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用于改进反应路径中键重排的相关平底弹性网络模型

Correlated Flat-Bottom Elastic Network Model for Improved Bond Rearrangement in Reaction Paths.

作者信息

Koda Shin-Ichi, Saito Shinji

机构信息

Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan.

School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan.

出版信息

J Chem Theory Comput. 2025 Apr 8;21(7):3513-3522. doi: 10.1021/acs.jctc.4c01549. Epub 2025 Mar 19.

Abstract

This study introduces correlated flat-bottom elastic network model (CFB-ENM), an extension of our recently developed flat-bottom elastic network model (FB-ENM) for generating plausible reaction paths, i.e., collision-free paths preserving nonreactive parts. While FB-ENM improved upon the widely used image-dependent pair potential (IDPP) by addressing unintended structural distortion and bond breaking, it still struggled with regulating the timing of series of bond breaking and formation. CFB-ENM overcomes this limitation by incorporating structure-based correlation terms. These terms impose constraints on pairs of atom pairs, ensuring immediate formation of new bonds after breaking of existing bonds. Using the direct MaxFlux method, we generated paths for 121 reactions involving main group elements and 35 reactions involving transition metals. We found that CFB-ENM significantly improves reaction paths compared to FB-ENM. CFB-ENM paths exhibited lower maximum DFT energies along the paths in most reactions, with nearly half showing significant energy reductions of several tens of kcal/mol. In the few cases where CFB-ENM yielded higher energy paths, most increases were below 10 kcal/mol. We also confirmed that CFB-ENM reduces computational costs in subsequent precise reaction path or transition state searches compared to FB-ENM. An implementation of CFB-ENM based on the Atomic Simulation Environment is available on GitHub for use in computational chemistry research.

摘要

本研究引入了相关平底弹性网络模型(CFB-ENM),它是我们最近开发的用于生成合理反应路径(即保留非反应部分的无碰撞路径)的平底弹性网络模型(FB-ENM)的扩展。虽然FB-ENM通过解决意外的结构变形和键断裂问题改进了广泛使用的图像依赖对势(IDPP),但它在调节一系列键断裂和形成的时机方面仍存在困难。CFB-ENM通过纳入基于结构的相关项克服了这一限制。这些项对原子对施加约束,确保现有键断裂后立即形成新键。使用直接最大通量方法,我们为121个涉及主族元素的反应和35个涉及过渡金属的反应生成了路径。我们发现,与FB-ENM相比,CFB-ENM显著改善了反应路径。在大多数反应中,CFB-ENM路径沿路径的最大密度泛函理论(DFT)能量较低,近一半反应显示出几十千卡/摩尔的显著能量降低。在少数CFB-ENM产生较高能量路径的情况下,大多数能量增加低于10千卡/摩尔。我们还证实,与FB-ENM相比,CFB-ENM在后续精确反应路径或过渡态搜索中降低了计算成本。基于原子模拟环境的CFB-ENM实现可在GitHub上获取,供计算化学研究使用。

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