Machine learning potential as a guide for eutectic in ultra-refractory multicomponent ceramics.

Valiulin VE, Mikheyenkov AV, Chtchelkatchev NM, Levashov EA

DOI: 10.1063/5.0309969
Published: 2026 Feb 7
Container: The Journal of chemical physics
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1063/5.0309969,
  title = {Machine learning potential as a guide for eutectic in ultra-refractory multicomponent ceramics.},
  author = {Valiulin VE and Mikheyenkov AV and Chtchelkatchev NM and Levashov EA},
  year = {2026},
  journal = {The Journal of chemical physics},
  doi = {10.1063/5.0309969},
  url = {https://doi.org/10.1063/5.0309969}
}

RIS

TY  - JOUR
TI  - Machine learning potential as a guide for eutectic in ultra-refractory multicomponent ceramics.
AU  - Valiulin VE
AU  - Mikheyenkov AV
AU  - Chtchelkatchev NM
AU  - Levashov EA
PY  - 2026
JO  - The Journal of chemical physics
DO  - 10.1063/5.0309969
UR  - https://doi.org/10.1063/5.0309969
ER  -

APA

VE, V., AV, M., NM, C., & EA, L. (2026). Machine learning potential as a guide for eutectic in ultra-refractory multicomponent ceramics.. The Journal of chemical physics. https://doi.org/10.1063/5.0309969

Source records

pubmed · retrieved 2026-09-26T23:14:24.220Z
europe-pmc · retrieved 2026-09-26T23:14:24.237Z