Optimization and validation of a deep learning CuZr atomistic potential: Robust applications for crystalline and amorphous phases with near-DFT accuracy

We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu–Zr materials, an example of a binary alloy system, that can coe...