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PreprintLicence not statedChemRxiv

Accuracy, Reliability, and Efficiency of a MACE Machine-Learning Interatomic Potential for Aspirin: A Reproducible Benchmark for Molecular Simulation

  • Modupe A. Omoniyi1,2
  1. 1Department of Chemistry
  2. 2University of Vermont
Open at sourceDOICite

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Cite

BibTeXRIS
BibTeX
@misc{omoniyi2026accuracy,
  title = {{Accuracy, Reliability, and Efficiency of a MACE Machine-Learning Interatomic Potential for Aspirin: A Reproducible Benchmark for Molecular Simulation}},
  author = {Modupe A. Omoniyi},
  howpublished = {ChemRxiv},
  year = {2026},
  month = oct,
  doi = {10.26434/chemrxiv.15011308/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011308/v1},
}
RIS
TY  - UNPB
TI  - Accuracy, Reliability, and Efficiency of a MACE Machine-Learning Interatomic Potential for Aspirin: A Reproducible Benchmark for Molecular Simulation
AU  - Modupe A. Omoniyi
PY  - 2026
DA  - 2026/10/30
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15011308/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011308/v1
ER  -