Modelling study on phase equilibria behavior of ionic liquid-based aqueous biphasic systems

Yuqiu Chen,Xiaodong Liang,John M Woodley,Georgios M Kontogeorgis

doi:10.1016/j.ces.2021.116904

Yuqiu Chen, Xiaodong Liang + Show 2 more

Open Access

https://doi.org/10.1016/j.ces.2021.116904

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Abstract

The ability to predict the phase equilibria behavior is of crucial relevance in the early design stage of biphasic liquid-liquid systems. Ionic liquid-based aqueous biphasic systems (IL-ABS) have demonstrated superior performance in many applications such as the recovery of bio-products and the recycling of hydrophilic ILs from aqueous solutions. In order to better utilize these novel biphasic liquid-liquid systems, modelling studies on phase equilibria behavior are carried out in this work. First, the IL database developed in our previous work is extended to these unconventional biphasic systems. In total, 17,449 experimental binodal data points covering 171 IL-ABS at different temperatures (278.15 K-343.15 K) are collected. Then, all involved IL-ABS are correlated using a popular three-parameter mathematical description and the optimal parameters of each IL-ABS are obtained. Afterwards, we try to build a linear group contribution (GC) model to predict the phase equilibria behavior of IL-ABS, but it fails due to the high complexity of these biphasic systems. For this reason, we finally turn to applying a well-known machine learning algorithm, i.e., artificial neural network (ANN), to build a nonlinear GC model for such a purpose. This model gives a mean absolute error (MAE) of 0.0175 and squared correlation coefficient (R2) of 0.9316 for the 13,789 training data points, and for the 3,660 test data points they are 0.0177 and 0.9195, respectively. The results indicate that the proposed nonlinear ANN-GC model, to some extent, is capable to predict the phase equilibria behavior of IL-ABS. Besides the efforts of building GC models, we also discuss some main issues that govern the phase equilibria behavior of IL- ABS, which could be a guidance in the design of IL-ABS.

Highlights

Ionic liquids (ILs) are being considered as potential alternatives to conventional organic solvents due to their attractive properties such as negligible volatility, non-flammability, exhibiting good solubility and selectivity for a wide range of organic and inorganic chemicals (Rogers and Seddon, 2003)
On the other hand, the linear group contribution (GC) model based on this three-parameter mathematical description is unable to simultaneously represent the phase property of Ionic liquid-based aqueous biphasic systems (IL-aqueous biphasic systems (ABS))
Despite the developed artificial neural network (ANN)-GC model is able to provide reliable predictions, we should not ignore that unlike the traditional models such as UNIFAC and NRTL, this ANN-GC model is not derived from thermodynamic principles

Summary

Introduction

Ionic liquids (ILs) are being considered as potential alternatives to conventional organic solvents due to their attractive properties such as negligible volatility, non-flammability, exhibiting good solubility and selectivity for a wide range of organic and inorganic chemicals (Rogers and Seddon, 2003). Inorganic salts such as NaH2PO4, K3PO4 and (NH4)2SO4 are the most widely used second phase-forming agents in IL-based ABS, while a certain number of more benign species such as organic salts, amino acids, carbohydrates and polymers are being studied as alternatives to high-charge-density inorganic salts in the formation of second phase (Ventura, 2017). As both IL and phase-forming agent have influence on the system’s properties, it is challenging to rationally design IL-based ABS for specific tasks. Besides the efforts of building GC models, we discuss some main issues that govern the phase equilibria behavior of IL- ABS, which could be a guidance in the design of IL-ABS

Experimental data sets

Linear model

Nonlinear GC model

Results and discussions

Conclusion