In Silico Discovery of Covalent Organic Frameworks for Carbon Capture

We screen a database of more than 69,000 hypothetical covalent organic frameworks (COFs) for carbon capture, using parasitic energy as a metric. In order to compute CO2-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine. Furthermore, we identify over 70 top performers that, based on the same metrics of evaluation, perform comparably to Mg-MOF-74 and outperform reported experimental COFs for this application. We analyze the effect of pore topology on carbon capture performance in order to guide development of improved carbon capture materials.