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Microstructure design using graphs
npj Computational Materials
  • Pengfei Du, Iowa State University
  • Adrian Zebrowski, University at Buffalo
  • Jaroslaw Zola, University at Buffalo
  • Baskar Ganapathysubramanian, Iowa State University
  • Olga Wodo, University at Buffalo
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Thin films with tailored microstructures are an emerging class of materials with applications such as battery electrodes, organic electronics, and biosensors. Such thin film devices typically exhibit a multi-phase microstructure that is confined, and show large anisotropy. Current approaches to microstructure design focus on optimizing bulk properties, by tuning features that are statistically averaged over a representative volume. Here, we report a tool for morphogenesis posed as a graph-based optimization problem that evolves microstructures recognizing confinement and anisotropy constraints. We illustrate the approach by designing optimized morphologies for photovoltaic applications, and evolve an initial morphology into an optimized morphology exhibiting substantially improved short circuit current (68% improvement over a conventional bulk-heterojunction morphology). We show optimized morphologies across a range of thicknesses exhibiting self-similar behavior. Results suggest that thicker films (250 nm) can be used to harvest more incident energy. Our graph based morphogenesis is broadly applicable to microstructure-sensitive design of batteries, biosensors and related applications.


This article is published as Du, Pengfei, Adrian Zebrowski, Jaroslaw Zola, Baskar Ganapathysubramanian, and Olga Wodo. "Microstructure design using graphs." npj Computational Materials 4, no. 1 (2018): 50. DOI: 10.1038/s41524-018-0108-5. Posted with permission.

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Pengfei Du, Adrian Zebrowski, Jaroslaw Zola, Baskar Ganapathysubramanian, et al.. "Microstructure design using graphs" npj Computational Materials Vol. 4 (2018) p. 50
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