Perhaps the most significant difficulty in locating transition states is to
obtain a good initial guess of the geometry to feed into a surface-walking
algorithm. This difficulty becomes especially relevant for large systems, for
which the dimensionality of the search space is large. Interpolation
algorithms are promising for locating good guesses of the minimum-energy
pathway connecting reactant and product states as well as approximate
saddle-point geometries. For example, the
nudged elastic band method
Phys. Rev. Lett.
(1994), 72, pp. 1124. , 452 J. Chem. Phys.
(2000), 113, pp. 9978. and the string method 299 Phys. Rev. B
(2002), 66, pp. 052301. start from a certain initial reaction pathway connecting the reactant and the product state, and then optimize in discretized path space towards the minimum-energy pathway. The highest-energy point on the approximate minimum-energy pathway becomes a good initial guess for the saddle-point configuration that can subsequently be used with any local surface-walking algorithm.
Inevitably, the performance of any interpolation method heavily relies on the
choice of the initial reaction pathway, and a poorly-chosen initial pathway can
cause slow convergence, or possibly convergence to an incorrect pathway. The
J. Chem. Phys.
(2004), 120, pp. 7877. and freezing-string method 84 J. Chem. Phys.
(2011), 135, pp. 224108. , 1028 J. Chem. Theory Comput.
(2012), 8, pp. 5166. offer solutions to this problem, in which two string fragments (one representing the reactant state and the other representing the product state) are “grown” (i.e., increasingly-finely defined) until the two fragments join. The freezing-string method offers a choice between Cartesian interpolation and linear synchronous transit (LST) interpolation. It also allows the user to choose between conjugate gradient and quasi-Newton optimization techniques.
Freezing-string calculations are requested by setting JOBTYPE =
FSM in the $rem section. Additional job-control keywords are
described below, along with examples. Consult Refs.
J. Chem. Phys.
(2011), 135, pp. 224108. and 1028 J. Chem. Theory Comput.
(2012), 8, pp. 5166. for a guide to a typical use of this method.
An example input appears below. Note that the $molecule section includes
geometries for two optimized intermediates, separated by
order of the atoms is important, as Q-Chem assumes that the th atom in the
reactant moves toward the th atom in the product. The FSM string is printed
out in the file stringfile.txt, which contains Cartesian coordinates of
the structures that connect reactant to product. Each node along the path is
labeled in this file, and its energy is provided. The geometries and energies
are also printed at the end of the Q-Chem output file, where they are labeled:
---------------------------------------- STRING ----------------------------------------
Finally, if MOLDEN_FORMAT is set to TRUE, then geometries along the string are printed in a MolDen-readable format at the end of the Q-Chem output file. The highest-energy node can be taken from this file and used to run a transition structure search as described in Section 9.1. If the string returns a pathway that is unreasonable, check whether the atoms in the two input geometries are in the correct order.
$molecule 0 1 Si 1.028032 -0.131573 -0.779689 H 0.923921 -1.301934 0.201724 H 1.294874 0.900609 0.318888 H -1.713989 0.300876 -0.226231 H -1.532839 0.232021 0.485307 **** Si 0.000228 -0.000484 -0.000023 H 0.644754 -1.336958 -0.064865 H 1.047648 1.052717 0.062991 H -0.837028 0.205648 -1.211126 H -0.855603 0.079077 1.213023 $end $rem JOBTYPE fsm FSM_NGRAD 3 FSM_NNODE 12 FSM_MODE 2 FSM_OPT_MODE 2 METHOD b3lyp BASIS 6-31G $end