材料和表面化学的半局域交换和非局域相关泛函的数据驱动和约束优化
Data-driven and constrained optimization of semi-local exchange and non-local correlation functionals for materials and surface chemistry
摘要：
可靠的表面化学反应能量学的预测需要一个准确的描述化学吸附和物理吸附。在这里，我们提出了一个经验的方法，同时优化半本地交换和非本地相关的密度泛函近似，以改善这些能量。固体块体，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的VCML-rVV 10交换相关功能。由于训练数据的多样性，VCML-rVV 10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和体晶格常数和弹性性质的准确描述。
英文摘要：
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 non-local 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.
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