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SC2/MICDE Seminar: Eric Jankowski, Materials Science and Engineering, Boise State University
March 8, 2017 @ 2:00 pm - 3:00 pm
2540 G.G. Brown (2350 Hayward St.)
Bio: Eric Jankowski is an assistant professor of Materials Science and Engineering at Boise State University. He earned his PhD in Chemical Engineering from the University of Michigan in 2012, where he developed computational tools to study the self-assembly of nanoparticles. These tools leveraged graphics processors to accelerate computations and provided insight into systems of both theoretical and practical importance. Dr. Jankowski began focusing on renewable energy generation during his postdoctoral positions at the University of Colorado and the National Renewable Energy Laboratory. At these postdocs, Dr. Jankowski applied techniques he developed during his thesis to understand factors that determine the ordering of molecules in organic solar cells.
This is a joint seminar of the Scientific Computing Student Club and MICDE, sponsored in part by U-M Rackham Graduate School.
Cobbling together computational components to engineer inexpensive plastic solar panels
In order to meet projected global energy demands over the next 25 years, the equivalent of building a 1GW power plant each day is needed. Existing clean power generation technologies can meet this demand in principle, but their relatively large short-term costs have limited widespread adoption. In this work we explain manufacturing strategies for organic (plastic) solar panels that overcome economic barriers to adoption by optimizing the structure of the organic active layer responsible for generating electricity. We perform coarse-grained molecular dynamics simulations accelerated with graphics processing units to determine the thermodynamically stable morphologies for a variety of candidate ingredients. Using these morphologies we perform kinetic Monte Carlo charge transport simulations to determine which morphologies are better candidates for solar devices. The simulation pipeline developed here combines computational tools developed for solving unrelated problems, and we discuss the evolving landscape of scientific computing education and how it overlaps with this work.