Skip to content
DraconiticResearch
Search Sources API
203,948 studies31 sourcesUpdated 26 min ago
PreprintLicence not statedChemRxiv

Accurate and Rapid Vibrational Spectra of Molecular Crystals from Machine-Learned Interatomic Potentials

Related

  1. How accurate are foundational machine learning interatomic potentials for heterogeneous catalysis?
    Luuk H. E. Kempen, Raffaele Cheula, Mie Andersen
    The Journal of Chemical PhysicsPeer-reviewedLicence not statedFull text9 citedMaterials & polymersOpenAlex
  2. FACTO: fast atom-centered tensor operator for accurate and efficient foundational machine-learned interatomic potentials
    Siyuan Liu, Chang Han, Sheng Gong +6
    arXivPreprintCC BY-SA 4.0Full textPhysical chemistryarXiv
  3. Universal Interatomic Potentials as Configuration-Space Generators for One-Shot and Iterative Fine-Tuning of Ab Initio-Accurate Material-Specific Models
    Jonas Hänseroth, Aaron Flötotto, Christian Dreßler
    arXivPreprintarXiv licenceFull textPhysical chemistryCondensed matterarXiv
  4. A Divide-and-Conquer Embedded Correlated Wavefunction Transfer Learning Approach for Chemically Accurate Condensed-Phase Interatomic Potentials: Liquid Water as a Test Case.
    Xuezhi Bian, Emily A Carter
    The journal of physical chemistry lettersPeer-reviewedCC BYFull textMaterials & polymersEurope PMC
  5. Accurate, transferable, and verifiable machine-learned interatomic potentials for layered materials
    Johnathan D. Georgaras, Akash Ramdas, Chung Hsuan Shan +4
    Nature CommunicationsPeer-reviewedCC BY-NC-NDFull text8 citedMaterials & polymersOpenAlex
BibTeX
@misc{petrov2026accurate,
  title = {{Accurate and Rapid Vibrational Spectra of Molecular Crystals from Machine-Learned Interatomic Potentials}},
  author = {Maria Petrov and Johanna Kölbel and William B. Stoll and Michael T. Ruggiero},
  howpublished = {ChemRxiv},
  year = {2026},
  month = nov,
  doi = {10.26434/chemrxiv.15011775/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011775/v1},
}
RIS
TY  - UNPB
TI  - Accurate and Rapid Vibrational Spectra of Molecular Crystals from Machine-Learned Interatomic Potentials
AU  - Maria Petrov
AU  - Johanna Kölbel
AU  - William B. Stoll
AU  - Michael T. Ruggiero
PY  - 2026
DA  - 2026/11/05
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15011775/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011775/v1
ER  -