Transition state (TS) search is key in chemistry for elucidating reaction mechanisms and exploring reaction networks. The search for accurate 3D TS structures, however, requires numerous computationally intensive quantum chemistry calculations due to the complexity of potential energy surfaces. Here, we developed an object-aware SE(3) equivariant diffusion model that satisfies all physical symmetries and constraints for generating sets of structures - reactant, TS, and product - in an elementary reaction. Provided reactant and product, this model generates a TS structure in seconds instead of hours required when performing quantum chemistry-based optimizations. The generated TS structures achieve a median of 0.08 Å root mean square deviation compared to the true TS. With a confidence scoring model for uncertainty quantification, we approach an accuracy required for reaction rate estimation (2.6 kcal/mol) by only performing quantum chemistry-based optimizations on 14\% of the most challenging reactions. We envision the proposed approach useful in constructing large reaction networks with unknown mechanisms.
Elementary exposition of realizing phase space structures relevant to chemical reaction dynamics
在这篇文章中，我们审查的分析和数值方法计算的相空间结构的两个自由度的哈密顿系统中出现的化学反应。特别地，这些相空间结构是与指数-1鞍相关联的不稳定周期轨道、周期轨道分割面以及不稳定周期轨道的稳定不变流形和不稳定不变流形。我们审查的背景下，一个两个自由度的哈密顿与一个四次潜在的二次潜在的方法。我们推导出了可积情形下相空间结构的解析形式，并将其在三维能量面上的几何形状可视化。然后，我们调查的分歧的分割面由于势能的参数的变化。我们还回顾了\emph{turning point}的数值方法，并提出了它的新的修改称为\emph{turning point based on configuration difference}计算两个自由度系统的不稳定周期轨道。这些方法在开源python包UPOsHam~ \cite{Lyu2020}中实现。
Reaction-Transformation-Aware Flow Matching for Generalizable Transition State Generation
Shanghai Jiao Tong University（上海交通大学）；Shanghai Innovation Institute（上海创新研究院）；East China Normal University（华东师范大学）；University of Science and Technology of China（中国科学技术大学）
