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 as well as higher-order architectures, and their unique properties make them a groundbreaking class of current scientific research. The advantageous properties of COFs include easily tunable porous structures, high surface area, low density, with great chemical and thermal stability. Having 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 dynamic (MD) simulation, density functional theory (DFT), hybrid quantum mechanical/molecular mechanics (QM/MM), multiscale modelling and machine learning (ML) approaches, researchers provided profound understanding of interaction/adsorption mechanisms, performance-structure relationships and electronic behaviour of COFs even at atomic level, which often unattainable through conventional experimental methods. Currently, with emerging computational methodologies, computational techniques play a more imperative role in unveiling the exciting potential of COFs for global challenges-oriented applications, including environment, energy and sustainability. The review explores the critical role of computational chemistry during design, modelling, and applications of COFs, including key challenges and future perspectives, serving as a stepping stone for future advancements.