University of Texas, Austin – Department of Chemistry and Biochemistry
Accelerating molecular dynamics: Adaptive kinetic Monte Carlo and κ-dynamics
Friday, March 2, 2:00 – 3:00 p.m.
227 Benedum Hall
ABSTRACT: Two computational methods will be presented for simulating the dynamics of atomic systems on time scales much longer than can be accessed with classical dynamics. In the first, called adaptive kinetic Monte Carlo, possible reaction mechanisms available to the system are found by exploring the potential energy surface from minima to find nearby saddle points. Reaction rates are then calculated using harmonic transition state theory, and the system is propagated in time according to the kinetic Monte Carlo algorithm. Our algorithm is efficient enough to model the evolution of systems with ab initio forces. I will show a few examples, including metal cluster formation on oxides and catalytic reactions on metal surfaces. In the second, called kappa-dynamics, a trajectory from an initial state is determined by running short time dynamics from a transition state surface. I will show that for rare event systems, the escape time can be calculated from the transition state theory rate of escape for the surface and the number of sampled trajectories required to find a single reactive one. In this way, an exact state-to-state trajectory can be determined.