Date(s) - 02/14/2023
3:00 pm - 4:00 pm
Rhines Hall 125
Matthew Begley, Ph.D.
Professor, Materials Science and Mechanical Engineering
University of California, Santa Barbara
Dr. Matthew Begley is a Professor of Materials and a Professor of Mechanical Engineering at the University of California, Santa Barbara. His research emphasizes the use of computational mechanics to identify mechanisms limiting the performance of advanced material systems, spanning strain transfer in bone implants, acoustic assembly of patterned battery electrodes, and oxidation in high-temperature composites and coatings.
Professor Begley’s current focus is on the interplay between 3D printing, material microstructures and macroscopic performance, with the ultimate goal of controlling spatial distributions of properties in metamaterials to improve performance.
Professor Begley is a former recipient of the NSF Career Award and the Fraunhofer-Bessel Fellowship and has given invited talks at the Gordon Conference on Thin Films, the Gordon Conference on Corrosion, and the Gordon Conference on Microfluidics, the Chief Technology Officer Forum, and the Advanced Metallization Conference.
In many applications, performance gains enabled by architected porous materials are greatest when feature length-scales push the limits of printer resolution. This implies that printed components will contain a large number of microstructural and geometric defects, with inherent trade-offs between performance and reliability.
This talk will present highly efficient simulation tools that embed statistical distributions of geometry, strength, and ductility to quantify relationships between microscale variability and macroscopic performance. These links provide potentially powerful opportunities to quickly identify processing targets for significant improvements.
Illustrations of these concepts will be provided for three classes of materials: (i) stochastic elastomeric foams used in human-material interactions, where polydispersity in cell size controls softening, (ii) ceramic lattices used at high temperature, where Weibull strength distributions control peak stress, and (iii) quasi-ductile refractory metal lattices being developed for aerospace, where limited ductility controls strength after damage initiation.
The potential advantages and drawbacks of using models with coarse-grained descriptions will be briefly discussed, focusing on the development of optimization frameworks that embed processing science.