ITR: Computational Tools for Multicomponent Materials Design

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This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.This collaborative research project involves two materials scientists, a computerscientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural, and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. A prototype GRID-enabled software will be developed for multicomponent materials design with efficient information exchange between design stages. Each design stage will incorporate effective algorithms and parallel computing schemes. Four computational components will be integrated, these are: (1) first-principles calculations to determine thermodynamic properties, lattice parameters, and kinetic data of unary, binary and ternary compounds; (2) CALPHAD data optimization computation to extract thermodynamic properties, lattice parameters, and kinetic data of multicomponent systems combining results from first-principles calculations and experimental data; (3) multicomponent phase-field modeling to produce microstructure; and (4) finite element analysis to obtain the mechanical response from the simulated microstructure. The research involves a parallel effort in information technology with two main components: (1) advanced discretization and parallel algorithms, and (2) a software architecture for distributed computing system. The first component includes: (a) a coupling of spectral and finite element approximations, (b) local adaptivity and multi-scale resolution, (c) high order stable semi-implicit in time schemes, (d) parallelization through domain decomposition, and (e) scalable sparse system solvers. The second component involves computational GRID-enabled software for the overall design process; this software architecture enables the use of geographically distributed high performance parallel computing resources to reduce application turnaround time while providing a flexible client-server interface that allows multiple design cycles to proceed.The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.%%%This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.This collaborative research project involves two materials scientists, a computerscientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. Prototype GRID-enabled software will be developed for multicomponent materials design. Effective algorithms and parallel computing schemes will be incorporated into the design. The GRID-enabled software allows geographically distributed high performance parallel computing resources to be harnessed bringing greater computational power to bear on a given problem and enabling practical application of these computational tools. The prototype software, with improved predictive power in multicomponent materials design, may enable scientists to develop new materials with unique properties and to tailor existing materials for better performance.The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.***