However, a single DFT-based pathway calculation takes hours or even days, making the exhaustive pathway calculations required to elucidate a complex catalytic mechanism difficult. This situation has recently been significantly improved with the advent of the neural network potential (NNP) . An NNP trained on a sufficient DFT-based structure-energy database provides a good estimate of the DFT energy and force at a given atomic composition. with 1,000 atoms. More importantly, it is trained on data for 72 elements and their combinations, making it versatile and easily applicable to a wide range of systems .