The Shear-Bond Descriptor and Universal Machine-Learning Potential Enable Large-Scale Discovery of Negative Thermal Expansion Materials.
- DOI
- 10.1021/jacs.6c07432
- Published
- 2026 Oct 28
- Container
- Journal of the American Chemical Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/jacs.6c07432,
title = {The Shear-Bond Descriptor and Universal Machine-Learning Potential Enable Large-Scale Discovery of Negative Thermal Expansion Materials.},
author = {Chen G and Tian S and Feng K and Liu Y and Yin W and Gao Q and Zhou K},
year = {2026},
journal = {Journal of the American Chemical Society},
doi = {10.1021/jacs.6c07432},
url = {https://doi.org/10.1021/jacs.6c07432}
}RIS
TY - JOUR TI - The Shear-Bond Descriptor and Universal Machine-Learning Potential Enable Large-Scale Discovery of Negative Thermal Expansion Materials. AU - Chen G AU - Tian S AU - Feng K AU - Liu Y AU - Yin W AU - Gao Q AU - Zhou K PY - 2026 JO - Journal of the American Chemical Society DO - 10.1021/jacs.6c07432 UR - https://doi.org/10.1021/jacs.6c07432 ER -
APA
G, C., S, T., K, F., Y, L., W, Y., Q, G., & K, Z. (2026). The Shear-Bond Descriptor and Universal Machine-Learning Potential Enable Large-Scale Discovery of Negative Thermal Expansion Materials.. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.6c07432
Source records
- pubmed · retrieved 2026-11-10T11:15:33.272Z