Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy
Author:
Affiliation:
1. Department of Chemistry and Biochemistry − Faculty of Sciences, University of Porto - Rua do Campo Alegre, S/N, 4169-007 Porto, Portugal
2. Centre of Chemistry, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
Funder
MIT Portugal
Funda??o para a Ci?ncia e a Tecnologia
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00544
Reference63 articles.
1. Generalized molecular solvation in non-aqueous solutions by a single parameter implicit solvation scheme
2. Delfos: deep learning model for prediction of solvation free energies in generic organic solvents
3. Hybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairs
4. Multisolvent Models for Solvation Free Energy Predictions Using 3D-RISM Hydration Thermodynamic Descriptors
5. MLSolvA: solvation free energy prediction from pairwise atomistic interactions by machine learning
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