Atomistic simulations of rare events using gentlest ascent dynamics
arXiv:1108.1941 · doi:10.1063/1.3692803
Abstract
The dynamics of complex systems often involve thermally activated barrier crossing events that allow these systems to move from one basin of attraction on the high dimensional energy surface to another. Such events are ubiquitous, but challenging to simulate using conventional simulation tools, such as molecular dynamics. Recently, Weinan E et al. [Nonlinearity, 24(6),1831(2011)] proposed a set of dynamic equations, the gentlest ascent dynamics (GAD), to describe the escape of a system from a basin of attraction and proved that solutions of GAD converge to index-1 saddle points of the underlying energy. In this paper, we extend GAD to enable finite temperature simulations in which the system hops between different saddle points on the energy surface. An effective strategy to use GAD to sample an ensemble of low barrier saddle points located in the vicinity of a locally stable configuration on the high dimensional energy surface is proposed. The utility of the method is demonstrated by studying the low barrier saddle points associated with point defect activity on a surface. This is done for two representative systems, namely, (a) a surface vacancy and ad-atom pair and (b) a heptamer island on the (111) surface of copper.
total 30 pages
References in corpus (4)
- The Gentlest Ascent Dynamics
- Some improvements of the ART method for finding transition pathways on potential energy surfaces
- Non-stochastic behavior of atomic surface diffusion on Cu(111) at all temperatures
- Dynamical dimer method for the determination of transition states with ab initio molecular dynamics
Cited by in corpus (5)
- Jump Markov models and transition state theory: the Quasi-Stationary Distribution approach
- Simplified Gentlest Ascent Dynamics for Saddle Points in Non-gradient Systems
- Kinetic Activation-Relaxation Technique and Self-Evolving Atomistic Kinetic Monte Carlo: Comparison of on-the-fly kinetic Monte Carlo algorithms
- An Iterative Minimization Formulation for Saddle-Point Search
- Multiscale Gentlest Ascent Dynamics for Saddle Point in Effective Dynamics of Slow-Fast System