The authors combine a Jacobi-Legendre machine-learning potential with exact enumeration of configurations to predict that disordered fcc Ni-Pd is a metastable solid solution at room temperature and becomes thermodynamically stable around 600 K.
Persson, Commentary: The Mate- rials Project: A materials genome approach to accelerat- ing materials innovation , APL Mater
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Machine-learning approach for the phase stability and mechanical properties of disordered alloys at finite temperature
The authors combine a Jacobi-Legendre machine-learning potential with exact enumeration of configurations to predict that disordered fcc Ni-Pd is a metastable solid solution at room temperature and becomes thermodynamically stable around 600 K.