Gibbs Energy Of Solvation Research Articles

Concentration Scales and Solvation Thermodynamics: Some Theoretical and Experimental Observations Regarding Spontaneity and the Partition Ratio.

The solvation thermodynamics (ST) formalism proposed by A. Ben-Naim is a mathematically rigorous and physically grounded theory for describing properties related to solvation. It considers the solvation process as the transfer of a molecule ("solute") from a fixed position in the ideal gas phase to a fixed position within the solution. Thus, it removes any contribution to the solvation process that is not related to the interactions between this molecule and its environment in the solution. Because ST is based on statistical thermodynamics, the natural variable is number density, which leads to the amount (or "molar") concentration scale. However, this choice of concentration scale is not unique in classical thermodynamics and the solvation properties can be different for commonly used concentration scales. We proposed and performed experiments with diethylamine in a water/hexadecane heterogeneous mixture to confront the predictions of the ST, based on the amount (or "molar") concentration scale, and the Fowler-Guggenheim formalism, based on the mole fraction scale. By means of simple acid-base titration and 1H NMR measurements, it was established that the predictions of differences in the solvation Gibbs energy and the partition ratio (or "partition coefficient") of diethylamine between water and hexadecane are consistent with the ST formalism. Additionally, with current literature data, we have shown additional experimental support for the ST. However, due to the arbitrariness of the relative amount of solvents in the partition ratio, the choice of a single concentration scale within the classical thermodynamics is still not possible.

Solvation Thermodynamics and Its Applications.

In this article, we start by describing a few "definitions" of the solvation processes, which were used in the literature until about 1980. Then, we choose one of these definitions and show that it has a simple molecular interpretation. This fact led to a new definition of the solvation process and the corresponding thermodynamic quantities. The new measure of the solvation Gibbs energy has a simple interpretation. In addition, the thermodynamic quantities associated with the new solvation process have several other advantages over the older measures. These will be discussed briefly in the third section. In the fourth section, we discuss a few applications of the new solvation process.

Theoretical study of the Tetraaminelithium and Tetraaminesodium molecules complexed with H-, Li- and Na- anions: static and dynamic NLO parameters.

This work focuses on the study of six molecules composed of the TetraAmineLithium (TALi+) and TetraAmineSodium (TANa+) structures linked with the anions H-, Li- and Na-. The NLO results obtained by these calculations showed significant values of static first hyperpolarizabilities (βtot) ranging from 8.74 * 10-30 to 691.99 * 10-30 esu. The two molecules TALi-Li and TALi-Na gave the highest values of static βtot equal to 563.20 and 691.99 * 10-30 esu respectively and static second hyperpolarizabilities (γav) of 680.02 and 779.05 * 10-35 esu. The highest dynamic first hyperpolarizabilities (β||) values are around 1474080.00 * 10-30 esu and 6,145,080.00 * 10-30 esu at 720nm lasers and which are attributed to the two molecules TANa-Li and TANa-Na respectively. Four molecules have push-pull behavior where the anions are donor groups, the Li+-NH3 and Na+-NH3 groups are acceptor groups and a bridge composed by the three remaining NH3 ligands. The maximum wavelengths (λmax) in vacuum and in the presence of solvents for all molecules are in the range 240 to 870nm. The software used in this study is Gaussian 16. The optimizations of the molecules were calculated by B3LYP-D3/6-31 + + G(d,p). The static first hyperpolarizability (βtot) was calculated by different functionals: CAM-B3LYP, LC-wPBE, LC-BLYP, M11, wB97X, HSEh1PBE and M06-2X and the MP2 method, the basis-set used is 6-31 + + G(d,p). Other calculations of static βtot were carried out by the CAM-B3LYP functional combined with several basis-sets: 6-31G(d,p), 6-31 + + G(d,p), cc-pVDZ, AUG-cc- pVDZ, 6-311G(d,p), 6-311 + + G(d,p), cc-pVTZ and AUG-cc-pVTZ. The calculations of the first (β||) and second (γ||) hyperpolarizabilities in second harmonic generation (SHG) were calculated by CAM-B3LYP/6-31 + + G(d,p). The delocalization energies (E(2)) were determined by the NBO approach and calculated by the same functional and basis-set cited before. The solvation Gibbs energies (ΔGsolv) were calculated using the implicit SMD model. Maximum wavelengths (λmax) and oscillator strengths ([Formula: see text]) were calculated by TD-CAM-B3LYP/6-31 + + G(d,p) in the presence of the implicit CPCM model.

Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy.

Many challenges persist in developing accurate computational models for predicting solvation free energy (ΔGsol). Despite recent developments in Machine Learning (ML) methodologies that outperformed traditional quantum mechanical models, several issues remain concerning explanatory insights for broad chemical predictions with an acceptable speed-accuracy trade-off. To overcome this, we present a novel supervised ML model to predict the ΔGsol for an array of solvent-solute pairs. Using two different ensemble regressor algorithms, we made fast and accurate property predictions using open-source chemical features, encoding complex electronic, structural, and surface area descriptors for every solvent and solute. By integrating molecular properties and chemical interaction features, we have analyzed individual descriptor importance and optimized our model though explanatory information form feature groups. On aqueous and organic solvent databases, ML models revealed the predictive relevance of solutes with increasing polar surface area and decreasing polarizability, yielding better results than state-of-the-art benchmark Neural Network methods (without complex quantum mechanical or molecular dynamic simulations). Both algorithms successfully outperformed previous ΔGsol predictions methods, with a maximum absolute error of 0.22 ± 0.02 kcal mol-1, further validated in an external benchmark database and with solvent hold-out tests. With these explanatory and statistical insights, they allow a thoughtful application of this method for predicting other thermodynamic properties, stressing the relevance of ML modeling for further complex computational chemistry problems.

Calculating the Gibbs Energy of Solvation of Pyridine in Nonaqueous Solvents

Calculating the Gibbs Energy of Solvation of Pyridine in Nonaqueous Solvents

Calculating the Gibbs Energy of Solvation of Pyridine in Nonaqueous Solvents

Gibbs energies of the solvation of pyridine (Py) in methanol, acetonitrile, and N,N-dimethylformamide are calculated via quantum chemical modeling. Contributions from universal and specific types of interaction between the Py and solvent molecules to the change in the Gibbs energies of solvation of the aromatic heterocycle are determined when alcohol is replaced with aprotic solvents.

Prediction of solvation energies at infinite dilution by the tc-PR cubic equation of state with advanced mixing rule based on COSMO-RS as gE model

The prediction of solvation quantities is an important issue in several fields of chemical and process engineering. In this regard, this work was conducted to increase the prediction power of the equation-of-state (EoS) approach by coupling the tc-PR (translated-consistent Peng-Robinson) EoS with COSMO-RS (Conductor-like Screening Model for Real Solvents) as gE model through an advanced mixing rule. Since the only input parameter of the COSMO-RS model is the charge density (σ) profile of each molecule, the resulting EoS (called tc-PR/COSMO-RS) does not require any binary interaction parameter contrary to other predictive cubic EoS, such as VTPR, PPR78, PSRK, and UMR-PRU. This feature allows the quantification of solvation data of a great number of systems from readily available pure-component properties (critical temperature and pressure, acentric factor and σ -profile). Satisfactory results were obtained for the prediction of solvation Gibbs energy data that were extracted from the extensive CompSol database (the average absolute deviation is 0.30 kcal/mol). The proposed model represents a very flexible alternative for the prediction of solvation data, since it can deal with a large variety of solutes in either a pure or mixed solvent, and for the entire phase diagram (including the supercritical region).

Random Forest Algorithm-Based Prediction of Solvation Gibbs Energies

Random Forest Algorithm-Based Prediction of Solvation Gibbs Energies

Effect of Conformational Equilibrium on Solvation Properties of 1,2-DCE in Water: A Solvation Thermodynamics and 3D-RISM Study.

The contributions of the enthalpy and entropy of solvation for the study of chemical and biological systems are important in the prediction, interpretation, and manipulation of these processes. The relation between solvation Gibbs energies, enthalpies, and entropies of solvation, and their rigorous relation with the conformational equilibrium, are derived for the first time and applied with a computational method, in accordance with the Solvation Thermodynamics previous results, to 1,2-dichloroethane solvation in water. The rigid conformer calculations in solution were performed by using PC+/3D-RISM approach, with the conformational averaged results for enthalpy and solvation Gibbs energy reproducing the experimental results quite successfully. A qualitative agreement in the entropy of solvation predictions was also observed.

