Empirically Fitted Parameters for Calculating pKa Values with Small Deviations from Experiments Using a Simple...

Area of Science:

• Computational Chemistry
• Physical Chemistry
• Chemical Thermodynamics

Background:

• Accurate prediction of acid-base dissociation constants (pKa) is crucial in chemistry.
• Existing computational methods can be computationally expensive or lack sufficient accuracy.
• A need exists for efficient and reliable methods for pKa estimation.

Purpose of the Study:

• To derive empirically fitted parameters for rapid and accurate pKa calculations.
• To validate the developed parameters across various chemical families and theoretical levels.
• To enable computationally based pKa estimations for unknown species.

Main Methods:

• Empirical fitting of two parameters using least-squares analysis.
• Training sets of 20 molecules for phenols, carboxylic acids, and amines.
• Validation using independent test sets of 10 molecules per family.

Main Results:

• The derived parameters enable fast pKa calculations using Gibbs energy difference (ΔGs(BA)).
• Deviations from experimental pKa values are generally below 0.5 units, except for MP2.
• High accuracy was achieved, with mean unsigned errors below 0.35 pKa units for most tested theories.

Conclusions:

• The developed fitting parameters method offers a reliable approach for pKa prediction.
• This method is expected to aid in estimating pKa values for molecules lacking experimental data.
• Further testing is needed for the reliability of the fitting parameters (FP) method on more complex systems.