Accelerate the discovery of OCM catalysts with machine-learning and machine-synthesis

Oxidative coupling of methane (OCM) reaction is crucial for converting natural gas into value-added chemicals like ethylene. Despite the development of over 2000 catalysts, achieving a C2 (C2H4 + C2H6) yield of 30% necessary for industrial viability remains a great challenge. In recent years, the rapid advancement of artificial intelligence (AI) has brought new opportunities to address this issue: the integration of machine learning (M-L) facilitates the identification and optimization of catalyst compositions, while machine synthesis (M-S) enhances the efficiency of catalyst synthesis. This perspective discusses the recent advancements in OCM using M-L and M-S techniques, aiming to accelerate the discovery and identification the most efficient catalyst in a benchmarking study, and promote the industrial application of OCM reaction.