Diffusion coefficients in a five-component high entropy alloy are extracted over a wide composition range by combining three strategic diffusion couples with a constraint-anchored physics-informed neural network.
We have also shown such reliable outcomes following the augmented Kirkaldy Lane method by producing di; erent types of di;usion paths in 38 the same system [13]
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Extracting Composition-Dependent Diffusion Coefficients Over a Very Large Composition Range in NiCoFeCrMn High Entropy Alloy Following Strategic Design of Diffusion Couples and Physics Informed Neural Network Numerical Method
Diffusion coefficients in a five-component high entropy alloy are extracted over a wide composition range by combining three strategic diffusion couples with a constraint-anchored physics-informed neural network.