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Insights into metastability of photovoltaic materials at the mesoscale through massive I-V analytics

: Peshek, T.J.; Fada, J.S.; Hu, Y.; Xu, Y.; Elsaeiti, M.A.; Schnabel, E.; Köhl, M.; French, R.H.

Volltext urn:nbn:de:0011-n-4228935 (1.9 MByte PDF)
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Erstellt am: 1.3.2017

Journal of vacuum science and technology B. Microelectronics and nanometer structures 34 (2016), Nr.5, Art. 050801, 12 S.
ISSN: 0734-211X
ISSN: 1071-1023
ISSN: 2166-2746
ISSN: 2166-2754
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer ISE ()
Solarthermie und Optik; Photovoltaik; Silicium-Photovoltaik; Feedstock; Kristallisation und Wafering; Photovoltaische Module und Kraftwerke; Modultechnologie; Gebrauchsdauer- und Schadensanalyse; Photovoltaische Kraftwerke

The authors demonstrate the feasibility of quantifying cell-level performance heterogeneity from module-level I-V curves by determining conditions of bypass diode turn-on. Analysis of these curves falls outside of typical diode-based models of photovoltaic (PV) performance. The authors show that this approach can leverage statistical and machine learning techniques for broad application to massive datasets, and combine those insights with simulations and laboratory-based experiments to provide useful information into the metastability of the interfaces of a PV cell. The authors find good agreement between the experimentally determined curves and the simulated curves, which guide the variable selection in the massive dataset collected from sites in Cleveland, OH, USA, the Negev Desert, Israel, Isla Gran Canaria, Spain, and Mount Zugspitze, Germany.