Abstract
Semi-empirical quantum-chemical methods such as extended tight-binding (xTB) models are widely used for large-scale simulations. Despite their popularity, their accuracy for transition-metal containing systems is lower than, for example, closed-shell organic molecules. In this work, we extend the Q-Chem-xTB framework with a geometric direct minimization (GDM) scheme for robust self-consistent convergence and Hubbard correction (+ (Formula presented.)) to improve the description of local interactions and reduce self-interaction errors similar to those characteristic of density-functional theory calculations for transition-metal complexes. The Hubbard correction term is integrated self-consistently within the xTB Hamiltonian, allowing shell-specific (Formula presented.) values for each atom. The performance of Q-Chem-xTB+ (Formula presented.) is assessed for four benchmark sets of iron complexes, focusing on their spin-state energetics. Sensitivity and optimization analyses of the spin parameters show that parameter tuning alone cannot systematically reduce the error or consistently recover correct spin ground-state predictions across different datasets. In contrast, introducing the + (Formula presented.) correction yields significant error reduction and improved electronic linearity with respect to fractional occupation, demonstrating that the correction fulfills its intended role of reducing self-interaction error. However, the optimized (Formula presented.) values remain system-dependent, and the resulting improvements are only partially transferable. As a side effect, the + (Formula presented.) correction stabilizes the self-consistent field optimization by widening the HOMO–LUMO gap, thereby overcoming convergence instabilities of the conventional direct inversion of the iterative subspace (DIIS) scheme at low electronic temperatures.
| Original language | English |
|---|---|
| Article number | e70346 |
| Journal | Journal of Computational Chemistry |
| Volume | 47 |
| Issue number | 7 |
| DOIs | |
| State | Published - 15 Mar 2026 |
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