用于量子嵌入的活性轨道空间自动化、一致性且公平的选择方法
Automated, Consistent, and Even-handed Selection of Active Orbital Spaces for Quantum Embedding
AI总结：
针对金属团簇等含离域近简并轨道体系的量子化学计算中轨道空间划分一致性差的问题，提出基于SPADE算法的自动化一致划分方法，经过渡金属团簇小分子结合能计算验证有效。
摘要：
在量子化学计算中，降低计算成本的一种广泛使用的策略是将体系划分为活性子系统（即计算工作的核心对象）和以更低计算水平处理的环境部分。体系划分主要基于定域分子轨道。当需要计算反应路径或能量差时，确保所有结构的轨道空间保持一致至关重要。轨道空间的不一致会导致势能面出现不可预测的误差。虽然针对有机体系甚至金属-有机体系，已经建立了确保这种一致性的有效策略，但这些方法在面对具有高密度近简并且离域的分子轨道的金属团簇或纳米颗粒时通常会失效，而这类体系与催化作用高度相关。因此，准确且可行的量子力学从头算计算是人们迫切需要的。在本研究中，我们提出了一种基于SPADE算法（用于轨道空间划分的算法）的方法，即使对于存在离域且近简并分子轨道的体系，也能实现自动化且一致的划分，并通过过渡金属团簇上小分子的结合能计算验证了该方法的有效性。
英文摘要：
A widely used strategy to reduce the computational cost in quantum-chemical calculations is to partition the system into an active subsystem, which is the focus of the computational efforts and an environment that is treated at a lower computational level. The system partitioning is mostly based on localized molecular orbitals. When reaction paths or energy differences are to be calculated, it is crucial to keep the orbital space consistent for all structures. Inconsistencies in the orbital space can lead to unpredictable errors in the potential energy surface. While successful strategies to ensure this consistency have been established for organic and even metal-organic systems, these methods often fail for metal clusters or nanoparticles with a high density of near-degenerate and delocalized molecular orbitals. However, such systems are highly relevant for catalysis. Accurate yet feasible quantum-mechanical ab initio calculations are therefore highly desired. In this work, we present an approach based on the SPADE algorithm that allows us to ensure an automated and consistent partitioning even for systems with delocalized and near-degenerate molecular orbitals and demonstrate the validity of this method for the binding energies of small molecules on transition-metal clusters.
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