Multilevel screening and mechanism analysis of ionic liquids for separating pyridine from coal pyrolysis model oil

Abstract

The separation of high-purity pyridine from coal pyrolysis oil is a typical challenge faced in the coal chemical industry for the high-value utilization of resources. In this study, a systematic framework combining multilevel screening and mechanism exploration is presented to investigate ionic liquids (ILs) for efficiently separating pyridine from toluene as a representative of coal pyrolysis oil. First, the COSMO-RS model is used to predict the key thermodynamic properties of ILs, thereby pre-screening ILs with high separation potential. Then, a deep learning method is employed to estimate the key physicochemical properties of ILs for further IL screening. Subsequently, the performance of the remaining ILs in a continuous extraction and extractive distillation is evaluated in Aspen Plus to obtain better-performing ILs in terms of energy and solvent consumption. The optimal three ILs, namely [C₃OHPy][C(CN)₃], [C₄mim][HSO₄], and [C₃OHC₁Pyr][C(CN)₃] are determined through the multilevel screening strategy. Finally, quantum chemical calculation and molecular dynamics simulation are elaborated to reveal the separation mechanism at the microscopic scale and verify the reliability of the screening results.