Uncovering the role of the stationary points in the dynamics of the F− + CH3I reaction
Literature Information
Balázs Olasz, Gábor Czakó
We describe an analysis method which assigns geometries to stationary points along (quasi)classical trajectories. The method is applied to the F− + CH3I reaction, thereby uncovering the role of the minima and transition states in the dynamics of the SN2 inversion, SN2 retention via front-side attack and double inversion, induced inversion, and proton-transfer channels. Stationary-point probability distributions, stationary-point-specific trajectory orthogonal projections, root-mean-square distance distributions, transition probability matrices, and time evolutions of the stationary points reveal long-lived front-side (F−⋯ICH3) and hydrogen-bonded (F−⋯HCH2I) complexes in the entrance channel and significant post-reaction ion-dipole complex (FCH3⋯I−) formation in the SN2 exit channel. Most of the proton-transfer stationary points (FH⋯CH2I−) participate in all the reaction channels with larger distance deviations than the double-inversion transition state. Significant forward–backward transitions are observed between the minima and transition states indicating complex, indirect dynamics. The utility of distance and energy constraints is also investigated, thereby restricting the assignment into uniform configuration or energy ranges around the stationary points.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.













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