分因数四倍和一个预测器的更高层次的相关性在热化学
James H Thorpe1, Zachary W Windom2, Rodney J Bartlett2
1Department of Chemistry, Southern Methodist University, Dallas, Texas 75275, United States.
The journal of physical chemistry. A
|August 28, 2024
概括
这项研究为合集群理论引入了具有成本效益的四倍校正,改善了反应能量预测. 一个新的缩放性扰动估计器准确地近似结合后集群单双和三倍 (CCSD(T)) 贡献,计算成本最小.
科学领域:
- 计算化学计算化学
- 量子化学 是一个量子化学.
- 理论化学 理论化学
背景情况:
- 结合集群理论,特别是CCSDT,对于准确的初始分子性质预测至关重要.
- 高阶激发 (四倍) 在计算上是昂贵的,规模为O(N^6) 或更糟糕.
- 预测对反应能量的后CCSD (T) 校正的必要性是具有挑战性的.
研究的目的:
- 调查用于整合四倍激发纠正的成本有效方法.
- 评估因子化的合集群方法和反应能量的新估计技术的准确性.
主要方法:
- 采用了因子化的CCSD (TQf) 方法,这是CCSD (TQ) 的计算性更便宜的替代方案.
- 评估了古德森的持续分数方法来估计CCSDT的贡献.
- 开发并测试了一个基于CCSD ((TQf) /cc-pVDZ. 的缩放扰动估计器.
主要成果:
- 与CCSD (TQ) 相比,因子化的CCSD (TQf) 方法显示出最小的误差.
- 缩放扰动估计器准确地预测了CCSDT ((Q) Λ贡献,平均误差为0.07kcal/mol,约3000次反应.
- 这个估计器以不超过CCSDT的计算成本实现了高精度.
结论:
- 分因式合集群方法为降低高精度计算成本提供了可行的途径.
- 缩放扰动估计器提供了一种可靠且计算成本低廉的方法来估计CCSD后 (T) 对反应能量的影响.
- 这种方法可以有效地评估高阶相关性效应在热化学预测中的重要性.
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