Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

We present a group contribution method (SoluteGC) and a machine learning model (SoluteML) to predict the Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The proposed group contribution method uses atom-centered functional groups with corrections for ring and polycyclic strain whilst the machine learning models adopt a directed message passing neural network. The solute parameters predicted from SoluteGC and SoluteML are used to calculate solvation energy and enthalpy via linear free energy relationships. Extensive data sets containing 8366 solute parameters, 20253 solvation free energies, and 6322 solvation enthalpies are compiled in this work to train the models. The three models are each evaluated on the same test sets using both random and substructure-based solute splits for solvation energy and enthalpy predictions. The results show that the DirectML model is superior to the SoluteML and SoluteGC models for both predictions and can provide accuracy comparable to that of advanced quantum chemistry methods. Yet, even though the DirectML model performs better in general, all three models are useful for various purposes. Uncertain predicted values can be identified by comparing the 3 models, and when the 3 models are combined together, they can provide even more accurate predictions than any one of them individually. Finally, we present our compiled solute parameter, solvation energy, and solvation enthalpy databases (SoluteDB, dGsolvDBx, dHsolvDB) and provide public access to our final prediction models through a simple web-based tool, software package, and source code.

Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

We present a group contribution method (SoluteGC) and a machine learning model (SoluteML) to predict the Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The proposed group contribution method uses atom-centered functional groups with corrections for ring and polycyclic strain whilst the machine learning models adopt a directed message passing neural network. The solute parameters predicted from SoluteGC and SoluteML are used to calculate solvation energy and enthalpy via linear free energy relationships. Extensive data sets containing 8366 solute parameters, 20253 solvation free energies, and 6322 solvation enthalpies are compiled in this work to train the models. The three models are each evaluated on the same test sets using both random and substructure-based solute splits for solvation energy and enthalpy predictions. The results show that the DirectML model is superior to the SoluteML and SoluteGC models for both predictions and can provide accuracy comparable to that of advanced quantum chemistry methods. Yet, even though the DirectML model performs better in general, all three models are useful for various purposes. Uncertain predicted values can be identified by comparing the 3 models, and when the 3 models are combined together, they can provide even more accurate predictions than any one of them individually. Finally, we present our compiled solute parameter, solvation energy, and solvation enthalpy databases (SoluteDB, dGsolvDBx, dHsolvDB) and provide public access to our final prediction models through a simple web-based tool, software package, and source code.

Thermochemistry of Solution, Solvation, and Hydrogen Bonding of Cyclic Amides in Proton Acceptor and Donor Solvents. Amide Cycle Size Effect

In the present work, the thermochemistry of solution, solvation, and hydrogen bonding of cyclic amides in proton acceptor (B) and proton donor (RXH) solvents were studied. The infinite dilution solution enthalpies of δ-valerolactam, N-methylvalerolactam, ε-caprolactam, and N-methylcaprolactam were measured at 298.15 K. The solvation enthalpies of cyclic amides were calculated based on the measured solution enthalpies and sublimation/vaporization enthalpies from literature. The enthalpies of hydrogen bonding between cyclic amides and proton acceptor and donor solvents were then calculated as a difference between the total solvation enthalpy and the non-specific contribution. The latter was estimated via two different approaches in proton donor and proton accepting solvents. The effect of the cycle size on the strength of hydrogen bonding of the cyclic amides in solution is discussed.

Solvation enthalpy of uranium tetrachloride in aqueous-alcohols mixed solvents

The process of interaction between ions of a solute and the molecules of the solvent through relatively weak covalent bonds is called solvation. It involves evening out a concentration gradient and evenly distributing the solute molecules within the solvent. Hydration is a special case of solvation when the solvent molecules are water. Solvation energy, generally, is the energy released when ions in crystal lattices associate with molecules in a solvent, however it can be positive or negative, depending upon the combined effects of lattice and hydration energies in case of aqueous-ionic solid dissolution. Uranous chloride or uranium tetrachloride (UCl4) is a green crystalline solid which sublimes in vacuum at 500°C/10-3 mm. It is a Lewis acid and hence dissolves in solvents which can act as non-protic Lewis bases. Although dissolution of uranium tetrachloride crystals in water is an exothermic process yielding a green solution which is fairly stable in the cold, yet is hydrolyzed to a considerable extent to furnish an acidic reaction. Solvation enthalpies of quadrivalent uranium system have been scantly reported. The present communication deals with the calculation of enthalpy of solution of uranium tetrachloride in aqueous-non-aqueous solvent mixtures, particularly in 10 and 20 weight (wt) % methyl alcohol-water and ethyl alcohol-water systems at 25°C calorimetrically and thereby estimating the solvation enthalpy of UCl4 in the said media.