Abstract
High-entropy carbides are promising candidates for extreme-temperature environments, but their grain-boundary chemistry remains difficult to resolve because segregation involves both chemical disorder and finite-temperature configurational sampling. Here, we quantify temperature-dependent grain-boundary segregation in high-entropy carbides using a universal message-passing atomic cluster expansion (MACE) machine learning interatomic potential combined with a hybrid Monte Carlo–molecular dynamics workflow. A 53.1 (Formula presented.) (Formula presented.) symmetric tilt grain boundary was sampled for six representative high-entropy carbide compositions containing group IV, V, and VI transition metals at 300 and 2000 K. Element-resolved metal-sublattice composition profiles reveal composition-dependent segregation modes. Several chemistries exhibit selective near-boundary enrichment by one or two dominant metals, including Ti/Zr, Mo/Zr, W/Zr, and Cr/Zr motifs, whereas (Formula presented.) shows persistent multi-element co-segregation. Increasing temperature broadens the segregation profiles and expands the chemically perturbed interfacial region, with secondary metal species contributing more strongly to the near-boundary composition at 2000 K. A Cr-containing composition shows the most pronounced high-temperature response, where Cr-rich segregation is accompanied by boundary broadening, chemical heterogeneity, and structural disordering. These results show that grain-boundary segregation in high-entropy carbides does not follow a single universal trend, but instead depends strongly on carbide chemistry and temperature.
Recommended Citation
M. M. Mou and T. M. Haque and S. E. Daigle and J. Roberts and W. G. Fahrenholtz and J. P. Maria and D. E. Wolfe and E. Zurek and S. Curtarolo and D. W. Brenner, "Finite-Temperature Grain-Boundary Segregation In High-Entropy Carbides," Journal of the American Ceramic Society, vol. 109, no. 7, article no. e71032, Wiley, Jul 2026.
The definitive version is available at https://doi.org/10.1111/jace.71032
Department(s)
Materials Science and Engineering
Publication Status
Open Access
Keywords and Phrases
grain boundary; high-entropy carbides; interfacial chemistry; machine learning interatomic potentials; Monte Carlo–molecular dynamics; segregation
International Standard Serial Number (ISSN)
1551-2916; 0002-7820
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2026 Wiley, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Jul 2026
Comments
Office of Naval Research, Grant N00014-21-1-2515