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Title: 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 Fe 2O 3, Cu 2V 2O 7, and BiVO 4. Here, 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.
 [1] ;  [1] ;  [1]
  1. California Inst. of Technology (CalTech), Pasadena, CA (United States). Joint Center for Artificial Photosynthesis
Publication Date:
Grant/Contract Number:
SC0004993; SC000499
Published Article
Journal Name:
ACS Combinatorial Science
Additional Journal Information:
Journal Volume: 18; Journal Issue: 11; Journal ID: ISSN 2156-8952
American Chemical Society (ACS)
Research Org:
California Inst. of Technology (CalTech), Pasadena, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; high-throughput screening; combinatorial science; band gap; UV−vis spectroscopy; optical spectroscopy; solar fuels
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1333916