Stability of copper-based alloys investigated through active learning

Copper-based alloys, due to their high electrical conductivity and high strength, are of great interest for electric and electronic applications such as connectors and lead frames. Here, we investigate the stability of Cu-Ni-Si-Cr alloys for different types and concentrations of alloy elements through computational means. Quantum-mechanical simulations are performed on a large number of structural candidates. We use a relaxation-on-the-fly active learning algorithm in order to relax the large number of n-ary candidates to their minimum energy, and target those with the lowest enthalpy of formation. The stability of alloy phases is then assessed based on their convex hull and the phonon density of states analysis. In the end, we propose copper alloy candidates with robust structural properties for practical applications.