Paper
13 September 2011 A novel approach for correlating capacitance data with performance during thin-film device stress studies
Rebekah L. Graham, Laura A. Clark, David S. Albin
Author Affiliations +
Abstract
A new data mining algorithm was developed to identify the strongest correlations between capacitance data (measured between -1.5 V and +0.49 V) and first- and second-level performance metrics (efficiency [η%], open-circuit voltage [VOC], short-circuit current density [JSC], and fill-factor [FF]) during the stress testing of voltage-stabilized CdS/CdTe devices. When considering only correlations between first- and second-level metrics, 96.5% of the observed variation in η% was attributed to FF. The overall decrease in VOC after 1,000 hours of open-circuit, light-soak stress at 60°C was about -1.5%. As determined by our algorithm, the most consistent correlation existing between FF and third-level metric capacitance data at all stages during stress testing was between FF and the apparent CdTe acceptor density (Na) calculated at a voltage of +0.49 V during forward voltage scans. Since the contribution of back-contact capacitance to total capacitance increases with increasing positive voltage, this result suggests that FF degradation is associated with decreases in Na near the CdTe/back contact interface. Also of interest, it appears that capacitance data at these higher voltages appears to more accurately fit the one-sided abrupt junction model.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rebekah L. Graham, Laura A. Clark, and David S. Albin "A novel approach for correlating capacitance data with performance during thin-film device stress studies", Proc. SPIE 8112, Reliability of Photovoltaic Cells, Modules, Components, and Systems IV, 81120V (13 September 2011); https://doi.org/10.1117/12.896648
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Cited by 4 scholarly publications.
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KEYWORDS
Capacitance

Sodium

Data mining

Remote sensing

Solar cells

Solar energy

Reliability

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