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PreprintLicence not statedChemRxiv

Applicability Domain of Universal Machine Learning Interatomic Potentials at Solid-State Battery Interfaces

  • Umang Agarwal1
  • Mengke Li1
  • Gopalakrishnan Sai Gautam2,3
  • Zeyu Deng1
  1. 1Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore, 117575
  2. 2Department of Materials Engineering
  3. 3Indian Institute of Science
Open at sourceDOICite

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Cite

BibTeXRIS
BibTeX
@misc{agarwal2026applicability,
  title = {{Applicability Domain of Universal Machine Learning Interatomic Potentials at Solid-State Battery Interfaces}},
  author = {Umang Agarwal and Mengke Li and Gopalakrishnan Sai Gautam and Zeyu Deng},
  howpublished = {ChemRxiv},
  year = {2026},
  month = nov,
  doi = {10.26434/chemrxiv.15011777/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011777/v1},
}
RIS
TY  - UNPB
TI  - Applicability Domain of Universal Machine Learning Interatomic Potentials at Solid-State Battery Interfaces
AU  - Umang Agarwal
AU  - Mengke Li
AU  - Gopalakrishnan Sai Gautam
AU  - Zeyu Deng
PY  - 2026
DA  - 2026/11/05
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15011777/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011777/v1
ER  -