Modeling and simulations of crystallization/solidification of materials for understanding a given material's microscopic structure and final properties have spawned significant advances in today's explorations of new nano-materials and devices in materials sciences and engineering. In the past decade, many computational models have been developed to partially simulate the crystallization and solidification on either microscopic or macroscopic scales. However, a generalized model to develop microscopic (molecular, meso-scale) calculations with macroscopic computations has not been developed, due to the model's complexity on multiple scales and validity of computational power. This research involves developing a computational infrastructure that includes a large-scale microscopic and macroscopic model of crystallization/solidification of nanostructure materials, and associated high performance computational algorithms and numerical methods, using the cyber-infrastructure-enabled computing resources and facilities. The investigators will develop an integrated software package which can systematically solve many challenges in the modeling and simulation of nanostructure material formation. The model begins with the atomic/molecular interactions for the origin of nucleation by using parallel molecular dynamics (MD), and considers the mechanisms of nano-scale crystallization, nano-particle/crystal formation and growth. The researchers employ thermal dynamics and the equilibrium theory to account for the microscopic liquid-state precipitation and/or segregation, local thermal and special non-equilibriums, microstructure transition, particles and interactions, and phase change. They also consider the macroscopic transport phenomena and various defects at a macroscopic level. The computational infrastructure model fully lies in the large-scale parallel computing technologies bred by national cyber-infrastructure. Numerous tasks for the model computation are distributed across multiple computing platforms connected by high-speed networks, while each task executes a parallel computation; thus increasing computational power for the challenging problem.
