Investigating the Increased CO2 Capture Performance of Amino Acid Functionalized Nanoporous Materials from First-Principles and Grand Canonical Monte Carlo Simulations

Abstract

Nanoporous materials such as metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs) have been identified as key candidates for environmental remediation through catalytic reduction and sequestration of pollutants. Given the prevalence of CO2 as a target molecule for capture, MOFs and COFs have seen a long history of application in the field. More recently, functionalized nanoporous materials have been demonstrated to improve performance metrics associated with the capture of CO2. We employ a multiscale computational approach including ab initio density functional theory (DFT) calculations and classical grand canonical Monte Carlo (GCMC) simulations, to investigate the impact of amino acid (AA) functionalization in three such nanoporous materials. Our results demonstrate a nearly universal improvement of CO2 uptake metrics such as adsorption capacity, accessible surface area, and CO2/N2 selectivity for six AAs. In this work, we elucidate the key geometric and electronic properties associated with improving the CO2 capture performance of functionalized nanoporous materials.