A machine learning–based classification approach for phase diagram prediction

Guillaume Deffrennes, Kei Terayama, Taichi Abe, Ryo Tamura

Materials & Design 215 110497 (2022) · Elsevier BV

DOI: 10.1016/j.matdes.2022.110497

Data: JSON record · id doi:10.1016/j.matdes.2022.110497 · metadata: crossref

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Relations

Cited by (Crossref reference lists) (1)

• A comparative study of predicting high entropy alloy phase fractions with traditional machine learning and deep neural networks (2024) [crossref_reference_list]

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