Multi-modal and multi-scale screening of solid sorbent materials for gas capture: The importance of adsorption kinetics

Abstract

High-Throughput Computational Screening (HTCS) is an invaluable technique that has been used to sift through the growing number of candidate gas capture and separation materials compiled in databases during the last two decades. The screening workflow typically consists of loading the material structure from a Crystallographic Information File (CIF) and performing Grand Canonical Monte Carlo (GCMC) simulations of the adsorption behavior of molecules of interest. GCMC provides the equilibrated number of molecules that adsorb on each material at a given temperature and pressure. By sweeping a range of pressures at a fixed temperature, one obtains an adsorption isotherm. In more advanced studies, the simulated isotherms are fed as input to a process-level optimization method that propagates the molecular-level performance metrics to the process scale. The process-level model covers both the equilibrium and kinetics aspects of adsorption, including mass transfer considerations. Sensitivity analysis shows that the process-level performance is heavily influenced by the adsorption kinetics. In this work, we performed molecular- to process-level screening of ~1000 metal-organic frameworks (MOF) for carbon capture. We simulated their adsorption isotherms and propagated their process-level performance, leading to a material ranking. We then took the top 10% materials and investigated with classical Molecular Dynamics (MD) simulations how the adsorbate molecules diffuse into the system. We found that many apparently good carbon capture materials in fact had very low diffusivity, which severely impacts their real-world performance at the process level. Finally, we propose a computational workflow that treats the diffusivity coefficient as a top-tier metric in HTCS studies going forward to accelerate the discovery of new sustainable materials for carbon capture.