Identification of High-CO2-Capacity Cationic Zeolites by Accurate Computational Screening

Solid porous materials such as cationic zeolites have shown great potential in energy-efficient separation processes. Conventional adsorbent design involves ad-hoc and inefficient experimental evaluation of a large structural and compositional space. We developed a computational methodology to screen cationic zeolites for CO2 separation processes with quantitative accuracy, and identified a number of novel high-performing materials. This study enabled us to develop an intuitive design workflow for selecting optimal materials and dramatically accelerate the development of industrially relevant separation processes.