Computational Screening of 2D Materials for Photocatalysis

TLDR

Two‑dimensional materials possess unique electronic, optical, and mechanical properties distinct from their bulk counterparts, making them promising for energy storage and conversion technologies. The paper reviews recent advances in solar water splitting with 2D materials and outlines a density‑functional theory–based computational screening strategy to identify promising photocatalysts, while proposing future research directions and methodological improvements. Density‑functional theory tools are used to predict the electronic, optical, and aqueous solubility properties of 2D photocatalysts and to explore strain, bias, doping, and pH modifications for activity enhancement.

Abstract

Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.