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Brianna Greenstein

University of Pittsburgh
Chemistry
Education
PhD Candidate, Chemistry, University of Pittsburgh, 2019-Present
Supervisor: Prof. Geoffrey Hutchison
Topic of Dissertation: Computational Discovery of Materials for Organic Solar Cells
Bachelor of Science, Chemistry, Binghamton University, NY, Aug 2015-May 2019
Profile

My research focuses on using computational tools such as genetic algorithms, machine learning, and quantum chemical calculations to optimize the materials in organic solar cells. By examining large amounts of experimental data, we can uncover some chemical design rules and use algorithms to predict even more efficient materials than currently experimentally reported. This "virtual synthesis" can drastically speed up materials discovery and aid experimentalists in the design of new molecules. 

Awards
  • 2022-2023 PQI Fellow
Most Cited Publications
  • Greenstein, B. L.; Hutchison, G. R. Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells. J. Phys. Chem. Lett. 202213 (19), 4235–4243. https://doi.org/10.1021/acs.jpclett.2c00866.
  • Greenstein, B. L.; Hiener, D. C.; Hutchison, G. R. Computational Evolution of High-Performing Unfused Non-Fullerene Acceptors for Organic Solar Cells. J. Chem. Phys. 2022156 (17), 174107. https://doi.org/10.1063/5.0087299.