Compensation relationship in thermodynamics of solvation and vaporization: Features and applications. II. Hydrogen-bonded systems

There is a well-known extrathermodynamic correlation between the entropies (or Gibbs energies) and enthalpies of many processes, including solvation and vaporization, called the compensation relationship. Non-hydrogen-bonded species, from rare gases to organic non-electrolytes, follow a common correlation between the Gibbs energies and enthalpies of solvation in solvents incapable of self-association. The Gibbs energies of solvation of apolar molecules in hydrogen-bonded solvents and ionic liquids tend to deviate towards the higher values on the compensation plot, which is known to be a manifestation of the solvophobic effect.However, there are more options for hydrogen bonding upon solvation, whose effect on the compensation relationship has not yet been studied, either qualitatively or quantitatively. In this work we classified hydrogen-bonded solute–solvent systems into the three types and quantitatively investigated the deviations arising in each case: 1) apolar solutes solvated in hydrogen-bonded solvents (e.g., octane in water); 2) solutes capable of hydrogen bonding with non-self-associated solvents (chloroform in pyridine); 3) solutes capable of hydrogen bonding with hydrogen-bonded solvents (chloroform in ethanol).Furthermore, we have shown how to predict the solvation enthalpies in various hydrogen-bonded systems, knowing the Gibbs energies of solvation and the molecular structures of the solute and solvent. The agreement between the predicted and literature values (RMS < 1.5 kJ·mol−1, N = 211) confirmed the regularities observed in each case.

Behavior of the aqueous sodium chloride solutions from molecular simulations and theories

Molecular simulations and theories are important tools for studying electrolyte solutions. In this work, molecular dynamics simulations with one of the most widely used force field combination of water and alkali and halide monovalent ion parameters were first conducted for the aqueous sodium chloride solutions to predict density, self-diffusion coefficients and molar conductivity. Then the radial distribution functions were analyzed to obtain the first shell solvation radii and coordination numbers of ions, which were found practically unchanged against concentration. Together with the force field parameters, they were further applied into various molecular theories to predict the Gibbs energy of solvation, static relative permittivity, mean ionic activity coefficients and molar conductivity. It is remarkable to see that the mean ionic activity coefficients and molar conductivity can be predicted with deviations of 1.1 % and 1.4 %, respectively, up to 6 mol/kg H2O.

Solvation Thermodynamics of Solutes in Water and Ionic Liquids Using the Multiscale Solvation-Layer Interface Condition Continuum Model.

Molecular assembly processes are generally driven by thermodynamic properties in solutions. Atomistic modeling can be very helpful in designing and understanding complex systems, except that bulk solvent is very inefficient to treat explicitly as discrete molecules. In this work, we develop and assess two multiscale solvation models for computing solvation thermodynamic properties. The new SLIC/CDC model combines continuum solvent electrostatics based on the solvent layer interface condition (SLIC) with new statistical thermodynamic models for hydrogen bonding and nonpolar modes: cavity formation, dispersion interactions, combinatorial mixing (CDC). Given the structures of 500 solutes, the SLIC/CDC model predicts Gibbs energies of solvation in water with an average accuracy better than 1 kcal/mol, when compared to experimental measurements, and better than 0.8 kcal/mol, when compared to explicit-solvent molecular dynamics simulations. The individual SLIC/CDC energy mode values agree quantitatively with those computed from explicit-solvent molecular dynamics. The previously published SLIC/SASA multiscale model combines the SLIC continuum electrostatic model with the solvent-accessible surface area (SASA) nonpolar energy mode. With our new, improved parametrization method, the SLIC/SASA model now predicts Gibbs energies of solvation with better than 1.4 kcal/mol average accuracy in aqueous systems, compared to experimental and explicit-solvent molecular dynamics, and better than 1.6 kcal/mol average accuracy in ionic liquids, compared to explicit-solvent molecular dynamics. Both models predict solvation entropies, and are the first implicit-solvation models capable of predicting solvation heat capacities.

A comparative study of COSMO-based and equation-of-state approaches for the prediction of solvation energies based on the compsol databank

The computation of solvation energies has many uses in several fields, such as design of separation processes, pharmacology and drug-design, and kinetic modeling. These applications require thermodynamic models capable of accurately predicting solvation energies, accounting for the temperature dependency of this property, and which are fast and robust. Within this framework, we compared two COSMO-based continuum solvation models (COSMO-RS and COSMO-SAC-dsp) with two versions of predictive cubic equations of state well-acknowledged for their efficiency (PSRK and UMR-PRU). For this purpose, a large experimental set of 57,000 datapoints extracted from the COMPSOL databank was considered. Comparisons between computed and experimental data were performed for Gibbs solvation energy and, for the first time in the literature, for both entropy and enthalpy of solvation simultaneously. For simpler binary mixtures, in which hydrogen bonding does not take place, all models were capable of providing accurate predictions, with average absolute deviations below 0.3 kcal/mol regarding the solvation Gibbs energy. For more complex associating mixtures, COSMO-RS showed the best correlation between experimental and calculated data, especially for aqueous systems; among EoS, it is observed that the PSRK model offers the best accuracy.

