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Comparison of various methods for large scale dislocation density characterization
|B. Gallien 1, Thierry Duffar 1, J. P. Garandet 2, S. Bailly 2, G. Stokkan 3|
1. SIMaP EPM, CNRS UJF, BP 75, Saint Martin d'Heres cedex 38402, France
|In the industry of silicon for photovoltaic application, the crystalline quality of the material is an important criterion as much as duration of the solidification process or the kerf loss due to the sawing of the ingot in wafers. Indeed, defects in the crystal lead directly to a decrease of photovoltaic efficiency of a solar cell.
Defects in the crystal matrix can be grain boundaries, precipitates, impurities or dislocations, which are the issue of this study. In the material, dislocations are generated by the application of a stress, generally created by the thermal field or the attachment between the crucible and the ingot. The dislocation have intrinsic activity due to the presence of dangling bonds at its core, but also act indirectly through the trapping of metallic impurities or their role as nucleation centers for oxygen precipitates, meaning that dislocations are often efficient minority carrier recombination centers. Due to the size of the ingots grown in industrial practice, where 450 kg is now a minimum, the characterization of dislocations in photovoltaic material requires a quick and efficient method which can be applied to large scale samples.
In this study, our purpose is to compare various characterization techniques on a sample of several square centimeters. To start with, the sample, a thin plate of silicon, is polished to obtain a mirror surface and etched to reveal dislocations. The reference method is to count them one by one with an optical microscope in order to obtain a precise and exhaustive map of dislocation density.
After this slow but necessary dislocation density characterization, the sample is submitted to different faster methods. First, a high resolution scanner is used to take a picture of the sample. The grey scale of this picture can be linked to dislocation density. In a second method, a Scanning Electron Microscope is used to take small pictures of several parts of the same sample. These pictures are treated with an image processing software, developed at INES laboratory, which recognizes and counts etch pits and gives the dislocation density. In a third method the sample is characterized by PVscan, an instrument used by photovoltaic industries to estimate the dislocation density of their wafers. The fourth method has been developed at NTNU and consists in illuminating the sample with an incident light and measuring the diffused light with a CCD camera. The results of these four methods are finally compared to the precise map obtained by the reference technique in order to draw conclusions concerning their accuracy and efficiency.
Presentation: Poster at 17th International Conference on Crystal Growth and Epitaxy - ICCGE-17, General Session 7, by Thierry Duffar
See On-line Journal of 17th International Conference on Crystal Growth and Epitaxy - ICCGE-17
Submitted: 2013-04-12 18:43 Revised: 2013-07-23 16:37