(372y) Integration of Molecular Simulations and Computer-Aided Molecular Design to Enable Novel Azeotropic Separations

Automated screening of Ionics Liquids (ILs) for use as separating agents in azeotropic mixtures remains a challenge for Computer-Aided Molecular Design (CAMD) methods [1][2][3]. CAMD depends on molecular properties, which are traditionally predicted using quantitative-structure property relationships (QSPRs) and group contribution methods. However, these methods often fail for complex molecules, including ILs [4], and lead to uncertainty as to which candidate IL design should be promoted for experimental analysis. In this work, we propose augmenting traditional CAMD methods with molecular simulations for more reliable IL screening [5][6]. Molecular simulations, which use classical force field methods to calculate the physical properties of molecules, can be used as a guide for focusing on specific IL designs within CAMD, but accurate force field parameters are necessary for accurate property prediction. We explore uncertainty within molecular simulations of mixtures of hydrofluorocarbons (HFCs) and ILs, which are used to inform CAMD decisions in developing IL separating agents for azeotropic separation of HFC mixtures into high and low global warming potential (GWP) components. Molecular simulations were performed to determine the phase equilibria of specific HFC-IL mixtures. Separate simulations were run using parameters from three force fields, Generalized Amber Force Field (GAFF), Optimized Potentials for Liquid Simulations (OPLS), and a customized force field. The critical properties of the three HFCs were calculated using the traditional method of rectilinear diameters and the method of Hajipour and Satyro [7], which incorporates uncertainty in the critical property prediction. A comparison between the methods of critical property prediction along with the three force fields studied provided insight into the optimal force field parameters to use in further molecular simulations of HFC-IL binary mixtures, which are necessary in informing CAMD decisions.

References:

[1] Ng, L. Y., Chong, F. K., & Chemmangattuvalappil, N. G. (2015). Challenges and opportunities in computer-aided molecular design. Computers & Chemical Engineering, 81, 115-129.

[2]Valencia-Marquez, D., Flores-Tlacuahuac, A., & Vasquez-Medrano, R. (2011). Simultaneous optimal design of an extractive column and ionic liquid for the separation of bioethanol–water mixtures. Industrial & Engineering Chemistry Research, 51(17), 5866-5880.

[3] Chávez-Islas, L. M., Vásquez-Medrano, R., & Flores-Tlacuahuac, A. (2010). Optimal synthesis of a high purity bioethanol distillation column using ionic liquids. Industrial & Engineering Chemistry Research, 50(9), 5175-5190.

[4] Shiflett, M. B., & Yokozeki, A. (2008). Phase equilibria of hydrofluorocarbon-4310mee mixtures with ionic liquids: miscibility of threo-and erythro-diastereomers in ionic liquids. Industrial & Engineering Chemistry Research, 47(3), 926-934.

[5] Adjiman, C. S., Galindo, A., & Jackson, G. (2014). Molecules matter: the expanding envelope of process design. In Computer Aided Chemical Engineering (Vol. 34, pp. 55-64). Elsevier.

[6]Chávez-Islas, L. M., Vasquez-Medrano, R., & Flores-Tlacuahuac, A. (2011). Optimal molecular design of ionic liquids for high-purity bioethanol production. Industrial & Engineering Chemistry Research, 50(9), 5153-5168.

[7] Hajipour, S., & Satyro, M. A. (2011). Uncertainty analysis applied to thermodynamic models and process design–1. Pure components. Fluid Phase Equilibria, 307(1), 78-94.