This study presents a framework for the automated generation of reaction networks in heterogeneous catalysis. Powered by state-of-the-art machine learning models, the framework enables the investigation of thermal and electrochemical processes not amenable to density functional theory. The capabilities of its kinetic module are demonstrated by simulating Fischer–Tropsch networks with 37,000 reactions.
- Santiago Morandi
- Oliver Loveday
- Núria López
