The field of materials and microstructure design and characterization techniques has progressed significantly in the past two decades. Materials and processing design methodologies effectively utilize the incomplete materials knowledgebase to link final product properties to initial microstructure. Microstructure representation has become a primary vehicle to reach this goal. Characterization techniques that can provide consistent microstructure representation include x-ray, microscopy (SEM, TEM), and tomography. Methodologies that can make the Inverse Materials Design a reality require novel mathematical and computational frameworks and methodologies in addition to experimentally-based knowledge creation to integrate computational-prediction and experimental-validation approaches. This talk will present current advances in multiscale computational materials frameworks based on Microstructure Sensitive Design and statistical homogenization techniques. Microstructure representation and digitization using spectral techniques are at the heart of such methodologies. Application of the present methodologies in thermo-mechanical processing of advanced magnesium alloys, the effect of machining in Al and Titanium alloys and processing of textured silicon solar cells and solid Oxide Fuel Cells are discussed with respect to inverse methodologies.
https://mediaspace.gatech.edu/media/garmestani/1_f0iy7f67
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