environment


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on the LLE phase behavior. The measurements were repeated at least three times so the overall uncertainty is no more than 0.1 K. The repeatability of the LLE experimental points was ±0.2 K.

Excess Enthalpy of Mixing (H E ) Excess enthalpies of mixing (H E ) for {[C4 C1 Pyr][N(CN)2 ] (1) + molecular solvent (2)} solutions were determined according to procedures similar to those described by us previously. 28 Thermal activity monitor (TAM) III calorimeter (TA Instruments, USA), employing technique called isothermal titration calorimetry (ITC), was used. The titration cell and the reference cell were placed in the test wells of the highly stable thermostatic oil bath of volume 22 L. Before the experiment, the temperature of the oil bath was maintained at desired temperature (in this case T = 298.15 K) for 24 hours with a stability of ±100 µK. Two modes of titration were performed during the experiments. Solvent-to-IL titration experiments were started from placing about 0.4 mL of pure IL in the stainless steel titration cell following by placing it in the thermostatic oil bath and equilibration for a few hours. Depending on the change in mole fraction of IL, (2–15) ± 0.001 µL of solvent was injected into the titration cell using the precise syringe pump provided by the manufacturer of the calorimeter. During the titration the mixture was rigorously stirred with the maximum stirring speed of 100 rpm. The molar amount (required to calculate mole fraction of solution) of the titrant fluid was calculated on the basis of the volume with the known density of solvent, determined in our laboratory directly prior the measurements by using vibrating tube densimeter (Anton Paar GmbH 4500), with an accuracy of density of ±10−4 g · mL−1 at T = 298.15 ± 0.01 K. The measured densities (g · mL−1 ) were: 0.87361 for benzene, 1.05846 for thiophene, 0.80571 for 1-butanol, 0.81514 for 1-hexanol, 0.82161 for 1-octanol. Titrations of ILs into alcohols were performed in an analogous manner. Initial volume of alcohol in the titration ampoule was about 0.4 mL, while the injection volumes were in the range (10–25) ± 0.001 µL. Mole fractions of the resulting mixtures were calculated on the basis of the density of [C4 C1 Pyr][N(CN)2 ] at T = 298.15 K also measured within the framework of this work, namely 1.01485 g · mL−1 . 8 ACS Paragon Plus Environment

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The actual property measured by TAM III calorimeter is the difference in heat flow between sample and the reference cell. Uncertainty of this measurement is estimated to be about ±0.2%. Each injection is associated in heat flow peak on the power-time curve. Then, heat effect corresponding to j-th injection (δq j ) is obtained by integrating the heat flow peak over the injection time. The total molar excess enthalpy of mixing corresponding to a series of i consecutive injections (HiE ) is readily calculated as: HiE

=

∑ij=1 δq j

(1)

n1 + ∑ij=1 ∆n2, j

where n1 is the number of moles of solute 1 (IL in alcohol-to-IL titrations, or alcohol otherwise) and ∆n2, j stands for the number of moles of solute 2 injected during j-th titration. In order to verify and test accuracy of the apparatus, H E for two reference systems, namely, methanol with water and cyclohexane with n-hexane, were measured at T = 298.15 K. The results obtained were compared to available literature data and an excellent agreement was observed. 28 Finally, the uncertainty of the H E data determined in the present study was estimated to be within ±0.5%.

Theoretical Background Perturbed-Chain SAFT Perturbed-chain statistical associating fluid theory (PC-SAFT) proposed by Gross and Sadowski 54,55 in the beginning of 2000s is an approach derived from thermodynamic perturbation theory of Wertheim. 56–59 It is based purely on statistical mechanics and molecular simulation data of molecular chains composed of spherical segments interacting by short-range physical (dispersion) and highly directional specific forces (e.g. hydrogen-bonded systems). In terms of the PC-SAFT, all thermodynamic properties of a mixture are expressed in the form of a dependence of residual Helmholtz free energy (Ares ) on temperature, density and mole fractions. Different contributions 9 ACS Paragon Plus Environment


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to the free energy, for example due to hard chain formation (hc), dispersive interactions (disp) and association (assoc) can be treated separately, so that the main working equation of PC-SAFT model reads as a˜res ≡

Ares = a˜hc + a˜disp + a˜assoc . NkB T

(2)

