The climbing image nudged elastic
band method (CI-NEB) is used
to identify reaction coordinates and to find saddle points representing
transition states of reactions. It can make efficient use of parallel
computing as the calculations of the discretization points, the so-called
images, can be carried out simultaneously. In typical implementations,
the images are distributed evenly along the path by connecting adjacent
images with equally stiff springs. However, for systems with a high
degree of flexibility, this can lead to poor resolution near the saddle
point. By making the spring constants increase with energy, the resolution
near the saddle point is improved. To assess the performance of this
energy-weighted CI-NEB method, calculations are carried out for a
benchmark set of 121 molecular reactions. The performance of the method
is analyzed with respect to the input parameters. Energy-weighted
springs are found to greatly improve performance and result in successful
location of the saddle points in less than a thousand energy and force
evaluations on average (about a hundred per image) using the same
set of parameter values for all of the reactions. Even better performance
is obtained by stopping the calculation before full convergence and
complete the saddle point search using an eigenvector following method
starting from the location of the climbing image. This combination
of methods, referred to as NEB-TS, turns out to be robust and highly
efficient as it reduces the average number of energy and force evaluations
down to a third, to 305. An efficient and flexible implementation
of these methods has been made available in the ORCA software.
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