Machine learning and DFT database for C-H dissociation on single-atom alloy surfaces in methane decomposition

Methane decomposition using single-atom alloy (SAA) catalysts, known for uniform active sites and high selectivity, significantly enhances hydrogen production efficiency without CO(2) emissions. This study introduces a comprehensive database of C-H dissociation energy barriers on SAA surfaces, generated through machine learning (ML) and density functional theory (DFT). First-principles DFT calculations were utilized to determine dissociation energy barriers for various SAA surfaces, and ML...