Temperature gradient image analysis to optimize an ultrafast regeneration of boron–oxygen-related defects
Abstract: In this study, we introduce a temperature screening image analysis to investigate the temperature dependence of boron-oxygen-related defect regeneration achieved by using one sample. For that purpose, we induce a temperature gradient in a single sample over a broad temperature range in our laser-based rapid thermal processing furnace, while other influencing factors are kept constant. Spatially resolved measurements of the temperature during the regeneration process (thermographic images) and photoluminescence (PL) images at different boron-oxygen-related defect states are recorded. By a pixelwise assignment of the PL images to the temperature image, the effectiveness of the regeneration process in terms of regeneration completeness is evaluated for each pixel. In this experiment, we investigate the temperature dependence of a boron-oxygen-related defect regeneration in a temperature range of 100-500 °C for different treatment times of 2-30 s at an illumination intensity of 100 kW/m 2 . Thereby, we determine the temperature regimes that allow for efficient regeneration for the respective regeneration parameter set with a single sample. The results can be used for industrial optimization of a boron-oxygen-related defect regeneration process. Furthermore, this technique can also be applied to other temperature-dependent process optimizations and even fundamental research
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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IEEE journal of photovoltaics. - 11, 3 (2021) , 606-612, ISSN: 2156-3403
- Klassifikation
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Elektrotechnik, Elektronik
- Ereignis
-
Veröffentlichung
- (wo)
-
Freiburg
- (wer)
-
Universität
- (wann)
-
2023
- Urheber
- DOI
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10.1109/jphotov.2021.3063659
- URN
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urn:nbn:de:bsz:25-freidok-2341091
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:45 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Roder, Sebastian
- Niewelt, Tim
- Brand, Andreas
- Schneider, Jale
- Nekarda, Jan
- Universität
Entstanden
- 2023
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