![Predicting Accurate Adsorption Energies for Rational Catalytic Design via Machine Learning](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Fung_thumbnail%20pic%20260x160.jpg?h=a08abdbb&itok=O7XqXjyc)
Materials databases generated by high-throughput computational screening, typically using density functional theory (DFT), are valuable resources for discovering new heterogeneous catalysts, though the computational cost associated with generating them