In eq (2) N stands for number of molecules in the system and kB is the Boltzmann constant. In this paper we will not discuss all the PC-SAFT equations in detail. Comprehensive summary and derivation of all the expressions involved in eq (2) can be found in the original PC-SAFT papers. 54,55 In this section we only introduce the model parameters and combining rules. In the case of systems that contain only nonassociating components (e.g., hydrocarbons), only the first two terms need to be included in eq (2). Each component of such a mixture is described by three characteristic pure-fluid parameters: number of spherical segments forming the chain (m), hard-sphere segment diameter (σ) and dispersion energy potential well depth (u/kB ). For systems composed of at least one associating component (e.g. water, alcohol, carboxylic acid), an association contribution in eq (2) becomes the most essential from the point of view of thermodynamic behavior of the system. Association in the system is described by the presence of associating sites attached to the chains. To characterize a given specific interaction between site A and site B, two additional parameters describing the strength of association are introduced. Those parameters are energy potential well depth and volume of association, denoted by εAB /kB and κAB , respectively. Summing up, any pure substance is described by three or more PC-SAFT parameters depending on its chemical nature. A common procedure for calculating all those parameters rests on adjusting them to experimental pure substance properties, such as saturated liquid and/or vapor density or vapor pressure. In order to apply the PC-SAFT equations to mixtures, one needs to assume combining rules for cross-interaction parameters involved in the dispersion and association terms. Potential well depth for dispersive interactions of segments constituting different molecules i and j (i.e., ui j /kB ) as well


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as segment diameter corresponding to this interaction (i.e., σi j ) are usually calculated by using the well-known combining rules of Lorentz-Berthelot (LB):

ui j =

√

ui u j ,

σi j =

σi + σ j 2

(3)

In the case of cross-associating systems, associating site A on molecule i (Ai ) can interact with associating site B on molecule j (B j ). At the same time, associating site B on molecule i (Bi ) can interact with associating site A on molecule j (A j ). To calculate the energy and volume of the cross-association (namely εAi B j /kB , εA j Bi /kB and κAi B j κA j Bi ), appropriate combining rules are required. It was found that the following relations proposed by Wolbach and Sandler (WS) 60 are suitable to describe the effects related to cross-association, when coupled with SAFT-based models:

ε

Ai B j

=ε

A j Bi

ε Ai B i + ε A j B j , = 2

κ

Ai B j

=κ

A j Bi

=

p

κAi Bi κA j B j

√

σi σ j σi j

3

.

(4)

Finally, if pure fluid parameters are known for all the components forming the mixture, the PC-SAFT equations combined with eqs (3) and (4) can be used in an entirely predictive manner. However, satisfactory results can be obtained only for systems composed of fairly similar size and chemical nature. To overcome this obstacle, binary interaction corrections to energetic crossWS interaction parameters of LB and WS combining rules (denoted by kiLB j and ki j , respectively) are

introduced with accordance to the following definitions:

ui j =

√

ε Ai B j =

ui u j 1 − kiLB j ,

(5)

ε Ai B i + ε A j B j 1 − kiWS , j 2

(6)

The expressions for σi j and κAi B j are assumed to be the same as in eqs (3) to (4). Of course, kiiLB = kiiWS = 0 and kiXj = kXji , where superscript X stands for LB or WS. In the conventional equationof-state modeling, the binary corrections are usually obtained from experimental binary data by 11 ACS Paragon Plus Environment


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means of fitting. Such an approach results in vanishing of predictive capacity of the model, unless distinct method for calculation of kiXj is available. Thus, development of either new methods and/or correlations for determination of the binary interaction parameters, or totally new combining rules seem to be very attractive.

