MedeA® Transition State Search

Transition states are saddle points in the potential energy surface of chemical systems; the connections between key regions of the potential energy hypersurface. Transition states determine system properties such as reaction rates and activation energy barriers, which govern kinetic and diffusive behavior. Given the importance of such properties, efficiently locating transition states is of considerable interest.

Mathematically, although a transition state is a stationary point (that is, the first derivative of the potential energy with respect to defined structural ordinates is zero); a single second derivative of the potential energy is negative, so in one particular direction the desired configuration is a local maximum of the potential energy surface. Locating such positions is computationally demanding as it is not a simple minimization problem. However, MedeA® Transition State Search makes the location of such transition states computationally efficient.

MedeA® Transition State Search provides direct access to the Nudged Elastic Band (NEB) method. The pathway connecting the initial and final configurations is explored at discrete intervals using a restraining force which keeps each configuration perpendicular to and regularly spaced along the connecting direction. Subject to these constraints, the highest of any obtained configuration provides a good initial estimate of the transition state between the supplied initial and final configurations.

An illustration of the level of accuracy which may be obtained with MedeA® Transition State Search is provided in E. Wimmer, W. Wolf, J. Sticht, P. Saxe, R. Najafabadi, and G.A. Young Jr, Phys. Rev. B 77, 34305 (2008).

Properties from TSS module

• Energy profile along reaction path
• Structure and energy of transition states
• Multiple minima and transition states
• Animation of reaction path

Computational characteristics

• Fully integrated with the MedeA® environment Job and TaskServer infrastructure. Hence, computational resources may be efficiently employed in locating transition states.
• Nudged Elastic Band (NEB) method
• Climbing image method
• BFGS2 optimizer
• Efficient Parallelization
  • Individual images and whole chain make use of dynamical parallelization of JobServer
• Automatic refinement:
  • automatic zoom on region near transition state with new set of images
• Final optimization using gradient minimization
• Choice of any number of intermediate images

Required MedeA® modules

• Core MedeA® environment
• MedeA® VASP 4.6 or 5.2
• JobServer and TaskServers

Datasheet: 

MedeA_Transition_State_Search_Datasheet.pdf