Inline Mapping of Amorphous Silicon Layer Thickness of Heterojunction Precursors Using Multispectral Imaging
DOI:
https://doi.org/10.52825/siliconpv.v2i.1324Keywords:
Amorphous Silicon, Inline Characterization, Silicon Heterojunction Solar Cells, Thickness Maps, Multispectral ImagingAbstract
In this paper, we present an inline characterization technique to determine spatially resolved thickness maps of ultra-thin layers on textured silicon substrates. The technique is based on multispectral imaging and optical modelling of discrete spectral reflectance data using rigorous polarization ray tracing and the transfer matrix method. The study demonstrates that quantitative inspection of ultra-thin amorphous silicon (a-Si) layers on textured silicon substrates requires an extension of the standard RGB illumination by two additional LED wavelengths in the near-UV. As the required five images are measured in less than a second, the tool is a suitable candidate for inline applications. The optical modelling requires reflectance-calibrated images which are obtained via linear calibration functions and allows the a-Si thickness to be determined at each pixel. The thin-film thickness can be determined either by a direct modelling of the measured reflectance spectra or by a differential approach using the reflectance spectra before and after coating to eliminate effects from non-idealities due to scattering as well as instrumental errors. The a-Si thickness extracted from the reflection data at the five chosen LED wavelengths shows good quantitative agreement with reference values from spectrally-resolved differential reflectance data. Evaluating a test sample with an intentional a-Si thickness variation, we compared the results from the multispectral thickness map and reference values from spectroscopic ellipsometry. We found good quantitative agreement for a-Si thicknesses above 10 nm and a slight overestimation of about 1.5 nm for thinner layers. Overall, the multispectral approach based on only five different channels proves to allow quantitative thickness maps with reasonable accuracy at inline speed.
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Copyright (c) 2024 Saravana Kumar, Christian Diestel, Saed Al-Hajjawi, Jurriaan Schmitz, Marc Hemsendorf, Jonas Haunschild, Stefan J. Rupitsch, Stefan Rein
This work is licensed under a Creative Commons Attribution 4.0 International License.
Accepted 2024-09-10
Published 2025-01-03
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Bundesministerium für Wirtschaft und Klimaschutz
Grant numbers 03EE1096A