Computer Modeling of Microstructural Evolution in Porous Solids and Thin Films
J. W. Bullard*
University of Illinois

This research focuses on applying high-performance computing to simulate the dynamics of interface motion in complex microstructures and thin-film systems. The approach is based on both sharp interface and diffuse interface theories, and allows one to track interface motion readily. A number of thermodynamic driving forces for energy dissipation, as well as several kinetic mechanisms by which dissipation occurs, have been included. A diverse set of phenomena can be studied with this model, and it is currently being used to examine the growth and coalescence of thin-film islands, Ostwald ripening of precipitates, and the distribution of absorbed liquid in porous networks.

Cellular Automata Modeling of Natural Phenomena
R. J. Gaylord,* K. Nishidate (Iwate Univ.)
University of Illinois; Iwate University, Japan

Computer simulations of time-dependent processes can be written using discrete systems of lattice sites whose values are synchronously updated in discrete time steps as a result of local interactions with other sites. We are developing cellular automata programs of a wide variety of physical, chemical, biological, and social phenomena.

Electronic and Energetic Properties of Materials
D. D. Johnson*
U.S. Department of Energy, DE-FG02-96ER45439 (In cooperation with the Materials Research Laboratory)

Within a Green's function formalism, electronic density-functional theory (DFT) techniques are used to investigate disordered, partially ordered, and fully ordered phases of multicomponent alloy systems. The underlying electronic origin of various materials properties (electronic, magnetic, thermodynamic, elastic) are then determined. Additional schemes are being developed to investigate larger-scale phenomena, such as microstructure and kinetics, which are ultimately based on such DFT results, thus allowing a connection of length scales: micro- to macroscale.

Intermediate- and Extended-Range Order in Amorphous Structures
J. Kieffer,* D. Nekhayev
National Science Foundation, DMR 93-15779

We developed algorithms for large-scale molecular dynamic simulations using massively parallel computing environments, allowing us to study ensembles up to millions of atoms. This gives us the opportunity to tackle the long-standing questions of structural characterization beyond nearest neighbors in amorphous materials. New analytical concepts are being developed allowing one to analyze large molecular configurations for topological patterns as well as structural and chemical heterogeneities.

Chaotic Motion in Molecular Structures
J. Kieffer,* B. J. Reardon
University of Illinois; Los Alamos National Laboratory

By using concepts from chaos theory, such as Lyapunov exponents and Kolmogorov-Sinai entropies, we characterize the dynamic behavior of large molecular configurations generated by molecular dynamic simulations. From these measures one can derive conclusions about the thermodynamic stability of a structure, as well as estimate the magnitudes of atomic transport coefficients. The goal of this project is to develop formalisms that allow one to relate the topology of a structure to the inherent mobility of its constituents, and with this knowledge improve the design of electrolytes used in batteries, fuel cells, and sensors.