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.
Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes.Advanced engineering materials, 6(5):299–303, 2004
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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.