What Data Are Most Valuable to Screen Ionic Liquid Entrainers for Hydrofluorocarbon Refrigerant Reuse and Recycling?

Abstract

Separating azeotropic mixtures of hydrofluorocarbons (HFCs) for reuse and recycle is environmentally and economically imperative. While ionic liquid (IL)-enabled HFC separations show promise, Edisonian trial-and-error screening for the optimal IL entrainer is intractable and expensive. Here, we propose an open-source, equation-oriented modeling framework to rapidly translate HFC/IL solubility data into regressed thermodynamic models which can be used for process design under uncertainty and rapid IL screening. Moreover, we use data science and process systems engineering tools to contemplate which data are the most valuable for IL screening. We find that binary solubility data collected at multiple temperatures is adequate for separation process design, and newly available ternary solubility measurements should be reserved for validation. Additionally, we use uncertainty quantification analyses to show up to 10% experimental error is acceptable for IL screening decisions. Informed by these results, we recommend a multistep workflow for IL screening.

Automatic Design of Extractive Distillation Sequence for a Multicomponent Azeotropic System

“…Salman et al separated the azeotrope of ethyl propionate and ethanol by the extractive distillation method and pressure swing distillation method, respectively, compared two entrainers (glycerine and ethylene glycol), and conducted an economic analysis of TAC of the two strategies. Common entrainers include some organic solvents, polymers, and ionic liquids . Gao et al established a heat pump pressure swing distillation process and a heat integrated pressure swing distillation process for cyclohexane/ tert -butanol azeotrope system, and both achieved lower energy consumption and improved economy.…”

Assessment and Ranking of Difluoromethane (R32) and Pentafluoroethane (R125) Interatomic Potentials Using Several Thermophysical and Transport Properties Across Multiple State Points

“…MS has emerged as a valuable tool to predict thermodynamic and transport properties for materials of industrial interest and to understand their microscopic origin. MS can aid in the design of novel processes for challenging separations, such as those posed by HFC mixtures. − MS requires accurate representations of interatomic interactions to obtain reliable predictions of properties and elucidation of molecular-level phenomena. These representations, commonly referred to as force fields (FFs), are mathematical models that describe the potential energies and forces between interaction sites (usually atomic nuclei).…”

Virtual Issue: A Multiscale View on Molecular and Process Design

“…3 Likewise, Lei et al 4 focused on IL design for aromatic mixture separations. Garciadiego et al discussed the separation of hydrofluorocarbon mixtures, 5 while Wang et al 6 considered the separation of CO 2 and SO 2 from gaseous mixtures. Meanwhile, Zhang et al tackled the design of deep eutectic solvents 7 for CO 2 absorption.…”