Metal-Organic Frameworks: Advances in First-Principles Computational Studies on Catalysis, Adsorption, and Energy Storage

Metal-organic frameworks (MOFs) have exhibited tremendous potential in catalysis, gas storage, drug delivery, and sensing due to their high surface area, high porosity, and tunability. MOFs are constructed from metal ions or clusters connected by organic ligands, offering scientists extensive research possibilities owing to their diversity and complexity. However, the diversity of MOFs also presents challenges in stability and controllability, particularly concerning instability or structural changes under varying environmental conditions. Theoretical calculations, especially first-principles calculations and molecular dynamics simulations, have become crucial tools for MOF research. These methods can predict the structural stability, adsorption properties, and catalytic activity of MOFs, simulate experimental processes, and guide experimental design to optimize the structure and performance of MOFs. Nevertheless, first-principles calculations face challenges of high computational costs and lengthy computations when dealing with large-scale systems or complex processes. Additionally, the accuracy of the calculation results is influenced by the selection of exchange-correlation functionals and basis sets. With advancements in computational techniques, it is anticipated that more accurate and efficient computational models will emerge to address the challenges in MOF research. These advancements will further drive the applications of MOFs in various fields, promoting the development of materials science. This review summarizes the frontier research progress of MOFs and their practical applications combined with theoretical calculations, while also discussing the limitations of first-principles in MOF research. Future research directions include the development of more accurate and efficient computational models to address the challenges in MOF research, driven by the enhancement of computational capabilities and methodological improvements.