Data-driven and constrained optimization of semi-local exchange and nonlocal correlation functionals for materials and surface chemistry,Journal of Computational Chemistry

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Data-driven and constrained optimization of semi-local exchange and nonlocal correlation functionals for materials and surface chemistry
Journal of Computational Chemistry ( IF 3.4 ) Pub Date : 2022-04-27 , DOI: 10.1002/jcc.26872
Kai Trepte ₁ , Johannes Voss ₁

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Reliable predictions of surface chemical reaction energetics require an accurate description of both chemisorption and physisorption. Here, we present an empirical approach to simultaneously optimize semi-local exchange and nonlocal correlation of a density functional approximation to improve these energetics. A combination of reference data for solid bulk, surface, and gas-phase chemistry and physical exchange-correlation model constraints leads to the VCML-rVV10 exchange-correlation functional. Owing to the variety of training data, the applicability of VCML-rVV10 extends beyond surface chemistry simulations. It provides optimized gas phase reaction energetics and an accurate description of bulk lattice constants and elastic properties.

中文翻译：

材料和表面化学的半局部交换和非局部相关泛函的数据驱动和约束优化

表面化学反应能量学的可靠预测需要准确描述化学吸附和物理吸附。在这里，我们提出了一种经验方法，可以同时优化密度泛函近似的半局部交换和非局部相关性，以改善这些能量学。固体体积、表面和气相化学和物理交换相关模型约束的参考数据的组合导致了 VCML-rVV10 交换相关函数。由于训练数据的多样性，VCML-rVV10 的适用性超出了表面化学模拟。它提供了优化的气相反应能量学以及对体积晶格常数和弹性特性的准确描述。

更新日期：2022-04-27

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