%0 Journal Article %1 Gebhardt_2020 %A Gebhardt, Julia %A Kiesel, Matthias %A Riniker, Sereina %A Hansen, Niels %D 2020 %I American Chemical Society (ACS) %J Journal of Chemical Information and Modeling %K EXC2075 myown peerReviewed pn3 pn3-8send:unibiblio %N 11 %P 5319--5330 %R 10.1021/acs.jcim.0c00479 %T Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients %U https://doi.org/10.1021%2Facs.jcim.0c00479 %V 60

@article{Gebhardt_2020, added-at = {2020-12-28T18:47:19.000+0100}, author = {Gebhardt, Julia and Kiesel, Matthias and Riniker, Sereina and Hansen, Niels}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/24dcf0d325cff2228be02563086a9c162/niels_hansen}, doi = {10.1021/acs.jcim.0c00479}, interhash = {a022d0658806a9d896eef7dcd2cd4413}, intrahash = {4dcf0d325cff2228be02563086a9c162}, journal = {Journal of Chemical Information and Modeling}, keywords = {EXC2075 myown peerReviewed pn3 pn3-8send:unibiblio}, month = aug, number = 11, pages = {5319--5330}, publisher = {American Chemical Society ({ACS})}, timestamp = {2023-11-28T20:48:56.000+0100}, title = {Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients}, url = {https://doi.org/10.1021%2Facs.jcim.0c00479}, volume = 60, year = 2020 }