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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . 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.
Highlights
F UNDAMENTAL understanding or empirical knowledge of the temperature dependence of a process step in a solar cell production is often essential for efficient process development or optimization
The results can be used for industrial optimization of a boron–oxygen-related defect regeneration process
We introduce the temperature screening imaging analysis to investigate the temperature dependence of BO defect regeneration with a laser-based rapid thermal processing (RTP) furnace, including a temperature imaging system
Summary
F UNDAMENTAL understanding or empirical knowledge of the temperature dependence of a process step in a solar cell production is often essential for efficient process development or optimization. This process can be performed in an industrial solar cell production with electrical injection and heating or a laser-based regeneration tool [1], [2]. Screening a broad temperature range with at least one sample per temperature can, be a material- and time-consuming approach. The emphasis in this article is to reduce the time and material consumption for process optimizations regarding the temperature and to get a complete picture of the influence of a wide temperature range. This approach is transferable to other temperature-dependent process optimizations and even fundamental research. The requirement is the technical possibility to induce a temperature gradient within the sample and have a spatially resolved quantitative measurement of the target quantity—such as the efficacy of the process
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