Study of residual stress in porous silicon during drying

Jiran Liang; Ming Hu; Yilan Kang; Yanwei Dou

doi:10.1117/12.717285

6 November 2006 Study of residual stress in porous silicon during drying

Jiran Liang, Ming Hu, Yilan Kang, Yanwei Dou

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 635746 (2006) https://doi.org/10.1117/12.717285
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

Porous silicon has been extensively researched as an interesting photoluminescent material for photoelectric device integration. Residual stress often occurs due to capillary force during drying and results in warp, fracture and failure of the devices. Micro-Raman spectroscopy (MRS) has many special advantages of nondestructive, non-contact, high spatial resolution (1μm), broad spectrum range, Raman shift unaffected by the frequency of laser source, and ability to focus on a specific layer of sample. Furthermore, Raman spectrum is a powerful tool for the study of residual stress for its sensitivity to strain in the sample, which make it possible to measure residual stress directly. The underlying basis of micro-Raman spectroscopy for strain measurement is that Raman shift reflects the atomic spacing change, namely the strain information. The residual stress was measured during drying using Micro-Raman spectrum technology, the maxim is 3.6GPa. The relation of residual stress and Raman shift, drying times and FWHM were analysed, the capillary effect and the residual stress evolution from wetting to drying stages of porous silicon were investigated using phonon confinement model.

Citation Download Citation

Jiran Liang, Ming Hu, Yilan Kang, and Yanwei Dou "Study of residual stress in porous silicon during drying", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 635746 (6 November 2006); https://doi.org/10.1117/12.717285

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