Investigation of Mechanical Properties of Combinatorial Ti-Cu Film Using MD Simulation With Neural Network Potential

Combinatorial approach is a prominent method to synthesize samples with atomic composition gradients, which enables the high-throughput discovery of new materials. Titanium-copper (Ti-Cu) alloy is widely used in electronic devices because of its excellent mechanical properties such as stress relaxation resistance, bond formality, and workability. By synthesizing Ti-Cu thin film with combinatorial approach, the mechanical property may be improved, leading to a new application. Molecular Dynamics (MD) simulation is a powerful tool to predict mechanical property, but it requires interatomic potentials to depict the movements of atoms. Because of the complex structures of Ti-Cu thin film synthesized by combinatorial approach, the creation of interatomic potentials is a difficult and time-consuming process. Therefore, in this study, a neural network (NN) based method to create interatomic potentials is developed, which are referred to as neural network potentials (NNPs). It is found that NNP can accurately reproduce the energies and forces calculated by Ab initio molecular dynamics (AIMD) simulations. Finally, using MD simulations with developed NNP, the mechanism of mechanical properties is investigated from the perspective of atomic scales.