Identifying promising covalent organic frameworks for HCHO/O-2 + N-2 adsorption from indoor air pollution using high-throughput computational screening

Formaldehyde is regarded as a member of Group 1 carcinogen to humans by the International Agency for Research on Cancer (IARC). Effective capture of indoor formaldehyde is especially important. In this work, we perform a high-throughput computational screening of ~470 experimentally realizable covalent organic frameworks (COFs) structures to identify the best candidate that can separate formaldehyde from indoor air pollution. Several performance metrics: working capacity, adsorption selectivity and adsorbent performance factor to assess the performance of the COFs in the database. COF-LZU8 was identified with the highest selec-tivity and adsorbent performance factor, outperforming the most of the promising hMOFs by high-throughput computational screening reported to date. In addition, based on the radial distribution functions, snapshots and contour plots of the center of mass, thioether-functionalized linkers in the COF-LZU8 framework had an effective approach to significantly strengthen COF separation capability.