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3D visualization and analysis of dislocation clusters in multicrystalline silicon ingot by approach of data science.

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Title: 3D visualization and analysis of dislocation clusters in multicrystalline silicon ingot by approach of data science.
Authors: Hayama, Yusuke1, Matsumoto, Tetsuya2, Muramatsu, Tetsuro1, Kutsukake, Kentaro3, Kudo, Hiroaki2, Usami, Noritaka1 usa@material.nagoya-u.ac.jp
Source: Solar Energy Materials & Solar Cells. Jan2019, Vol. 189, p239-244. 6p.
Subjects: Visualization, Dislocation interactions, Silicon, Ingots, Data science
Abstract: Abstract We report on our attempt to perform the three-dimensional (3D) visualization of dislocation clusters in multicrystalline silicon (mc-Si) ingot by processing photoluminescence (PL) images and analysis of dislocation clusters in mc-Si. As-sliced wafers prepared using a high-performance (HP) mc-Si ingot were sequentially measured by PL imaging with intentional superposition of reflection. Then, various image processing techniques were applied to all the PL images to extract dark regions, which most likely correspond to dislocation clusters, as well as microstructures. By 3D reconstruction using a large quantity of 2D images, we could successfully visualize the generation, propagation and annihilation of dislocation clusters in HP mc-Si ingot. In addition, relationship between source region of dislocation clusters and crystal orientation were investigated by combining data scientific and experimental approaches. As a result, it was suggested that small angle grain boundaries with angular deviation of less than 10 degrees cause the generation of dislocation clusters. Highlights • Dislocation clusters in mc-Si were visualized by the PL image processing. • Generation, propagation, and annihilation of dislocation clusters were visualized. • 3D structure of dislocation clusters was revealed. • Small angle grain boundaries are likely to be the source of dislocation clusters. [ABSTRACT FROM AUTHOR]
Copyright of Solar Energy Materials & Solar Cells is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 132854825
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: 3D visualization and analysis of dislocation clusters in multicrystalline silicon ingot by approach of data science.
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  Data: <searchLink fieldCode="AR" term="%22Hayama%2C+Yusuke%22">Hayama, Yusuke</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Matsumoto%2C+Tetsuya%22">Matsumoto, Tetsuya</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Muramatsu%2C+Tetsuro%22">Muramatsu, Tetsuro</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kutsukake%2C+Kentaro%22">Kutsukake, Kentaro</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Kudo%2C+Hiroaki%22">Kudo, Hiroaki</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Usami%2C+Noritaka%22">Usami, Noritaka</searchLink><relatesTo>1</relatesTo><i> usa@material.nagoya-u.ac.jp</i>
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  Data: <searchLink fieldCode="JN" term="%22Solar+Energy+Materials+%26+Solar+Cells%22">Solar Energy Materials & Solar Cells</searchLink>. Jan2019, Vol. 189, p239-244. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Visualization%22">Visualization</searchLink><br /><searchLink fieldCode="DE" term="%22Dislocation+interactions%22">Dislocation interactions</searchLink><br /><searchLink fieldCode="DE" term="%22Silicon%22">Silicon</searchLink><br /><searchLink fieldCode="DE" term="%22Ingots%22">Ingots</searchLink><br /><searchLink fieldCode="DE" term="%22Data+science%22">Data science</searchLink>
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  Data: Abstract We report on our attempt to perform the three-dimensional (3D) visualization of dislocation clusters in multicrystalline silicon (mc-Si) ingot by processing photoluminescence (PL) images and analysis of dislocation clusters in mc-Si. As-sliced wafers prepared using a high-performance (HP) mc-Si ingot were sequentially measured by PL imaging with intentional superposition of reflection. Then, various image processing techniques were applied to all the PL images to extract dark regions, which most likely correspond to dislocation clusters, as well as microstructures. By 3D reconstruction using a large quantity of 2D images, we could successfully visualize the generation, propagation and annihilation of dislocation clusters in HP mc-Si ingot. In addition, relationship between source region of dislocation clusters and crystal orientation were investigated by combining data scientific and experimental approaches. As a result, it was suggested that small angle grain boundaries with angular deviation of less than 10 degrees cause the generation of dislocation clusters. Highlights • Dislocation clusters in mc-Si were visualized by the PL image processing. • Generation, propagation, and annihilation of dislocation clusters were visualized. • 3D structure of dislocation clusters was revealed. • Small angle grain boundaries are likely to be the source of dislocation clusters. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Solar Energy Materials & Solar Cells is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.solmat.2018.06.008
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        Text: English
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        Type: general
      – SubjectFull: Dislocation interactions
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      – SubjectFull: Silicon
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      – SubjectFull: Data science
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              Text: Jan2019
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              Y: 2019
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