Dissolving power of the binary solvent carbon tetrachloride – methanol. Solubility of caffeine: Experiment, ASL model, and MD simulation

An experimental and theoretical study of the dissolving power of the binary solvent consisting of inert (carbon tetrachloride) and self-associated (methanol) components has been carried out. According to the experimental data, the dependence of the caffeine solubility on the composition of the binary solvent has a maximum in the region of 0.5 mole fraction of the cosolvent. The maximum is also observed for the concentration dependence of the Gibbs energy of solvation calculated within the framework of molecular dynamics (MD) simulation. Within the framework of the ASL (Associated Solution + Lattice) model, it was shown that the main contribution to solubility is made by the caffeine – methanol heteroassociation. The second largest contribution is defined by non-specific intermolecular interactions in the system. A negative contribution is made by the difference in the sizes of the molecules of the mixture components.

How acid can become a dihydrogen complex in water? A DFT study

To accurate know the acidity of a dihydrogen molecule coordinated to a transition metal ion in water medium is an issue of interest in many areas, from electrochemistry to enzymes and catalysis. However, experimental determination of this magnitude is challenging, and very few values have been reported. In this article we describe a computational protocol, based on DFT calculations and employing a discrete-continuum solvent representation, to estimate pKawater of transition metal dihydrogen complexes. In this approach the number of solvent molecules explicitly included in the calculations is determined by the convergence with the solvation Gibbs energy of the proton in the solvent. The approach has been initially validated with experimental data in tetrahydrofuran (THF) solvent. Using (THF)3 clusters a mean absolute deviation from experiments of only 1.4 pKa unit is achieved. In water the convergence is reached with (H2O)10 clusters. Using them in a discrete-continuum model, the pKawater of twelve dihydrogen complexes experimentally characterized in water have been computed. pKawater values span a wide range, from 23 to -4, illustrating how coordination to a transition metal modifies the dihydrogen acidity. Decomposition of the ∆G of the acid-base equilibrium in two contributions, one intrinsic to the complex and another one accounting for solvent effects enables a deeper analysis of the dihydrogen acidities.

Predicting aqueous solubility by QSPR modeling

The aqueous solubility is predicted here using quantitative structure property relationship (QSPR) models. In this study, we examine whether descriptors that individually yield favorable models for the prediction of the Gibbs energy of solvation and sublimation can be used in combination with octanol-water partition coefficient to produce QSPR models for the prediction of aqueous solubility. Based on this strategy, applied to seven distinct datasets, all models exhibited an R2 greater than 0.7 and Q2 greater than 0.6 for the estimation of aqueous solubility. We also determined how uncoupling the descriptors used to create QSPR models in the prediction of Gibbs energy of sublimation yielded an improved model. Model refinement using an artificial neural network applying the same descriptors generated significantly better models with improved R2 and standard deviation.

Relationship between the Bulk and Surface Basicity of Aliphatic Amines: A Quantum Chemical Approach.

To assess the surface basicity constant (pKb) of aliphatic amine films, the use of a theoretical approach recently developed to evaluate the pKa of carboxylic acid monolayers on the water surface is tested. The present paper gives a new full picture of the change of acid–base properties of surfactants during their aggregation at the air/water interface. The exploited approach is simple because it does not involve the construction of thermodynamic cycles but uses the Gibbs energies of the formation and dimerization of surfactant monomers in neutral and ionized forms in the aqueous and gaseous phases. The quantum chemical semiempirical PM3 method is applied to perform calculations using a conductor-like screening model, which takes into account the aqueous phase. The calculation shows that aliphatic amines, as well as carboxylic acids, are characterized by a change of the value of the basicity/acidity constant during the film formation. The film formation of surfactants leads to a decrease in their acid–base properties, i.e., the surface pKa values of carboxylic acids and pKb values of amines increase. However, unlike carboxylic acids, there is practically no dependence of the surface pKb value on the alkyl chain length of the aliphatic amine, which is caused by almost identical contributions of one CH2 fragment to the solvation Gibbs energy of neutral and ionized monomers within the calculation error. The obtained results agree with existing experimental data.

