Algorithms for finding transition states in atomic scale systems will be discussed, as well as how transition state theory rates can be used with kinetic Monte Carlo for modeling dynamics in materials over long time scales.
About the speaker:
Graeme Henkelman is professor of chemistry and director of Center for Computational Molecular Sciences in the University of Texas at Austin. He obtained his Ph.D. in theoretical chemistry in University of Washington in 2001. He is a main contributor for three saddle point finding methods (NEB, Dimer, and Lanczos) and several tools (bader and vtsttools) to work with the VASP code. The primary focus of his group is the development of simulation methodology to study kinetic processes at the atomic scale, especially in surface growth, diffusion in solids, and reactions at surfaces. He is also interested in systems for which there exist or for which we can develop empirical potentials. This allows for the study of much larger systems and it opens the possibility to develop methods that would be too costly otherwise, using which to understand the dynamics of chemical systems over experimental time scales.