Transition state searchΒΆ
A transition state (TS) search is very much like a geometry optimization: the purpose is to find a stationary point on the potential energy surface, primarily by monitoring the energy gradients, which should vanish. The difference between a transition state and a minimum is that at the transition state the Hessian has a negative eigenvalue: We are at a saddle point, not a minimum, with the “negative” mode connecting the two basins on the potential energy surface.
See also
Examples and the PES scan and transition state search tutorial
A transition state search in AMS is performed by selecting the corresponding task:
Task TransitionStateSearch
Due to the similarities between energy minimization and transition state search,
the TransitionStateSearch task in AMS is actually implemented as a special
kind of geometry optimization using the quasi-Newton
optimizer. As such all the settings and keywords described on the geometry
optimization manual page also apply to transition state
searches.
In a geometry optimization with a quasi-Newton based optimizer the Hessian is used to make a reasonably sized step in the “downhill” direction on the potential energy surface, as the goal is simply to minimize the energy. A transition state search is a bit different: In the first step a normal mode is picked along which the energy is to be maximized, while it is minimized along all other directions. Normally the mode with the lowest eigenvalue is picked, since we know that there should be exactly one negative eigenvalue at the TS geometry. If the initial geometry is sufficiently close to the transition state, i.e. we are close to the saddle, the lowest mode is normally the correct one to follow in order to get to the ridge of the saddle. Alternatively a different mode can also be selected manually.
TransitionStateSearch
ModeToFollow integer
End
TransitionStateSearchType: Block Description: Configures some details of the transition state search. ModeToFollowType: Integer Default value: 1 Description: In case of Transition State Search, here you can specify the index of the normal mode to follow (1 is the mode with the lowest frequency).
This selection happens only in the first step. Subsequent steps will attempt to maximize along the mode that resembles most (by overlap) the previous maximization direction.
Practice shows that transition states are much harder to find than a minimum. For a large part this is due to the much stronger anharmonicities that usually occur near the TS, which threaten to invalidate the quasi-Newton methods to find the stationary point. For this reason it is good advice to be more cautious in the optimization strategy when approaching a transition state:
- We recommend starting the transition state search with an intial geometry that is already close to the transition state. One can use a potential energy surface scan along something resembling the reaction coordinate to get a rough idea where the transition state is. This geometry can then be used as an initial geometry for the transitions state search.
- It is strongly recommended to manually supply a good initial Hessian for the transition state search. Otherwise the first step of the search might not be taken in the correct direction and subsequent steps will attempt to keep steering in the wrong direction. In AMS this is easily possible by loading a Hessian from a previous calculation, see the initial Hessian section of this manual. A good way to obtain a reasonable Hessian is to compute it explicitly with one of the fast engines (i.e. at a lower lever of theory) and read that Hessian as the initial Hessian for the transition state search at a higher level of theory. This approach is demonstrated in the Examples and the PES scan and transition state search tutorial.
- When the method converges it is usually a good idea to verify that the found geometry is indeed a transition state. This can be done by performing a frequency analysis and checking whether the Hessian has exactly one negative eigenvalue (represented by a mode with a negative frequency). Doing so is expensive however. Since we are really only interested in the lowest two normal modes calculating the full Hessian is however not necessary and one can use the faster PES point characterization instead. This uses a Davidson-type algorithm to obtain the lowest few normal modes without constructing the full Hessian. The user is referred to the PES point characterization documentation page for further details.