Exploring covalent organic frameworks through the lens of computational chemistry

Abstract

Covalent organic frameworks (COFs) are a special class of porous polymeric architectures with robust covalent bonds that can have two- or three-dimensional frameworks. They can easily be utilised for designing primary and higher-order architectures, and their unique properties make them a groundbreaking class of materials in the current scientific research. The advantageous properties of COFs include easily tunable porous structures, high surface area, low density, and exceptional chemical and thermal stability. With their diverse molecular structures, they are promising candidates for ubiquitous applications including energy and the environment. Employing various advanced computational methods such as grand canonical Monte Carlo (GCMC) simulations, molecular dynamics (MD) simulations, density functional theory (DFT), hybrid quantum mechanical/molecular mechanics (QM/MM), multiscale modelling and machine learning (ML) approaches, researchers provided a profound understanding of the interaction/adsorption mechanisms, performance–structure relationships and electronic behaviour of COFs even at the atomic level, which is often unattainable through conventional experimental methods. Currently, emerging computational methodologies play more imperative roles in unveiling the exciting potential of COFs in mitigating global challenges pertaining to environment, energy and sustainability. This review explores the critical role of computational chemistry in the design, modelling, and applications of COFs, including key challenges and future perspectives, serving as a stepping stone for future advancements.