Semicontinuum (Cluster-Continuum) Modeling of Acid-Catalyzed Aqueous Reactions: Alkene Hydration.

An effort is made to reduce the errors of continuum solvation models (CSMs) with semicontinuum modeling to achieve 3 kcal mol-1 agreement with experiment for acid-catalysis activation Gibbs energies. First, two underappreciated CSM issues are reviewed: errors in the CSM solvation Gibbs energies grow beyond 5 kcal mol-1 (i) as ions are made smaller and (ii) as water clusters grow larger. Second, the computational reproduction of the known Gibbs energies (ΔrG and Δ‡G) of the paradigmatic reaction ethene + H2O + H3O+ → TS+ → ethanol + H3O+ is attempted. It is argued that, despite the >5 kcal mol-1 solvation errors for ions, it is possible to employ error cancellation strategies to reduce the errors in the reaction and activation Gibbs energies to 3 kcal mol-1 accuracy. A new 3 kcal mol-1 effect due to solvent-molecule "placement" (confinement from 1 M bulk concentration) was isolated and proved useful. Third, computational reproduction of the known entropies (ΔrS and Δ‡S) of the paradigmatic reaction is attempted using Trouton's constant and neglect of solvent structure reorganization effects (which must cancel well for this reaction); this worked well for ΔrS but needs empirical correction of ∼11 cal mol-1 K-1 for Δ‡S due to solvent disorientation when H3O+ is consumed. These entropy estimates allow for enthalpy (ΔrH and Δ‡H) estimation from the Gibbs energy values. Fourth, two recommended options, including A + H3O+·2W → [AHOH2+·2W]‡, are shown to also work well for the activations of propene and isobutene.

The SAMPL6 challenge on predicting octanol\u2013water partition coefficients from EC-RISM theory

Results are reported for octanol–water partition coefficients (log P) of the neutral states of drug-like molecules provided during the SAMPL6 (Statistical Assessment of Modeling of Proteins and Ligands) blind prediction challenge from applying the “embedded cluster reference interaction site model” (EC-RISM) as a solvation model for quantum-chemical calculations. Following the strategy outlined during earlier SAMPL challenges we first train 1- and 2-parameter water-free (“dry”) and water-saturated (“wet”) models for n-octanol solvation Gibbs energies with respect to experimental values from the “Minnesota Solvation Database” (MNSOL), yielding a root mean square error (RMSE) of 1.5 kcal mol−1 for the best-performing 2-parameter wet model, while the optimal water model developed for the pKa part of the SAMPL6 challenge is kept unchanged (RMSE 1.6 kcal mol−1 for neutral compounds from a model trained on both neutral and ionic species). Applying these models to the blind prediction set yields a log P RMSE of less than 0.5 for our best model (2-parameters, wet). Further analysis of our results reveals that a single compound is responsible for most of the error, SM15, without which the RMSE drops to 0.2. Since this is the only compound in the challenge dataset with a hydroxyl group we investigate other alcohols for which Gibbs energy of solvation data for both water and n-octanol are available in the MNSOL database to demonstrate a systematic cause of error and to discuss strategies for improvement.

Study on solute-solvent interactions in the aqueous solutions containing guaifenesin drug, sodium chloride and potassium chloride salts in viewpoint of volumetric, electrical conductivity properties and quantum computing

Sodium and potassium ions have an important role in controlling the blood pressure in the body. Potassium ion along with sodium ion regulates the water and the acid-base balances in the tissues and blood. In this work, solute-solvent interactions in the aqueous solutions containing the guaifenesin drug (GG), NaCl and KCl salts were studied. To reach this purpose, the density and electrical conductivity data for GG drug in water and aqueous solutions of NaCl and KCl were measured within salt and drug molality range of (0.05, 0.1, and 0.15) mol kg−1 at T = (298.15, 308.15 and 318.15) K. The apparent molar volumes (Vφ) were calculated from density data. These data were analysed with Redlich–Meyer equation to find the limiting apparent molar volume. The low concentration Chemical Model (lcCM) was used for evaluating the limiting values of the molar conductivity (Λ0), the association constant (Ka) and the standard Gibbs energy for the ion-association process. We also optimized the structures and calculated the Gibbs energies of considered molecules in gas phase with Gaussian 03 W using the Hartree-Fock approximation with 6-311G basis set. Tomasi’s polarized continuum model (PCM) with basis set of 6-311G was used for optimizing and calculating the Gibbs energies of molecules in aqueous phase. The calculated solvation Gibbs energies were used for elucidating the solute-solvent interactions.