High Throughput Light Absorber Discovery, Part 1: An Algorithm for Automated Tauc Analysis.
High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery of optical materials enables advancements in solar energy and other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, and we present an automated Tauc analysis algorithm for estimating band gap energies from optical spectroscopy data. The algorithm mimics the judgment of an expert scientist, which is demonstrated through its application to a variety of high throughput spectroscopy data, including the identification of indirect or direct band gaps in Fe2O3, Cu2V2O7, and BiVO4. The applicability of the algorithm to estimate a range of band gap energies for various materials is demonstrated by a comparison of direct-allowed band gaps estimated by expert scientists and by automated algorithm for 60 optical spectra.
Joint Center for Artificial Photosynthesis, California Institute of Technology , Pasadena California 91125, United States.
Santosh K
SK
Suram
Joint Center for Artificial Photosynthesis, California Institute of Technology , Pasadena California 91125, United States.
Paul F
PF
Newhouse
Joint Center for Artificial Photosynthesis, California Institute of Technology , Pasadena California 91125, United States.
John M
JM
Gregoire
D000465:Algorithms; D001729:Bismuth; D004735:Energy Transfer; D005290:Ferric Compounds; D057166:High-Throughput Screening Assays; D008956:Models, Chemical; D012993:Solar Energy; D013057:Spectrum Analysis; D014638:Vanadates
D005290:Ferric Compounds; C091754:bismuth vanadium tetraoxide; D014638:Vanadates; D001729:Bismuth
UV−vis spectroscopy; band gap; combinatorial science; high-throughput screening; optical spectroscopy; solar fuels