Data-driven discovery of 2D materials as photocatalysts for water splitting
Two-dimensional (2D) materials are emerging as potential photocatalysts due to their effective sunlight absorption, large specific surface area, and abundant active sites.
Yet, the discovery of 2D materials that fulfill the essential photocatalyst criteria remains challenging. With significant growth in computing power and available computational data, the field of material discovery has evolved into a data-driven era, characterized by big data and advanced machine-learning (ML) algorithms.
Utilizing ML-predicted properties, one can conduct an application-focused preliminary screening of a wide range of materials, followed by more precise computations, such as density functional theory (DFT), to further investigate the selected materials.
For his PhD research, Yatong Wang used a data-driven approach to identify new two-dimensional materials that could be used as photocatalysts for solar water splitting.
Title of PhD thesis: . Supervisors: Geert Brooks, Richard van de Sanden, and S. Es.