Prediction of Relative Kinetic Solvent Effects for SN2 Reactions Using COSMO-RS.

Evaluating PBE-D3/M06 for copper-catalyzed carbon chemistry: Kinetic barriers and mechanistic insights.

Accurate prediction of activation barriers is essential for reliable mechanistic modeling of copper-catalyzed carbon conversion reactions yet remains challenging for conventional density functional theory. Here, we evaluate a hybrid PBE-D3/M06 approach for reaction kinetics on low-index Cu(100), Cu(110), and Cu(111) surfaces. Benchmarking against experimental barriers for seven representative elementary reactions shows that PBE-D3/M06 achieves near-chemical accuracy, with a mean absolute error and root mean square error of 0.06 eV, substantially outperforming PBE and RPBE. The method also reproduces embedded CASPT2 trends for C-C coupling on Cu(111), correctly identifying COH*-CHO* coupling as both kinetically and thermodynamically preferred. Applied to CO2 hydrogenation to methanol on Cu(111), PBE-D3/M06 indicates that the formate-mediated pathway is favored, with HCOOH* hydrogenation as the rate-determining step. This work suggests that PBE-D3/M06 is a promising framework for modeling elementary steps in copper-catalyzed carbon chemistry.

Determination of the Acid Dissociation Constant of Succinic Acid in Aqueous Solvent using Density Functional Theory and a Continuum Solvation Model

Determination of the Formation Constants of Copper(II) Complexes Using Quantum Chemical Calculations

Gibbs free energy values obtained from quantum-chemical calculations were used to determine the formation constants of homo- and heteroligand copper(II) complexes with various ligands (amino acids, diimines, and phosphorylated dithiocarbamates) in an aqueous medium. A computationally robust, yet moderately expensive, level of theory—B3LYP/def2-TZVPPD—was employed. Solvent effects were accounted for using two models: C-PCM and SMD. A key prerequisite for obtaining reliable results is the use of a reference complex with a known formation constant that is structurally and solvation-wise similar to the compound under study. In this context, “similarity” implies identical stoichiometry, the same coordination number, the same number of water molecules in the inner coordination sphere; matching charges, however, is considerably less critical. The importance of considering conformers and isomers to obtain the most accurate values is demonstrated. The more rigid the structure and the greater the degree of similarity between the studied and reference compounds, the better the agreement between calculated and experimental data; the discrepancy can be as low as 0.1–0.2 logarithmic units. When an appropriate reference is selected, the average deviation of the calculated stability constants is less than 1 logarithmic unit.

Acidity Determination by Spectroscopic and Modeling Methods in Monohydroxy- and Dihydroxy-Substituted Coumarins.

We report the pKa values for 15 mono- and disubstituted hydroxycoumarins determined using UV-vis absorbance spectroscopy and computational methods. Six of these values, including the pKa of 5-hydroxycoumarin, are reported for the first time. While the primary focus is on the effects of hydroxyl substitution on the benzene ring, we also examine how a 4-methyl substituent may influence acidity in a subset of four coumarin pairs. The experimental results are supported by two kinds of density functional theory calculations. Time-dependent DFT (TD-DFT) models of the UV-vis spectra show strong agreement with experimental observations of 30 species and facilitate spectral interpretation. In addition, pKa values are predicted through a thermodynamic-cycle calculation that combines gas-phase Gibbs free energies with solvation free energies. This computational method accurately reproduces pKa values for a training set (mean absolute error, MAE = 0.37) and yields predictions for the full experimental data set (MAE = 0.65). Together, the experimental and computational results provide a comprehensive view of the structure-acidity relationships in a diverse series of simple hydroxycoumarins.

COSMOSol: efficient solvent screening for polymer additives with open-source COSMO-SAC

Recycling polymers with solvents requires removing additives efficiently—yet for most of the hundreds of additives used industrially, the efficiency of various solvents to dissolve them is unknown, particularly due to the scarcity of experimental solubility data. This work proposes a systematic computational approach using the quantum mechanics-aided open-source COSMO-SAC model to screen solvents and requires only the fusion data of the additive as external input, or even no empirical input. To validate the method, we compiled solubility measurements for five representative additives across diverse solvent classes. Quantitatively, predictions typically fall within 0.5 log units of measured values (in mole fraction) and, more importantly, qualitatively correctly identify both the best and worst solvent types for each additive. Furthermore, we examined how different modeling choices affect predictions: for instance, values of fusion properties, molecular conformation and σ-profile of the additive, and dispersive interactions. When fusion data are unavailable, the infinite-dilution activity coefficient provides rankings comparable to those obtained from calculated equilibrium solubilities, particularly for poorly soluble additives. Minor limitations of the approach were observed in cases where solvents are structurally very similar—here, fine distinctions between them can be affected by interference from other effects or model simplifications. However, for choosing between different solvent classes—the decision that matters most in practice—the rankings prove robust. We additionally benchmarked COSMO-SAC against HANNA, a machine-learning activity-coefficient model: the two yield comparable solvent rankings. To facilitate reproducibility and extension of this work, we provide COSMOSol, a Python toolset containing all workflows and data. The method offers a practical, first-principles route to solvent screening—not only for polymer additives, but potentially for other compound classes where experimental data are lacking.

1H NMR-Based Framework for Estimating Molecular Formation Enthalpies of Organic Compounds

We report a method for estimating standard enthalpies of formation (ΔHf°) directly from routine 1H NMR spectra. By combining spectral features with heteroatom-based functional motifs, accurate models were obtained (R2 ≈ 0.99; RMSE ≈ 5.5 kcal mol–1). The predictive performance was consistent across multiple validation approaches and comparable to established group contribution methods, while avoiding the need for knowledge of compound structure. The obtained formation enthalpies further enabled reasonable estimation of reaction enthalpies for representative organic transformations. Overall, the results demonstrate that routinely accessible NMR observables capture trends associated with molecular thermodynamic stability.