Design of Sustainable Infrastructure Materials by Machine Learning
Newell Washburn, PhD, Associate Professor of Chemistry and Biomedical Engineering at Carnegie Mellon University, Pittsburgh
Tuesday, April 14, 2020, at 3:30 p.m.
McArthur Engineering Addition, Jose Milton Leadership Hall, Room 202
1251 Memorial Drive | Coral Gables, FL 33146
Abstract
More cement is produced than any other engineered material in the world, which forms the foundation for our modern infrastructure but its production contributes approximately 5% to global CO2 emissions due to the high-temperature calcination of limestone and clay. To address high CO2 emissions, as well as to improve its durability, cementitious materials based on locally sourced, minimally processed minerals have been a grand challenge in materials research, but the variability of mineral characteristics and the complexity of meeting a diversity of performance requirements has hindered deployment of alternative binder materials. Machine learning offers a framework for modeling complex systems, and this presentation will highlight how advances in data-driven methods are leading to powerful tools for materials design.
Newell Washburn, PhD, received his BS in Chemistry from University of Illinois at Urbana-Champaign and his PhD in Chemistry from University of California (Berkeley). Following post-doctoral work in Chemical Engineering at the University of Minnesota (Twin Cities), he joined the Polymers Division at NIST, first as an NRC post-doctoral associate then as leader of the Biomaterials Group. In 2004, he moved to Carnegie Mellon University where he is currently Associate Professor of Chemistry, Biomedical Engineering, and Materials Science and Engineering (by courtesy). His research interests focus on designing machine learning algorithms for complex physical systems and applying them to infrastructure materials, polymeric materials, and additive manufacturing. With his colleague in CMU’s Machine Learning Department he founded the chemicals/materials informatics company Ansatz AI, which is exploring industrial applications of algorithms developed at CMU.
Click here to RSVP
Click here to watch the Livestream
