Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide

Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide

Abstract Synthesis of high-entropy carbides (HEC) requires high temperatures that can be provided by electric arc plasma method. However, the formation temperature of a single-phase sample remains unknown. Moreover, under some temperatures multi-phase structures can emerge. In this work, we develope...

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Bibliographic Details
Main Authors: Alexander Ya. Pak, Vadim Sotskov, Arina A. Gumovskaya, Yuliya Z. Vassilyeva, Zhanar S. Bolatova, Yulia A. Kvashnina, Gennady Ya. Mamontov, Alexander V. Shapeev, Alexander G. Kvashnin
Format: Article
Language:English
Published: Nature Portfolio 2023-01-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-022-00955-9

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https://doi.org/10.1038/s41524-022-00955-9

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