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Title: Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials

Abstract

In this work, we present a description of an electroluminescence (EL) apparatus, easily sourced from commercially available components, with a quantitative image processing platform that demonstrates feasibility for the widespread utility of EL imaging as a characterization tool. We validated our system using a Gage R&R analysis to fnd a variance contribution by the measurement system of 80.56%, which is typically unacceptable, but through quantitative image processing and development of correction factors a variance contribution by the measurement system of 2.41% was obtained. We further validated the system by quantifying the signal-to-noise ratio (SNR) and found values consistent with other systems published in the literature, at SNR values of 10-100, albeit at exposure times of greater than 1 s compared to 10 ms for other systems. Finally, this SNR value range is acceptable for image feature recognition, providing the opportunity for widespread data acquisition and large scale data analytics of photovoltaics.

Authors:
ORCiD logo [1];  [1];  [1];  [1]; ORCiD logo [1];  [1]
  1. Case Western Reserve Univ., Cleveland, OH (United States)
Publication Date:
Research Org.:
Stanford Univ., CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1579854
Grant/Contract Number:  
EE0004946; EE0007140
Resource Type:
Accepted Manuscript
Journal Name:
Review of Scientific Instruments
Additional Journal Information:
Journal Volume: 87; Journal Issue: 8; Journal ID: ISSN 0034-6748
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 42 ENGINEERING; 14 SOLAR ENERGY

Citation Formats

Fada, Justin S., Wheeler, Nicholas R., Zabiyaka, Davis, Goel, Nikhil, Peshek, Timothy J., and French, Roger H. Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials. United States: N. p., 2016. Web. doi:10.1063/1.4960180.
Fada, Justin S., Wheeler, Nicholas R., Zabiyaka, Davis, Goel, Nikhil, Peshek, Timothy J., & French, Roger H. Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials. United States. doi:10.1063/1.4960180.
Fada, Justin S., Wheeler, Nicholas R., Zabiyaka, Davis, Goel, Nikhil, Peshek, Timothy J., and French, Roger H. Wed . "Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials". United States. doi:10.1063/1.4960180. https://www.osti.gov/servlets/purl/1579854.
@article{osti_1579854,
title = {Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials},
author = {Fada, Justin S. and Wheeler, Nicholas R. and Zabiyaka, Davis and Goel, Nikhil and Peshek, Timothy J. and French, Roger H.},
abstractNote = {In this work, we present a description of an electroluminescence (EL) apparatus, easily sourced from commercially available components, with a quantitative image processing platform that demonstrates feasibility for the widespread utility of EL imaging as a characterization tool. We validated our system using a Gage R&R analysis to fnd a variance contribution by the measurement system of 80.56%, which is typically unacceptable, but through quantitative image processing and development of correction factors a variance contribution by the measurement system of 2.41% was obtained. We further validated the system by quantifying the signal-to-noise ratio (SNR) and found values consistent with other systems published in the literature, at SNR values of 10-100, albeit at exposure times of greater than 1 s compared to 10 ms for other systems. Finally, this SNR value range is acceptable for image feature recognition, providing the opportunity for widespread data acquisition and large scale data analytics of photovoltaics.},
doi = {10.1063/1.4960180},
journal = {Review of Scientific Instruments},
number = 8,
volume = 87,
place = {United States},
year = {2016},
month = {8}
}

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