Generative design of high-fidelity microstructures using physics-aware machine learning
- DOI
- 10.1038/s41467-026-78118-3
- Published
- 2026-09-30
- Container
- Nature Communications
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41467-026-78118-3,
title = {Generative design of high-fidelity microstructures using physics-aware machine learning},
author = {Weijie Liao and Kaidi Li and Bin Tang and Jiangkun Fan and Jun Wang and Xiangyi Xue and Jinshan Li and Ruihao Yuan},
year = {2026},
journal = {Nature Communications},
doi = {10.1038/s41467-026-78118-3},
url = {https://doi.org/10.1038/s41467-026-78118-3}
}RIS
TY - JOUR TI - Generative design of high-fidelity microstructures using physics-aware machine learning AU - Weijie Liao AU - Kaidi Li AU - Bin Tang AU - Jiangkun Fan AU - Jun Wang AU - Xiangyi Xue AU - Jinshan Li AU - Ruihao Yuan PY - 2026 JO - Nature Communications DO - 10.1038/s41467-026-78118-3 UR - https://doi.org/10.1038/s41467-026-78118-3 ER -
APA
Liao, W., Li, K., Tang, B., Fan, J., Wang, J., Xue, X., Li, J., & Yuan, R. (2026). Generative design of high-fidelity microstructures using physics-aware machine learning. Nature Communications. https://doi.org/10.1038/s41467-026-78118-3
Source records
- crossref · retrieved 2026-11-10T14:34:49.027Z