Physics-Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel.

Wei X, Li Y, Wang C, Wang L, Song X, Mao K, Zhang Y, Xu W

DOI: 10.1002/advs.75515
Published: 2026 Jun 15
Container: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/advs.75515,
  title = {Physics-Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q\&P Steel.},
  author = {Wei X and Li Y and Wang C and Wang L and Song X and Mao K and Zhang Y and Xu W},
  year = {2026},
  journal = {Advanced science (Weinheim, Baden-Wurttemberg, Germany)},
  doi = {10.1002/advs.75515},
  url = {https://doi.org/10.1002/advs.75515}
}

RIS

TY  - JOUR
TI  - Physics-Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel.
AU  - Wei X
AU  - Li Y
AU  - Wang C
AU  - Wang L
AU  - Song X
AU  - Mao K
AU  - Zhang Y
AU  - Xu W
PY  - 2026
JO  - Advanced science (Weinheim, Baden-Wurttemberg, Germany)
DO  - 10.1002/advs.75515
UR  - https://doi.org/10.1002/advs.75515
ER  -

APA

X, W., Y, L., C, W., L, W., X, S., K, M., Y, Z., & W, X. (2026). Physics-Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel.. Advanced science (Weinheim, Baden-Wurttemberg, Germany). https://doi.org/10.1002/advs.75515

Source records

pubmed · retrieved 2026-09-27T07:22:47.621Z