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Identification and classification of contaminations on wafers using hyperspectral imaging

: Turek, M.; Backhaus, A.; Meyer, S.; Seiffert, U.

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Energy Procedia 92 (2016), S.232-235
ISSN: 1876-6102
International Conference on Crystalline Silicon Photovoltaics (SiliconPV) <6, 2016, Chambéry>
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer CSP ()
Fraunhofer IFF ()

We present a new characterization technique based on hyperspectral imaging applied to silicon wafers. It combines the measurement of spatially and spectrally resolved reflection features and a dedicated subsequent data analysis. This method allows for a rapid localization and classification of defects and contaminations on wafers. Thus, it complements standard imaging techniques such as infrared or luminescence imaging. In our work, we show that hyperspectral imaging is capable of separating clean and contaminated regions including a classification of the contamination type and a quantification of the coverage.