Multi-Scale Simulation of Rare-Event Dynamics in Assembly and Catalysis at Surfaces

TECHNICAL EXPLANATION:

The Division of Materials Research and the Chemistry Division jointly fund this award. It supports computational research and education aimed at addressing the challenging problem of using simulations of structural evolution to access long-time and large-length scales while accurately retaining atomic detail. Molecular-dynamics (MD) simulations can provide accurate details at the atomic scale. However, MD is not practical for simulating times or distances much beyond the nanometer scale. In many materials, dynamical evolution occurs through a series of 'rare events', in which the system spends a long-time period in one potential-energy minimum before escaping and moving on to another.

The PI aims to develop methods to advance the current capabilities for simulating rare-event dynamics. Specifically methods will be developed for parallel kinetic Monte Carlo (KMC) simulation, combination of lattice-based KMC simulations with rate equations, and accelerated MD simulation of thermal desorption. These methods will be applied to describe pattern formation in multi-layer, metal thin-film growth and the temperature-programmed desorption (TPD) of nalkane molecules from solid surfaces. Planned innovations to KMC simulations will allow their quantitative application to multi-scale problems, where length and time scales range from atomic scales to macroscopic scales. The accuracy and efficiency of these methods will be confirmed and assessed. The KMC studies will elucidate how pattern formation in metal thin-film epitaxy on fcc(110) surfaces depends on the surface temperature and the deposition rate. It is of particular interest in these studies to determine how experimentally observed nanostructures can self-organize and how the self-organization can be controlled.

The accelerated MD studies will be the first studies to simulate an entire TPD experiment in real space with MD. The simulations will be applied to resolve experimental controversy surrounding interpretation of n-alkane desorption. Further, the methodology that will be introduced could enable future simulations of large and complex catalytic systems whose net rate behavior reflects many different rate processes.

NON-TECHNICAL EXPLANATION:

The Division of Materials Research and the Chemistry Division jointly fund this award. It supports computational research and education aimed at addressing the challenging problem of using simulations of structural evolution to capture essential physical and chemical processes on long-time and large-length scales while accurately retaining detail at the atomic scale. Molecular-dynamics simulations can provide accurate details at the atomic scale, but it is not practical for simulating times or distances much beyond the nanometer scale. In many materials, dynamical evolution occurs through a series of 'rare events.'

The PI aims to develop computational algorithms and tools to enable meaningful simulation that can span from atomic to macroscopic length and time scales. This is a difficult and important problem in computational materials research and chemisty. Effective solutions of this problem can enable the interpretation and understanding of a wide range of experiments and contribute to the discovery of new materials and phenomena. The PI will focus on applications to the growth of films, patterned films, and nanostructures on the surfaces of materials, and the desorption of chainlike molecules from graphite and metal surfaces. The algorithms and computational tools that result from this work may find applications across other areas of chemistry, materials research, and biological physics.