A Statistically Supported Antioxidant Activity DFT Benchmark-The Effects of Hartree-Fock Exchange and Basis Set Selection on Accuracy and Resources Uptake

Polyphenolic compounds are now widely studied using computational chemistry approaches, the most popular of which is Density Functional Theory. To ease this process, it is critical to identify the optimal level of theory in terms of both accuracy and resource usage-a challenge we tackle in this study. Eleven DFT functionals with varied Hartree-Fock exchange values, both global and range-separated hybrids, were combined with 14 differently augmented basis sets to calculate the reactivity indices of caffeic acid, a phenolic acid representative, and compare them to experimental data or a high-level of theory outcome. Aside from the main course, a validation of the widely used Janak's theorem in the establishment of vertical ionization potential and vertical electron affinity was evaluated. To investigate what influences the values of the properties under consideration, linear regression models were developed and thoroughly discussed. The results were utilized to compute the scores, which let us determine the best and worst combinations and make broad suggestions on the final option. The study demonstrates that M06-2X/6-311G(d,p) is the best fit for such research, and, curiously, it is not necessarily essential to include a diffuse function to produce satisfactory results.

Automated summary

This study aims to identify the optimal level of theory for computational chemistry research on polyphenolic compounds, exploring different combinations of DFT functionals and basis sets to find the best fit. The research also evaluates the application of Janak's theorem in vertical ionization potential and electron affinity, and analyzes the factors influencing the properties through linear regression models.