通过将轨道和职业优化相结合,增强低密度矩阵功能理论计算
1Center for Theoretical and Computational Chemistry, Frontiers Science Center for New Organic Matter, State Key Laboratory of Advanced Chemical Power Sources, Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Department of Chemistry, Nankai University, Tianjin 300071, China.
The journal of physical chemistry. A
|August 29, 2024
概括
一种新的合优化方法在减少密度矩阵函数理论 (RDMFT) 计算中同时更新轨道和职位. 与传统的脱方法相比,这种方法显著提高了融合速度和稳定性,使RDMFT变得更加实用.
科学领域:
- 计算化学计算化学
- 量子化学 是一个量子化学.
- 材料科学 材料科学 材料科学
背景情况:
- 减少密度矩阵函数理论 (RDMFT) 计算通常使用轨道和职业的脱优化方法.
- 现有的方法,如轨道的单元优化和职业的显式隐式优化 (EBI),虽然单独强大,但导致缓慢的融合.
- 解的RDMFT优化通常需要大量的交替,阻碍计算效率和更广泛的应用.
研究的目的:
- 为RDMFT计算开发一种新的合优化方法.
- 为了提高RDMFT的融合速度,稳定性和实用性.
- 为了在单个优化步骤中实现轨道和职业的同时更新.
主要方法:
- 一种结合优化策略,将单元和EBI方法结合起来,用于同时进行轨道和职位更新.
- 引入有效的先决条件和线索搜索,以确保与一级算法的良好融合.
- 对各种分子,基础集,函数和初始猜测进行广泛的测试,以验证方法的性能.
主要成果:
- 与所有经过测试的脱方法相比,合优化方法表现出优越的融合速度,准确性和稳定性.
- 显著减少了合所需的代次数,即使对于像C60.0这样的大型系统也是如此.
- 在实用的代次数 (154) 中为C60分子实现了高精度 (10^-8 au).
结论:
- 建议的合优化方法在RDMFT中比传统的脱方法提供了实质性的改进.
- 这一进步使RDMFT计算变得更加有效和实用,用于更广泛的科学应用.
- 结合方法促进了RDMFT在计算化学和相关领域的进一步发展和更广泛的采用.
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