Analysis of grain structure evolution based on optical measurements of mc Si wafers

Abstract Grain structure and grain competition have a strong impact on bulk lifetime in multicrystalline (mc) silicon. A fast and thorough characterization of grain structure is crucial in order to improve industrial crystal growth. This work introduces key parameters of grain structure, extracted with a newly developed image processing tool. Four bricks grown with different concepts were chosen to investigate the value of the identified key parameters and to identify characteristic developments along the brick. Optical measurements on as-cut wafers from these bricks serve as a basis to extract grain structure properties, i.e., size, shape, homogeneity and distribution of grain size. By connecting the 2D-information over brick height, a statistical insight into the entire brick is gained. Weighted percentiles of grain area offer a robust measure to characterize grain size distribution. As twinning has a large impact on grain competition, twinned grains are detected via grain shape. Additionally, regions with strong grain competition are highlighted for investigations on grain overgrowth. It is found that the share of twin grains increases with brick height in high-performance mc (HPM) silicon with fine-granular seeds from almost zero up to about 15% whereas it remains rather constant over the whole brick height in standard mc-Si. The results of the investigated bricks show clearly that towards the brick top, the material differences in grain size decrease. This suggests that an energetically favorable state may exist for grain structure development.

[1]  K. Fujiwara,et al.  Formation mechanism of parallel twins related to Si-facetted dendrite growth , 2007 .

[2]  J. Friedrich,et al.  Influence of different seed materials on multi-crystalline silicon ingot properties , 2016 .

[3]  C. Lan,et al.  Development of grain structures of multi-crystalline silicon from randomly orientated seeds in directional solidification , 2014 .

[4]  Ye Zhou,et al.  Segmentation of petrographic images by integrating edge detection and region growing , 2004, Comput. Geosci..

[5]  Qiang Liu,et al.  Automated grain boundary detection using the level set method , 2009, Comput. Geosci..

[6]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[8]  Chung-Wen Lan,et al.  Development of high‐performance multicrystalline silicon for photovoltaic industry , 2015 .

[9]  K. Fujiwara,et al.  Arrangement of dendrite crystals grown along the bottom of Si ingots using the dendritic casting method by controlling thermal conductivity under crucibles , 2011 .

[10]  Jochen Friedrich,et al.  Laue scanner: A new method for determination of grain orientations and grain boundary types of multicrystalline silicon on a full wafer scale , 2014 .

[11]  Noritaka Usami,et al.  Generation mechanism of dislocations during directional solidification of multicrystalline silicon using artificially designed seed , 2010 .

[12]  Thomas Brox,et al.  Inline quality rating of multi‐crystalline wafers based on photoluminescence images , 2016 .

[13]  Chung-Wen Lan,et al.  Grain control in directional solidification of photovoltaic silicon , 2012 .

[14]  Xinming Huang,et al.  Seed-assisted growth of high-quality multi-crystalline silicon in directional solidification , 2014 .

[15]  T. Duffar,et al.  On the twinning occurrence in bulk semiconductor crystal growth , 2010 .

[16]  T. Sekiguchi,et al.  Grain growth of cast-multicrystalline silicon grown from small randomly oriented seed crystal , 2014 .

[17]  Joan Serrat,et al.  Segmentation of petrographical images of marbles , 1996 .