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Inline Characterization of Diamond Wire Sawn Multicrystalline Silicon Wafers

: Haunschild, J.; Bergmann, N.; Hammer, T.; Krieg, K.; Kaden, T.; Anspach, O.; Schremmer, H.; Rein, S.

Fulltext urn:nbn:de:0011-n-5486061 (568 KByte PDF)
MD5 Fingerprint: b405af813383c75cb4b3108cb587a7ba
Created on: 18.6.2019

Verlinden, P. ; WIP - Renewable Energies, München:
35th European Photovoltaic Solar Energy Conference and Exhibition 2018 : Proceedings of the international conference held in Brussels, Belgium, 24 September-28 September 2018; DVD-ROM
München: WIP, 2018
ISBN: 978-3-936338-50-8
ISBN: 3-936338-50-7
European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) <35, 2018, Brussels>
Conference Paper, Electronic Publication
Fraunhofer ISE ()
Inline-Wafer-/Prozessanalytik und Bildverarbeitung; Photovoltaik; Silicium-Photovoltaik; Charakterisierung von Prozess- und Silicium-Materialien; characterization; silicon; sawing; wire

While for monocrystalline silicon ingot slicing diamond wire sawing processes are widely used, the general approach for slicing multicrystalline bricks has been based on slurry wire processes. Driven by a strong decrease in wafer prices recently, wafer manufacturers of multicrystalline materials switched rather quickly to the diamond-cut process, although several severe technological challenges were to be faced. Unfortunately, sawing is more difficult and an adaptation of solar cell production is essential for texturing processes considering diamond-cut wafer surface morphology. Also characterization methodologies must be adapted to these new material properties. Especially saw mark inspection and thickness topology measurements are key aspects of developments. General imaging methods also need to be evaluated for defect detection and wafer rating purpose. In this paper, an overview of inline characterization methods and their applicability on diamond-cut wafers will be given. Five out of eight methods need hardware or software adjustments to work on diamond-cut wafers. Special attention is paid to the photoluminescence analysis which allows a forecast of solar cell parameters if the relevant defect features are correctly extracted from the images. Due to the increased optical artifacts, this is not a trivial task.