Considering the existence of a large number and variety of metal−organic frameworks (MOFs) and ionic liquids (ILs), assessing the gas separation potential of all possible IL/MOF composites by purely experimental methods is not practical. In this work, we combined molecular simulations and machine learning (ML) algorithms to computationally design an IL/MOF composite. Molecular simulations were first performed to screen approximately 1000 different composites of 1-n-butyl-3methylimidazolium tetrafluoroborate ([BMIM][BF 4 ]) with a large variety of MOFs for CO 2 and N 2 adsorption. The results of simulations were used to develop ML models that can accurately predict the adsorption and separation performances of [BMIM][BF 4 ]/MOF composites. The most important features that affect the CO 2 /N 2 selectivity of composites were extracted from ML and utilized to computationally generate an IL/MOF composite, [BMIM][BF 4 ]/UiO-66, which was not present in the original material data set. This composite was finally synthesized, characterized, and tested for CO 2 /N 2 separation. Experimentally measured CO 2 /N 2 selectivity of the [BMIM][BF 4 ]/UiO-66 composite matched well with the selectivity predicted by the ML model, and it was found to be comparable, if not higher than that of all previously synthesized [BMIM][BF 4 ]/MOF composites reported in the literature. Our proposed approach of combining molecular simulations with ML models will be highly useful to accurately predict the CO 2 /N 2 separation performances of any [BMIM][BF 4 ]/MOF composite within seconds compared to the extensive time and effort requirements of purely experimental methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.