Demkowicz leads project to develop nanometallic materials

Demkowicz, Michael JDr. Michael J. Demkowicz, associate professor in the Department of Materials Science and Engineering at Texas A&M University, has been awarded a grant to speed up the development and application of nanometallic materials (NMMs).

The grant is supported by the National Science Foundation’s (NSF) Designing Materials to Revolutionize and Engineer our Future (DMREF) program and is a collaborative effort between Texas A&M, the University of Michigan and Virginia Polytechnic Institute and State University. Texas A&M is the lead institution and Demkowicz is the principal investigator.

The project, “Designing and Synthesizing Nano-Metallic Materials with Superior Properties,” will develop NMMs that possess extreme strength, resistance to damage from repeated loading and the unique property of being resistant to radiation damage. NMMs are composites made up of nanoscale elements.

Demkowicz specializes in computational materials design and fundamental physics of material behavior, especially mechanical properties and radiation response.

“The shear variety of NMM structures is so vast that it cannot be explored exhaustively by brute force experiments,” said Demkowicz. “That’s where computation comes in. We want to scan over a vast space of NMM designs using efficient, fast algorithms constructed based on judiciously selected experiments."

The NSF, in support of the multi-agency federal Materials Genome Initiative (MGI), seeks to target one of the primary MGI goals — to halve the time and cost for transitioning breakthroughs from the laboratory to the marketplace — a process that currently takes as long as two decades.

By integrating theory, modeling and experiments, the project led by Demkowicz aims to engineer the architectures, interfaces, and compositions of NMMs to achieve superior mechanical performance. The project will follow an iterative design-synthesize-test cycle that scans the design space rapidly and integrates insights gained in each iteration by updating theoretical models connecting design parameters to performance metrics.