Physics-informed AI framework for multiscale design, discovery, and optimization of polymer nanocomposite microstructures using neural operators.
- DOI
- 10.1038/s41598-026-51738-x
- Published
- 2026 May 14
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-51738-x,
title = {Physics-informed AI framework for multiscale design, discovery, and optimization of polymer nanocomposite microstructures using neural operators.},
author = {Lakshmaiya N and Kilari N and Ajay CH and Kaliappan S and Maranan R and Rajendran A and Mammo WD},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-51738-x},
url = {https://doi.org/10.1038/s41598-026-51738-x}
}RIS
TY - JOUR TI - Physics-informed AI framework for multiscale design, discovery, and optimization of polymer nanocomposite microstructures using neural operators. AU - Lakshmaiya N AU - Kilari N AU - Ajay CH AU - Kaliappan S AU - Maranan R AU - Rajendran A AU - Mammo WD PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-51738-x UR - https://doi.org/10.1038/s41598-026-51738-x ER -
APA
N, L., N, K., CH, A., S, K., R, M., A, R., & WD, M. (2026). Physics-informed AI framework for multiscale design, discovery, and optimization of polymer nanocomposite microstructures using neural operators.. Scientific reports. https://doi.org/10.1038/s41598-026-51738-x
Source records
- pubmed · retrieved 2026-09-26T09:46:10.176Z