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Predicting Composition of Photo Voltaic Cells Using Neural NetworksA better understanding of IV (current voltage) curve data collected from photo voltaic cells may lead to the construction of solar cells with improved electrical properties. With this in mind, IV curve data from different types of solar cells were acquired from the Photovoltaics and Electrochemical Systems Branch, NASA Glenn Research Center. Neural networks were created to predict the chemical composition of three classes of solar cells. The success of these predictions varied with class.


Document ID
20190033883
Acquisition Source
Ames Research Center
Document Type
Other
Authors
Norman, Thaddeus J.
(InuTeq, LLC Beltsville, MD, United States)
Ranjan, Shubha S.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
December 12, 2019
Publication Date
November 22, 2019
Subject Category
Space Sciences (General)
Report/Patent Number
ARC-E-DAA-TN75359
Funding Number(s)
CONTRACT_GRANT: 80ARC018D0010
Distribution Limits
Public
Copyright
Public Use Permitted.
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