How to Predict the pKa of Any Compound in Any Solvent

Kuvaus

Summary of all compounds including their IUPAC names, scaling relations for correcting the implicit solvation models and the errors associated with them, all computed pKa’s in all considered solvents, the used solvatochromic parameters, proton solvation energies in water and nonaqueous solvents, relative stability of all considered tautomers, total Gibbs Free energies of all compounds, results of the cross validation (XLS) Acid–base properties of molecules in nonaqueous solvents are of critical importance for almost all areas of chemistry. Despite this very high relevance, our knowledge is still mostly limited to the pKa of rather few compounds in the most common solvents, and a simple yet truly general computational procedure to predict pKa’s of any compound in any solvent is still missing. In this contribution, we describe such a procedure. Our method requires only the experimental pKa of a reference compound in water and a few standard quantum-chemical calculations. This method is tested through computing the proton solvation energy in 39 solvents and by comparing the pKa of 142 simple compounds in 12 solvents. Our computations indicate that the method to compute the proton solvation energy is robust with respect to the detailed computational setup and the construction of the solvation model. The unscaled pKa’s computed using an implicit solvation model on the other hand differ significantly from the experimental data. These differences are partly associated with the poor quality of the experimental data and the well-known shortcomings of implicit solvation models. General linear scaling relationships to correct this error are suggested for protic and aprotic media. Using these relationships, the deviations between experiment and computations drop to a level comparable to that observed in water, which highlights the efficiency of our method.
Näytä enemmän

Julkaisuvuosi

2022

Aineiston tyyppi

Tekijät

Department of Chemistry and Materials Science

Elisabet Ahlberg - Tekijä

Ernst Ahlberg - Tekijä

Kari Laasonen Orcid -palvelun logo - Tekijä

Michael Busch - Tekijä

Universal Prediction AB - Muu tekijä

University of Gothenburg - Muu tekijä

Uppsala University - Muu tekijä

figshare - Julkaisija

Projekti

Muut tiedot

Tieteenalat

Kemia

Kieli

Saatavuus

Avoin

Lisenssi

Creative Commons Nimeä EiKaupallinen 4.0 Kansainvälinen (CC BY NC 4.0)

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