A method for finding the ridge between saddle points applied to rare event rate estimates

Literature Information

Publication Date 2011-12-22
DOI 10.1039/C2CP23421A
Impact Factor 3.676
Authors

Jón Bergmann Maronsson, Hannes Jónsson, Tejs Vegge


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Abstract

A method is presented for finding the ridge between first order saddle points on a multidimensional surface. For atomic scale systems, such saddle points on the energy surface correspond to atomic rearrangement mechanisms. Information about the ridge can be used to test the validity of the harmonic approximation to transition state theory, in particular to verify that second order saddle points—maxima along the ridge—are high enough compared to the first order saddle points. New minima along the ridge can also be identified during the path optimisation, thereby revealing additional transition mechanisms. The method is based on a string of discretisation points along a path between the first order saddle points and using an iterative optimisation which requires only the force acting on the atoms. At each iteration during the optimisation, the force is inverted along an unstable eigenmode perpendicular to the path. The method is applied to Al adatom diffusion on the Al(100) surface to find the ridge between 2-, 3- and 4-atom concerted displacements and hop mechanisms. A correction to the harmonic approximation of transition state theory was estimated by direct evaluation of the configuration integral along the ridge.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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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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