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The Crystal Growth Explorer: Real-Time Navigable 3D Visualization of Silicon Grains and Defect Related Data in Cast-Mono and Multicrystalline Bricks

: Schönauer, J.; Demant, M.; Trötschler, T.; Kovvali, A.S.; Schremmer, H.; Krenckel, P.; Riepe, S.; Rein, S.

Volltext urn:nbn:de:0011-n-6181855 (2.2 MByte PDF)
MD5 Fingerprint: b1cae0186969893a6dcdd15208105a35
Erstellt am: 11.12.2020

Pearsall, Nicola (Editor):
37th European Photovoltaic Solar Energy Conference and Exhibition, EU PVSEC 2020 : 07-11 September 2020, Online Conference
München: WIP, 2020
ISBN: 3-936338-73-6
European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) <37, 2020, Online>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ISE ()
Photovoltaik; cast mono; characterization; crystallization; data analytics; dislocation; grain; machine learning; SMART seeding; visualization; Silicium-Photovoltaik; feedstock; Kristallisation; wafering; Charakterisierung von Prozess- und Silicium-Materialien

Development of novel materials for silicon solar cell production like SMART mono material with functional grain boundaries depends on the human insight and understanding of the structural and dynamic properties of the underlying crystallization process. In this work, we present an analysis and visualization process that allows for comfortable, flexible human exploration and interpretation of various crystallization-related data types ranging from per-wafer photographic images and defect measurements to segmented and 3D-reconstructed grain and defect data, by putting and combining them in a concrete, meaningful, vivid visualization context close to the spatial structure of the actual grown crystal. We address two urgent challenges for smart mono development by combining appropriate data analysis and inspection methods: (1st) analyzing crystal growth characteristics for non-destructive quality inspection and (2nd) investigating defect scenarios for identifying the best crystallization recipes.