This award is being made in response to a proposal submitted under the Materials World Net for collaborative research on computational materials between the NSF and EC.
Carnegie Mellon University (CMU) and Princeton University propose to team with three institutions in Europe to address the multiscale challenges of modeling recrystallization. The US side of the project will address issues of three-dimensional representation of materials that include the relevant aspects of microstructure and state, heterogeneous subgrain coarsening leading to nucleation, dislocation dynamics during recovery and grain boundary properties relevant to microstructural evolution. Recent developments in level set methods, for example, have opened up new possibilities and will allow us to make quantitative predictions of the complex dislocation motions that occur during recovery that include climb as well as glide. At a somewhat coarser length scale, modeling and theory of subgrain coarsening has progressed to the point where it should be applied to the complex and variable structures observed in deformed materials. Thus the project will have specific impact on fundamental research on materials in terms of developing new understanding of the processes of microstructural evolution via quantitative, predictive models. It will also have broad impact through the education of students with regular international exchanges and through the development of tools that can be readily transferred to industry for modeling the processing of commodity materials.
The overall thrust of the collaboration is to develop the Digital Microstructures approach that will develop computational tools that address the combination of heterogeneous plastic deformation with recovery and recrystallization processes through numerical characterization and simulation from the atomistic scale required for boundary motion, through dislocation dynamics of deformation followed by recovery at the cell and subgrain scale, to the grain-scale aspects of plastic deformation, coupled with long-range motion of boundaries (as recrystallization fronts). The US members of the team will concentrate on key aspects such as kinetic properties of grain boundaries (mobility), dislocation dynamics in recovery and mesoscopic simulation of the recrystallization process including all relevant features such as grain structure and crystallographic orientation. Verification of the predictive capability of the set of computational tools will be conducted by comparing the statistics of the computed microstructures to microstructures measured experimentally (based on data available from prior work). This proposal outlines the entire collaborative project but only those aspects to be worked on in the US are described in full. The elements of the program to be conducted in the US are identified.
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