A permutation-invariant neural network predicts strain- and chemistry-dependent vacancy formation energies in FCC CoCrFeNi with R^2 = 0.958, showing volumetric strain dominates the average response.
Spectral quadrature for the first principles study of crystal defects: Application to magnesium.Journal of Computational Physics, 456:111035, 2022
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Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys
A permutation-invariant neural network predicts strain- and chemistry-dependent vacancy formation energies in FCC CoCrFeNi with R^2 = 0.958, showing volumetric strain dominates the average response.