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An interatomic potential for Al-Tb alloy around the composition of Al90Tb10was developed using the deep neural network (DNN) learning method. The atomicconfigurations and the corresponding total potential energies and forces oneach atom obtained from ab initio molecular dynamics (AIMD) simulations arecollected to train a DNN model to construct the interatomic potential for Al-Tballoy. We show the obtained DNN model can well reproduce the energies andforces calculated by AIMD. Molecular dynamics (MD) simulations using the DNNinteratomic potential also accurately describe the structural properties ofAl90Tb10 liquid, such as the partial pair correlation functions (PPCFs) and thebond angle distributions, in comparison with the results from AIMD.Furthermore, the developed DNN interatomic potential predicts the formationenergies of crystalline phases of Al-Tb system with the accuracy comparable toab initio calculations. The structure factor of Al90Tb10 metallic glassobtained by MD simulation using the developed DNN interatomic potential is alsoin good agreement with the experimental X-ray diffraction data.

Development of Interatomic Potential for Al-Tb Alloy by Deep Neural Network Learning Method