Investigation of defect properties in Cu(In,Ga)Se2 solar cells by deep-level transient spectroscopy
| Autor: | Rommel Noufi, Woo Kyoung Kim, L.L. Kerr, Sheng S. Li, Oscar D. Crisalle, Timothy J. Anderson, J. Abushama, Steve Johnston |
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| Rok vydání: | 2004 |
| Předmět: |
Materials science
Deep-level transient spectroscopy business.industry Chalcopyrite Photovoltaic system Analytical chemistry Electron Condensed Matter Physics Copper indium gallium selenide solar cells Electronic Optical and Magnetic Materials Photovoltaics visual_art Materials Chemistry visual_art.visual_art_medium Optoelectronics Electrical and Electronic Engineering business Relevant information Voltage |
| Zdroj: | Solid-State Electronics. 48:1579-1586 |
| ISSN: | 0038-1101 |
| DOI: | 10.1016/j.sse.2004.03.005 |
| Popis: | The performance of the chalcopyrite material Cu(In,Ga)Se 2 (CIGS) used as an absorber layer in thin-film photovoltaic devices is significantly affected by the presence of native defects. The deep-level transient spectroscopy (DLTS) technique is used in this work to characterize the defect properties, yielding relevant information about the defect types, their capture cross-sections, and energy levels and densities in the CIGS cells. Three solar cells developed using different absorber growth technologies were analyzed using DLTS, capacitance–voltage ( C – V ), and capacitance–temperature ( C – T ) techniques. It was found that CIS cells grown at the University of Florida exhibits a middle-gap defect level that may relate to the cell's low fill factor and open-circuit voltage values observed. A high efficiency ( η c >18%) CIGS cell produced by the National Renewable Energy Laboratory (NREL) was found to contain three minority-carrier (electron) traps and a 13% CIGS cell produced by the Energy Photovoltaics Inc. (EPV) exhibited one majority (hole) trap. The approach followed using the DLTS technique serves as a paradigm for revealing the presence of significant defect levels in absorber materials, and may be used to support the identification of remedial processing operations. |
| Databáze: | OpenAIRE |
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