SAFT Molecular Schemes Prediction of thermodynamic properties of ILs-based systems with the SAFT-like models requires a physically meaningful molecular models reflecting various characteristics of the constituting compounds. Whereas the PC-SAFT representation is quite straightforward for common molecular compounds such as hydrocarbons or alcohols, the problem is not so obvious for ILs. Of course, this due to their complexity at molecular level related to different phenomena, e.g. different contribution of dispersive and polar-electrostatic interactions, ion pairing, nanoscale segregation. 4 Therefore, some simplifications have to be assumed to model such fluids with the PC-SAFT approach. 27 In the case of ILs based on [N(CN)2 ] anion, three approaches were proposed in literature thus far. Accoriding to the work of Mutelet et al., 45 these ILs can be represented by homonuclear chains with a single associating site mimicking the specific interactions. In terms of that model the molecules of ILs are capable of cross-association with other molecules. However, self-association between ILs molecules is not permitted. It was shown that such an approach allows accurate representation of liquid density data for imidazolium series at atmospheric pressure. Sadowski et al. 33 modeled [N(CN)2 ] IL as an self- and cross-associating substance, having 4 positive (donor) and 4 negative (acceptor) sites per chain. The number of sites for such symmetric associating scheme was established on the basis on optimization of the model performance. In our previous paper, 29 we also employed symmetric scheme. However, we assumed not 8, but 6 sites per chain: 3 donor and 3 acceptor sites. Our reasoning was based on physical arguments, namely assignment of the negative (acceptor) sites to lone electron pairs on nitrogen atoms present in the structure of dicyanamide anion. We showed that our approach enables PC-SAFT model to accurately reproduce both volumetric data and vapor pressure of pure 1-butyl-3-methylimidazolium dicyanamide. 29 Thus, we 12 ACS Paragon Plus Environment

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decided to follow this methodology and adopt it also in the current work. In the case of molecular solvents considered in this paper, namely n-heptane, benzene, toluene, ethylbenzene, thiophene, 1-butanol, 1-hexanol and 1-octanol, the PC-SAFT parameters are readily available in literature. 54,55,61 In particular, we used 2B associating scheme for 1-alcohols, i.e. one donor site and acceptor site reflecting donating/accepting facilities of hydroxyl group are assumed per molecule. Remaining compounds were treated as non-associating ones. Complete list of the PC-SAFT parameters used in this work is given in Table 1.



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Table 1: PC-SAFT Parameters of Pure [C4 C1 Pyr][N(CN)2 ] Ionic Liquid and the Investigated Molecular Compounds. Compound

m

σ (Å)

u/kB (K)

εAB /kB (K)

κAB

[C4 C1 Pyr][N(CN)2 ] (3 + 3 scheme) 30

7.2323

3.5147

290.735

2276.35

0.0797

n-heptane 54

3.4831

3.8049

238.40

benzene 54

2.4653

3.6478

287.35

toluene 54

2.8149

3.7169

285.69

ethylbenzene 54

3.0799

3.7974

287.35

thiophene 61

2.3644

3.5655

301.73

1-butanol 55 (1 + 1 scheme)

2.7515

3.6139

259.59

2544.6

0.006692

1-hexanol 55 (1 + 1 scheme)

3.5146

3.6735

262.32

2538.9

0.005747

1-octanol 55 (1 + 1 scheme)

4.3555

3.7145

262.74

2754.8

0.002197


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Fitting Binary Corrections to Infinite Dilution Data X (X = LB or WS) appearing in eqs (3) and (4) are usually The binary interaction parameters k12

obtained from the binary phase equilibrium data by means of fitting. 24 In this work we follow the methodology employed by us previously. 25,27 It rests on application of experimental activity coefficients of molecular solvent at infinite dilution in IL (γ∞ 2 ). The advantage of such way of modeling is that γ∞ 2 values are more easily accessible (mainly by GLC measurements) than other bulk phase equilibrium properties of ILs-based systems, e.g., LLE or H E . The determination of X is based on iterative solving of the following equation (at defined temperature): k12

L,∞ X L,0 X Φ k12 ≡ ϕ2 (k12 )/ϕ2 − γ∞ 2 = 0, L,∞

where ϕ2

L,0

and ϕ2

(7)

denote liquid phase fugacity coefficients of 2 at infinite dilution in 1 and in

pure state, respectively. The fugacity coefficients are calculated from residual Helmholtz energy on the basis of common thermodynamic formula. In turn, X is set as LB or WS, depending on the type of molecular solute 2. For non-associating and self-associating compounds X = LB (and WS = 0) and X = WS (and kLB = 0), respectively. Finally, it is assumed that kX is a function of k12 12 12

temperature and follows experimental temperature dependence of γ∞ 2 approximated by: ln γ∞ 2 = a+

b . T

(8)

In present study, we used the experimental γ∞ 2 for n-heptane, benzene and thiophene measured by Blahut and Dohnal. 62 In turn, γ∞ 2 data for 1-butanol, 1-hexanol and 1-octanol were estimated by means of linear solvation-energy relationship (LSER) adopted to the experimental γ∞ 2 data.

