3 papers
cond-mat.mtrl-sci2025
Predicting Trends in Through Rapid, Multimodal Characterization of State-of-the-Art p-i-n Perovskite Devices
Amy E. Louks, Brandon T. Motes, Anthony T. Troupe +3
Perovskite photovoltaic technologies are approaching commercial deployment, yet single junction and tandem architectures both still have significant room to improve power conversio…
cond-mat.mtrl-sci2024
Predicting Organic-Inorganic Halide Perovskite Photovoltaic Performance from Optical Properties of Constituent Films through Machine Learning
Ruiqi Zhang, Brandon Motes, Shaun Tan +7
We demonstrate a machine learning (ML) approach that accurately predicts the current-voltage behavior of 3D/2D-structured (FAMA)Pb(IBr)3/OABr hybrid organic-inorganic halide perovs…
physics.app-ph2020
Accurate Determination of Semiconductor Diffusion Coefficient Using Optical Microscopy
Dane W. deQuilettes, Roberto Brenes, Madeleine Laitz +3
Energy carrier transport and recombination in emerging semiconductors can be directly monitored with optical microscopy, leading to the measurement of the diffusion coefficient (D)…