OPERA: A Unified Framework for AI-Assisted Polymer Metamaterial Design Through Operator Learning, Physics Embedding, and Normalizing-Flow Inverse Architecture.
- DOI
- 10.3390/polym18141733
- Published
- 2026 Jul 15
- Container
- Polymers
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3390/polym18141733,
title = {OPERA: A Unified Framework for AI-Assisted Polymer Metamaterial Design Through Operator Learning, Physics Embedding, and Normalizing-Flow Inverse Architecture.},
author = {Enakoutsa K and Giorgio I},
year = {2026},
journal = {Polymers},
doi = {10.3390/polym18141733},
url = {https://doi.org/10.3390/polym18141733}
}RIS
TY - JOUR TI - OPERA: A Unified Framework for AI-Assisted Polymer Metamaterial Design Through Operator Learning, Physics Embedding, and Normalizing-Flow Inverse Architecture. AU - Enakoutsa K AU - Giorgio I PY - 2026 JO - Polymers DO - 10.3390/polym18141733 UR - https://doi.org/10.3390/polym18141733 ER -
APA
K, E., & I, G. (2026). OPERA: A Unified Framework for AI-Assisted Polymer Metamaterial Design Through Operator Learning, Physics Embedding, and Normalizing-Flow Inverse Architecture.. Polymers. https://doi.org/10.3390/polym18141733
Source records
- pubmed · retrieved 2026-11-10T07:10:02.079Z
- europe-pmc · retrieved 2026-11-10T07:10:02.078Z