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Calculation of Solute Partition Coefficient Using the A-P Scheme

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Machine Learning Solvation Environments in Conductive Polymers: Application to ProDOT-2Hex with Solvent Swelling

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From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

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Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

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Atomic Neural Network for Calculation of Solvation Free Energies in Organic Solvents

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A Solvent Selection Framework for Porous Organic Polymers

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Enhancing Accuracy and Feature Insights in Hydration Free Energy Predictions for Small Molecules with Machine Learning

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Chemical accuracy prediction of molecular solvation and partition in ionic liquids with educated estimators

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Machine Learning with Physically Inspired Descriptors to Predict Solvation Free Energies of Neutral and Ionic Solutes in Aqueous and Nonaqueous Solvents

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High-Energy and Long-Lasting Organic Electrode for a Rechargeable Aqueous Battery

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DeepBBBP: High Accuracy Blood‐brain‐barrier Permeability Prediction with a Mixed Deep Learning Model

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Something for nothing: improved solvation free energy prediction with $${\Delta }$$-learning

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Predicting solvation free energies with an implicit solvent machine learning potential

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Machine Learning for Chemical Reactions

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Comprehensive modelling of pharmaceutical solvation energy in different solvents

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Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning

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Multisolvent Models for Solvation Free Energy Predictions Using 3D-RISM Hydration Thermodynamic Descriptors

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Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy

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Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks

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Factor analysis of error in oxidation potential calculation: A machine learning study

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Current and future machine learning approaches for modeling atmospheric cluster formation

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A Two‐Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies

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Hydration‐Free Energies for Small Molecules With Physics‐Based Descriptors: Graph Neural Network With Cross‐Attention

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Machine Learning-Guided Approach for Studying Solvation Environments

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Transfer learning for solvation free energies: From quantum chemistry to experiments

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Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks

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IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method

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Enhanced Immune Response Against Echinococcus Granulosus Through a CTLA-4/B7 Affinity-Based Vaccine

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SUSSOL—Using Artificial Intelligence for Greener Solvent Selection and Substitution

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Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning

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Modeling Solvatochromic Effect by a Two-Step Machine Learning Approach for Organic Chromophores

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Modeling of the Crystallization Conditions for Organic Synthesis Product Purification Using Deep Learning

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Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures

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Data-Centric Development of Lignin Structure–Solubility Relationships in Deep Eutectic Solvents Using Molecular Simulations

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Molecular Design Learned from the Natural Product Porphyra-334: Molecular Generation via Chemical Variational Autoencoder versus Database Mining via Similarity Search, A Comparative Study

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Graph Information Bottleneck-Based Dual Subgraph Prediction for Molecular Interactions

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