High-throughput computational screening of metal organic frameworks (MOFs) for CO2 selective separations: trends, challenges, and future perspectives

Abstract

Efficient separation of CO2 from industrial gas mixtures such as CO2/N2, CO2/CH4, CO2/H2, and CH4/H2 is central to carbon capture, clean fuel production, and hydrogen purification. While metal organic frameworks (MOFs) offer an unparalleled design space for addressing these separations, the vast chemical and structural diversity of MOFs renders experimental evaluation impractical. High-throughput computational screening (HTCS), enabled by molecular simulations, has therefore emerged as a powerful approach to systematically evaluate and rank MOFs across multiple separation targets. This review critically examines HTCS methodologies for both adsorption and membrane-based separations, with a unified analysis of four industrially important gas systems. Further, emerging structure-property relationships to extract general design principles for CO2-selective separations are also highlighted. The review emphasizes that the choice of appropriate simulation inputs such as modelling the framework, force field and charge assignment significantly influence the screening and ranking of MOFs. CO2 typically exhibits strong electrostatic interactions with MOF surfaces, resulting in higher adsorption affinity compared to other gases, whereas the smaller and lighter H2 molecule displays rapid diffusivity. In kinetic separation, mixture diffusivity data is crucial in determining membrane performance. There exists a correlation between MOF structural features and their separation performance. In general, MOFs with narrow pores (3-5 Å) and moderate porosities (0.5-.75) perform better for CO2 separation. This review details the approaches adopted in HTCS of MOFs and the screening outcomes to guide future HTCS-driven MOF discovery.