Melting simulations of high-entropy carbonitrides by deep learning potentials

Abstract The melting temperature is a crucial property of materials that determines their potential applications in different industrial fields. In this study, we used a deep neural network potential to describe the structure of high-entropy (TiZrTaHfNb)CxN1−x carbonitrides (HECN) in both solid and...

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Bibliographic Details
Main Authors: Viktor S. Baidyshev, Christian Tantardini, Alexander G. Kvashnin
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-78377-4
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