Benchmarking Hartree-Fock and DFT for Molecular Hyperpolarizability: Implications for Evolutionary Design

TL;DR

This study benchmarks Hartree-Fock and DFT methods for predicting molecular hyperpolarizability, showing that certain combinations reliably preserve molecular rankings essential for evolutionary design despite moderate errors.

Contribution

It systematically evaluates multiple functional and basis set combinations, confirming their suitability for evolutionary algorithms in molecular hyperpolarizability prediction.

Findings

HF/3-21G achieves 45.5% mean absolute percentage error.

All tested combinations maintain perfect pairwise ranking.

Larger basis sets reduce percentage error relative to experimental data.

Abstract

Evolutionary algorithms for molecular design require computationally efficient yet accurate fitness functions. We systematically benchmark Hartree-Fock and density functional theory for predicting molecular first hyperpolarizability ($\beta$), evaluating five functionals (HF, PBE0, B3LYP, CAM-B3LYP, M06-2X) across six basis sets against experimental data from five organic push-pull chromophores. For this dataset, HF/3-21G achieves 45.5% mean absolute percentage error with perfect pairwise ranking in 7.4 minutes per molecule. All 30 tested combinations of functional and basis sets maintain perfect pairwise agreement, validating their use as evolutionary fitness functions despite moderate absolute errors. Larger basis sets yield a lower percentage error compared to the experimental values than the difference with the functional. The preservation of pairwise rankings across all combinations of functionals and basis sets provides crucial guidance for evolutionary optimization of nonlinear optical materials.