Artificial Intelligence Driven Energy Chemistry: Make AI Do Your Work!

Energy catalysis represents a pivotal domain in contemporary scientific research. Nevertheless, the inherent complexity of many associated problems, influenced by numerous factors, surpasses the capabilities of traditional theoretical models. This raises a critical inquiry: can theoretical computations reliably anticipate experimental outcomes? I will present our recent progress in the interdisciplinary intersection of energy science and data science. AI technology is demonstrating robust auxiliary capabilities in catalyst material design, the establishment of catalysis theoretical models, experimental data mining, and various other aspects. This trend positions it as a prospective standard research tool in the field of energy catalysis in the near future.