MARS: Machine-Learned Force Field Framework for Automated Conformational Sampling, Vibrational Spectroscopy, and Microsolvation.
- DOI
- 10.1021/acs.jctc.6c01588
- Published
- 2026 Nov 10
- Container
- Journal of chemical theory and computation
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acs.jctc.6c01588,
title = {MARS: Machine-Learned Force Field Framework for Automated Conformational Sampling, Vibrational Spectroscopy, and Microsolvation.},
author = {Suárez-Dou S and Gallegos M and Brünig FN and Tkatchenko A},
year = {2026},
journal = {Journal of chemical theory and computation},
doi = {10.1021/acs.jctc.6c01588},
url = {https://doi.org/10.1021/acs.jctc.6c01588}
}RIS
TY - JOUR TI - MARS: Machine-Learned Force Field Framework for Automated Conformational Sampling, Vibrational Spectroscopy, and Microsolvation. AU - Suárez-Dou S AU - Gallegos M AU - Brünig FN AU - Tkatchenko A PY - 2026 JO - Journal of chemical theory and computation DO - 10.1021/acs.jctc.6c01588 UR - https://doi.org/10.1021/acs.jctc.6c01588 ER -
APA
S, S., M, G., FN, B., & A, T. (2026). MARS: Machine-Learned Force Field Framework for Automated Conformational Sampling, Vibrational Spectroscopy, and Microsolvation.. Journal of chemical theory and computation. https://doi.org/10.1021/acs.jctc.6c01588
Source records
- pubmed · retrieved 2026-11-10T19:51:15.327Z