Spin parameter optimization for spin-polarized extended tight-binding methods,Journal of Computational Chemistry

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Spin parameter optimization for spin-polarized extended tight-binding methods
Journal of Computational Chemistry ( IF 3.4 ) Pub Date : 2024-08-22 , DOI: 10.1002/jcc.27482
Siyavash Moradi ₁ , Rebecca Tomann ₂ , Josie Hendrix ₂ , Martin Head-Gordon ₂ , Christopher J Stein ₁

Affiliation

We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine. Sensitivity analysis using Sobol indices guides the identification of the most influential parameters for a given reference dataset, allowing for a nuanced understanding of their impact on diverse molecular properties. In the case of the W4-11 dataset, substantial error reduction was achieved, demonstrating the potential of the optimization. Transferability of the optimized spin-polarization constants over different properties, however, is limited, as we demonstrate by applying the optimized parameters on a set of singlet-triplet gaps in carbenes. Further studies on ionization potentials and electron affinities highlight some inherent limitations of current extended tight-binding methods that can not be resolved by simple parameter optimization. We conclude that the significantly improved accuracy strongly encourages the present re-optimization of the spin-polarization constants, whereas the limited transferability motivates a property-specific optimization strategy.

中文翻译：

自旋极化扩展紧密结合方法的自旋参数优化

我们提出了一种在自旋极化 GFN2-xTB 框架内原子特异性自旋极化常数的优化策略，旨在提高分子模拟的准确性。我们比较了氢、碳、氮、氧和氟的自旋参数的顺序和全局优化。使用 Sobol 指数进行敏感性分析可指导确定给定参考数据集中最具影响力的参数，从而可以细致入微地了解它们对不同分子特性的影响。在 W4-11 数据集的情况下，实现了大幅度的误差减少，展示了优化的潜力。然而，优化的自旋极化常数在不同性质上的可传递性是有限的，正如我们通过将优化参数应用于卡宾中的一组单重态-三重态间隙来证明的那样。对电离电位和电子亲和力的进一步研究突出了当前扩展紧束缚方法的一些固有局限性，这些局限性无法通过简单的参数优化来解决。我们得出的结论是，显着提高的精度强烈鼓励了目前对自旋极化常数的重新优化，而有限的可转移性则激发了特定属性的优化策略。

更新日期：2024-08-22

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