Can Machine Learning Predict Solvation Effects on Energies and Geometries of Highly Charged Molecules?

Baum D, Visscher L, Pausch A.

DOI: 10.1021/acs.jctc.6c00804
Published: 2026-10-01
Container: J Chem Theory Comput
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jctc.6c00804,
  title = {Can Machine Learning Predict Solvation Effects on Energies and Geometries of Highly Charged Molecules?},
  author = {Baum D and  Visscher L and  Pausch A.},
  year = {2026},
  journal = {J Chem Theory Comput},
  doi = {10.1021/acs.jctc.6c00804},
  url = {https://doi.org/10.1021/acs.jctc.6c00804}
}

RIS

TY  - JOUR
TI  - Can Machine Learning Predict Solvation Effects on Energies and Geometries of Highly Charged Molecules?
AU  - Baum D
AU  -  Visscher L
AU  -  Pausch A.
PY  - 2026
JO  - J Chem Theory Comput
DO  - 10.1021/acs.jctc.6c00804
UR  - https://doi.org/10.1021/acs.jctc.6c00804
ER  -

APA

D, B., L, V., & A., P. (2026). Can Machine Learning Predict Solvation Effects on Energies and Geometries of Highly Charged Molecules?. J Chem Theory Comput. https://doi.org/10.1021/acs.jctc.6c00804

Source records

europe-pmc · retrieved 2026-11-10T11:23:48.092Z