Results and Discussion In the current section we summarize and shortly discuss the new experimental data sets measured within the framework of this work and then we present PC-SAFT calculations carried out. 15 ACS Paragon Plus Environment


Experimental Data Five new experimental data sets on LLE in binary systems were obtained. The numeric values of IL mole fractions versus equilibrium temperature are listed in Table 2. The results are also shown graphically in Figure 2. 360 340 320 T/K

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300 280 260 0

0.2

0.4

0.6

0.8

1

x1

Figure 2: Liquid-liquid phase equilibrium phase diagrams (IL mole fraction x1 vs. equilibrium temperature T ) in binary systems {[C4 C1 Pyr][N(CN)2 ] (1) + molecular solvent (2)}. Key: circles, n-heptane; squares, benzene; triangles, toluene; stars, ethylbenzene; crosses, thiophene; solid lines, LB , see eq (5), fitted to experimental γ∞ data. 62 PC-SAFT predictions with k12 2


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Table 2: Liquid-Liquid Equilibrium Experimental Data (IL Mole Fraction x1 vs. Temperature T ) Obtained in This Work for Binary Systems Composed of [C4 C1 Pyr][N(CN)2 ] and Molecular Solvent.

T (K)

x1

T (K)

x1

benzene

n-heptane 0.9496

305.9

0.2566

285.8

0.9407

319.2

0.2712

316.9

0.9297

331.0

0.2787

342.8

0.9221

341.8

0.9137

350.4

toluene

ethylbenzene

0.4189

300.3

0.5331

253.6

0.4278

311.3

0.5544

298.9

0.4444

321.7

0.5580

302.7

0.4478

324.7

0.5766

316.7

0.4695

347.7

0.5874

320.6

0.6009

347.6

thiophene 0.1903

303.1

0.1935

318.1

0.1992

337.3

0.2024

347.4



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As can be easily concluded from the results collected, the solubility of the molecular solvent in [C4 C1 Pyr][N(CN)2 ] decreases in the following order: thiophene > benzene > toluene > ethylbenzene > n-heptane. Obviously, these results are in good agreement with previous studies concerned with liquid-liquid phase equilibria in ionic liquid systems. In particular, aliphatic hydrocarbons like alkanes have low solubility in ILs, because their mutual interactions with ILs’ constituting ions involve only weak dispersive van der Waals forces. Indeed, experimental solubility of n-heptane in [C4 C1 Pyr][N(CN)2 ] is at the level < 0.05 on mole fraction basis. Moreover, the solubility of n-heptane increases with temperature. Therefore the system {[C4 C1 Pyr][N(CN)2 ] + n-heptane} possibly exhibits upper critical solution temperature (UCST) phase behavior. On the other hand, solubility of aromatic hydrocarbons in the studied IL is much higher in comparison to n-heptane. This is mainly due to possible π-π and n-π cross-interactions between coupled aromatic and/or lone electrons located at the anion and solvent. Furthermore, increasing the length of alkyl chain substituent attached to aromatic ring (like in toluene and ethylbenzene) increases the contribution of nonpolar dispersive forces, hence results in a deterioration of solubility. In fact, in our experiments we evidenced that longer the chain, the lower solubility of a given alkylbenzene (from approx. 0.8 in the case of benzene to approx. 0.4 on the mole fraction basis for ethylbenzene). What is very interesting, binary mixtures composed of the studied IL and aromatic hydrocarbon displays lower critical solution temperature (LCST) phase diagram. In fact, in the range of temperature under study, the solubility of the aromatic hydrocarbon decreases as with an increase of temperature. It is concluded on the basis of the collected data, but also based on experimentally observed phase split disappearance during cooling. In the case of thiophene, the lone pair at the sulfur atom additionally promote higher solubility compared to benzene. Furthermore, this systems also exhibits LCST shape of LLE coexistence curve. It is important to note that the differences in the affinity to [C4 C1 Pyr][N(CN)2 ] observed for different families of hydrocarbons and thiophene may suggest some possible applications of the investigated IL in liquid-liquid separations, e.g. aromatic from aliphatic, or sulfur compounds from gasoline. Finally, it should be noted that we also check LLE phase behavior of [C4 C1 Pyr][N(CN)2 ], when mixed with alcohols. No miscibility gap was 18 ACS Paragon Plus Environment

