Fast-Tracking Transition-State Localization via Reaction Directional Analysis

Transition-state localization is critical for elucidating chemical reaction mechanisms but remains one of the most computationally demanding challenges in theoretical chemistry. Here, we introduce a novel method, reaction directional analysis-dimer (RDA-D), which integrates reaction directional analysis (RDA) with the dimer method to achieve efficient and reliable transition state searching. Reaction directional analysis generates high-quality quasi-transition-state structures directly from only the initial and final state geometries, combining dynamic interpolation, structural optimization, and directional analysis. These quasi-transition-state structures then serve as starting points for refinement via the dimer method. Benchmark tests on a diverse set of gas-phase and catalytic reactions on surfaces demonstrate that RDA-D is, on average, 5.83 times faster than the Nudged Elastic Band (NEB) method in CPU time and reduces the number of gradient evaluations by a factor of 4.74. Moreover, reaction directional analysis eliminates the need for predefined reaction coordinates or chemically intuitive initial guesses, providing a robust, scalable, and automation-friendly framework for transition-state localization.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-12-12
DOI
https://doi.org/10.1021/acs.jctc.5c01784
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52
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article

Fast-Tracking Transition-State Localization via Reaction Directional Analysis

P. Hu, Chenxi Guo, Peipei Zhang
1 citations
Journal of Chemical Theory and Computation
Machine Learning in Materials Science
0.52
article

Fast-Tracking Transition-State Localization via Reaction Directional Analysis

P. Hu, Chenxi Guo, Peipei Zhang
article en
1 citations

Abstract

Transition-state localization is critical for elucidating chemical reaction mechanisms but remains one of the most computationally demanding challenges in theoretical chemistry. Here, we introduce a novel method, reaction directional analysis-dimer (RDA-D), which integrates reaction directional analysis (RDA) with the dimer method to achieve efficient and reliable transition state searching. Reaction directional analysis generates high-quality quasi-transition-state structures directly from only the initial and final state geometries, combining dynamic interpolation, structural optimization, and directional analysis. These quasi-transition-state structures then serve as starting points for refinement via the dimer method. Benchmark tests on a diverse set of gas-phase and catalytic reactions on surfaces demonstrate that RDA-D is, on average, 5.83 times faster than the Nudged Elastic Band (NEB) method in CPU time and reduces the number of gradient evaluations by a factor of 4.74. Moreover, reaction directional analysis eliminates the need for predefined reaction coordinates or chemically intuitive initial guesses, providing a robust, scalable, and automation-friendly framework for transition-state localization.

Journal of Chemical Theory and ComputationVol. 21(24)
Queen's University Belfast (GB), East China University of Science and Technology (CN), ShanghaiTech University (CN), Coconut Research Institute (CN), Ministry of Education (PT), Industrial Technology Institute (LK), Dahua Technology (China) (CN)
Openalex Percentile: Top 29%
Machine Learning in Materials Science
0.52
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