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An Evaluation of an Automated Detection Algorithm to Count Defects Present in X-Ray Topographical Images of SiC Wafers

Published online by Cambridge University Press:  01 February 2011

Ian Brazil ,
Patrick J. McNally ,
Lisa O'Reilly ,
Andreas Danilewsky ,
Turkka O. Tuomi ,
Aapo Lankinen ,
Antti Säynätjoki ,
Rolf Simon ,
Stanislav Soloviev  and
Larry B. Rowland
...Show all authors
Ian Brazil
Affiliation:
[email protected], RINCE, Dublin City University, Dublin 9,, Ireland, Dublin, N/A, Ireland
Patrick J. McNally
Affiliation:
[email protected], Dublin City University, RINCE, Dublin, 9, Ireland
Lisa O'Reilly
Affiliation:
[email protected], Dublin City University, RINCE, Dublin, 9, Ireland
Andreas Danilewsky
Affiliation:
[email protected], Universität Freiburg, Kristallographisches Institute, Freiburg, N/A, Germany
Turkka O. Tuomi
Affiliation:
[email protected], Helsinki University of Technology, Helsinki, N/A, Finland
Aapo Lankinen
Affiliation:
[email protected], Helsinki University of Technology, Helsinki, N/A, Finland
Antti Säynätjoki
Affiliation:
[email protected], Helsinki University of Technology, Helsinki, N/A, Finland
Rolf Simon
Affiliation:
[email protected], Institut für Synchrotronstrahlung (ISS), Karlsruhe, N/A, Germany
Stanislav Soloviev
Affiliation:
[email protected], GE Global Research, Niskayuna, NY, 12309, United States
Larry B. Rowland
Affiliation:
[email protected], GE Global Research, Niskayuna, NY, 12309, United States
Peter M. Sandvik
Affiliation:
[email protected], GE Global Research, Niskayuna, NY, 12309, United States
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Abstract

An evaluation of an algorithm used to extract Threading Screw Dislocation defect data from Synchrotron White Beam X-Ray Topographical images of SiC wafers is reported.This extraction involves a two-fold process; firstly the algorithm highlights the appropriate defect and secondly updates the counter to provide a final result of defect count.The result of the automated algorithm is compared to hand counts in all cases, this allowing a critical analysis of the technique.Improvements to this algorithm have been made since last reported by the same authors, which are discussed. The analysis herein was also performed on a much larger sample of SiC wafer images than previously used by the same authors [1] allowing a better judgment of performance and critical evaluation.The algorithm is also compared with a previous algorithm that was used.Advantages and deficiencies in the algorithm are outlined and other potential avenues for extraction of the data are also discussed.

Keywords

crystaldefectsdislocations
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 994: Symposium F – Semiconductor Defect Engineering–Materials, Synthetic Structures and Devices II , 2007 , 0994-F11-13
Copyright
Copyright © Materials Research Society 2007

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References

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