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detected, when changing the alcohol from methanol up to 1-octanol in the range of temperature under consideration (T = 250–360 K). Excess enthalpies of mixing for all the considered mixtures are shown in Figures 3 and 4. A complete list of data is presented in the Supporting Information, Table S1. In particular, Figure 3 shows H E for binaries {[C4 C1 Pyr][N(CN)2 ] + benzene, or thiophene}, whereas Figure 4 recapitulates the data for the mixtures with alcohols. 0.6 0.2 HE / kJ ⋅ mol-1

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-0.2 -0.6 -1.0 -1.4

0

0.2

0.4

0.6

0.8

1

x1

Figure 3: Excess enthalpy of mixing in binary systems {[C4 C1 Pyr][N(CN)2 ] (1) + molecular solvent (2)} at T = 298.15 K. Key: circles, benzene; squares, toluene; solid lines, PC-SAFT predicLB , see eq (5), fitted to experimental γ∞ data; 62 dashed lines, PC-SAFT pure predictions tions with k12 2 LB = 0. Empty and filled markers correspond to solvent-to-IL and IL-to-solvent titrations, with k12 respectively. First, we emphasize that both solvent-to-IL and IL-to-solvent titration experiments yield qualitatively and quantitatively consistent data. In fact, the produced H E curves converge. This observation confirms the reliability of the apparatus as well as the method used. As can be easily noted, systems with benzene and thiophene exhibit negative values of H E , i.e. exothermic mixing effect. Such a result is usually interpreted in terms of the strength of molecular interactions between like and unlike molecules present in the mixture. Negative heat of mixing means that interactions IL-solvent stronger and more preferable than IL-IL and solute-solute interactions. Furthermore, 19 ACS Paragon Plus Environment


2.5 2.0 HE / kJ ⋅ mol-1

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1.5 1.0 0.5 0 -0.5

0

0.2

0.4

0.6

0.8

1

x1

Figure 4: Excess enthalpy of mixing in binary systems {[C4 C1 Pyr][N(CN)2 ] (1) + molecular solvent (2)} at T = 298.15 K. Key: circles, 1-butanol; squares, 1-hexanol; triangles, 1-octanol; solid WS , see eq (6), fitted to experimental γ∞ data; 62 dashed lines, lines, PC-SAFT predictions with k12 2 WS PC-SAFT pure predictions with k12 = 0. Empty and filled markers correspond to solvent-to-IL and IL-to-solvent titrations, respectively. H E for system with thiophene is higher (in terms of absolute value), compared to benzene. Such experimental (macroscopic) observation corresponds to the molecular level (microscopic) characteristic, namely stronger IL-thiophene interactions compared to those for IL-benzene mixture. It was also confirmed by solubility measurements as clearly stated in the previous paragraph. Similar behavior was reported by other authors as well. In particular, we reported it recently for analogous systems containing isoquinolinium IL. 28 It is also noteworthy, that the sign of H E reported in this work is consistent with the sign of partial infinite dilution enthalpy of solute (∆H2E,∞ ) determined independently from gas-liquid chromatography measurements by Blahut and Dohnal. 62 In fact, E,∞

those authors showed that in the case of both benzene and thiophene ∆H2

< 0.

Contrary to benzene and thiophene, H E for systems with alcohols is positive in the entire range of IL mole fractions. Thus, IL-alcohol interactions are less-preferable than IL-IL and alcoholalcohol. Moreover, the effect of mixing is higher as the alkyl chain length of the alcohol increases. Of course, this is due to the dispersive contribution to molecular interactions, which is more sig-


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nificant for longer chains. The measured data are consistent with γ∞ 2 data reported by Blahut and E,∞

Dohnal, 62 as they showed that ∆H2

for alcohols and it increases with the order: methanol

Thermodynamic Study of Binary Mixtures of 1-Butyl-1

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