Explaining and Fixing DFT Failures for Torsional Barriers

TL;DR

This paper investigates the failure of standard DFT functionals in predicting certain torsional barriers, identifies the causes related to delocalization errors, and demonstrates that using Hartree-Fock densities significantly improves accuracy.

Contribution

The study provides a comprehensive database of torsional barriers, analyzes the causes of DFT failures, and shows that HF-DFT methods, especially HF-PBE0, effectively fix these issues.

Findings

DFT errors are linked to delocalization caused by hyperconjugation.

HF-DFT significantly improves torsional barrier predictions.

HF-PBE0 offers the best overall performance.

Abstract

Most torsional barriers are predicted to high accuracy (about 1kJ/mol) by standard semilocal functionals, but a small subset has been found to have much larger errors. We create a database of almost 300 carbon-carbon torsional barriers, including 12 poorly behaved barriers, all stemming from Y=C-X group, where X is O or S, and Y is a halide. Functionals with enhanced exchange mixing (about 50%) work well for all barriers. We find that poor actors have delocalization errors caused by hyperconjugation. These problematic calculations are density sensitive (i.e., DFT predictions change noticeably with the density), and using HF densities (HF-DFT) fixes these issues. For example, conventional B3LYP performs as accurately as exchange-enhanced functionals if the HF density is used. For long-chain conjugated molecules, HF-DFT can be much better than exchange-enhanced functionals. We suggest that HF-PBE0 has the best overall performance.