Tackling complexity in crystal structure determination of metal organic compounds using machine learning interatomic potentials.

Wu H, Zhu Q, Zhou W

DOI: 10.1039/d6cc01457g
Published: 2026 Jun 11
Container: Chemical communications (Cambridge, England)
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1039/d6cc01457g,
  title = {Tackling complexity in crystal structure determination of metal organic compounds using machine learning interatomic potentials.},
  author = {Wu H and Zhu Q and Zhou W},
  year = {2026},
  journal = {Chemical communications (Cambridge, England)},
  doi = {10.1039/d6cc01457g},
  url = {https://doi.org/10.1039/d6cc01457g}
}

RIS

TY  - JOUR
TI  - Tackling complexity in crystal structure determination of metal organic compounds using machine learning interatomic potentials.
AU  - Wu H
AU  - Zhu Q
AU  - Zhou W
PY  - 2026
JO  - Chemical communications (Cambridge, England)
DO  - 10.1039/d6cc01457g
UR  - https://doi.org/10.1039/d6cc01457g
ER  -

APA

H, W., Q, Z., & W, Z. (2026). Tackling complexity in crystal structure determination of metal organic compounds using machine learning interatomic potentials.. Chemical communications (Cambridge, England). https://doi.org/10.1039/d6cc01457g

Source records

pubmed · retrieved 2026-11-10T07:40:11.382Z