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A framework to predict binary liquidus by combining machine learning and CALPHAD assessments

Guillaume Deffrennes, Kei Terayama, Taichi Abe, Etsuko Ogamino, Ryo Tamura.
Materials & Design 232 112111. 2023.
Open Access Elsevier BV (Publisher)

NIMS author(s)


Fulltext and dataset(s) on Materials Data Repository (MDR)


    Created at: 2023-07-19 10:50:20 +0900 Updated at: 2026-10-30 09:39:04 +0900

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