Data-driven discovery of ultrahigh specific hardness alloys

Data-driven discovery of advanced alloys using experimental data is challenging due to the difficulty of obtaining large and reliable experimental datasets, the vastness of the compositional design space, and the risk of overfitting machine learning (ML) models. This study employed an iterative proc...

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Detalles Bibliográficos

Principais autores:	Taeyeop Kim, Wook Ha Ryu, Geun Hee Yoo, Donghyun Park, Ji Young Kim, Eun Soo Park, Dongwoo Lee
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2024-11-01
Series:	Journal of Materials Research and Technology
Assuntos:	Data-driven materials sciences Complex concentrated alloys Combinatorial experiments Nanoindentation Specific hardness
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S2238785424026814
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