The scheme of the NN model is shown in Fig. . The total energy of a given system is expressed by the sum of individual atomic energies: 𝐸 = ∑i 𝐸i. While the atomic energy of each atom is determined by its local chemical environment. To guarantee the translational, rotational, and permutational symmetries lying in the PES, the Cartesian coordinates of atomics are mapped to an embedding network. The relationship between the atomic energy and the embedding network is learned by another neural network called fitting network. Both networks use the ResNet architecture . The size of the embedding network was set to and the size of the embedding matrix was set to 12. The size of the fitting network is set to (240, 240, 240). The cutoff radius was set to 6.0Å and the descriptors decay smoothly from 1.0 Å to 6.0 Å. The initial learning rate was set to 0.001 and it will decay every 4000 steps. The loss is defined by