The Behler-Parrinello high-dimensional neural network potential (HDNNP) was constructed using the neural network potential package (n2p2) on the initial dataset (Figure ), as described in Methods and Section S1. The NNPs were trained via multistream extended Kalman filter algorithm using energies and forces, and the dataset was expanded via active learning, Figure . In short, two NNPs were trained with the initial dataset. And 1%-25% of structures of the dataset were used to perform the Neural Network based Molecular Dynamics (NN-MD) simulations using one of the NNPs.