Multilevel screening of ionic liquid absorbents for the capture of low-content styrene VOC

As a volatile organic compound (VOC), styrene can pose significant risks to human health and environment if released into the air without proper treatment. Absorption based on ionic liquids (ILs) has been widely regarded as a promising VOC treatment approach, whereas there is limited research on capturing styrene by ILs. In this work, a multilevel framework was proposed to screen IL absorbents from the largest number of cation-anion combinations in the latest COSMObase. The COSMO-RS model is applied to estimate the absorption and desorption potentials of all IL candidates for styrene capture based on solubility prediction, while important physical properties of them namely melting point, viscosity, and toxicity are estimated by a recently-reported deep learning model. A parallel screening specific to the commercially available ILs in the initial candidate database was also performed. The top-ranked three ILs, identified in both scenarios with and without limiting the commercially availability, were further evaluated in a simulated absorption-desorption process in Aspen Plus. The most promising ILs in each scenario were figured out, which vividly demonstrates the value of discovering novel ILs.