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20162026
most citedMachine learning materials physics: Integrable deep neural networks enable scale bridging by learning free energy functions

113 citations · 175 across the 12 of their papers we have counts for

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cond-mat.mtrl-sci2016

A comparison of Redlich-Kister polynomial and cubic spline representations of the chemical potential in phase field computations

Gregory H. Teichert, N. S. Harsha Gunda, Shiva Rudraraju +4

Free energies play a central role in many descriptions of equilibrium and non-equilibrium properties of solids. Continuum partial differential equations (PDEs) of atomic transport,…