Employing infrared microscopy (IRM) in combination with a pre-trained neural network to visualise an...
Employing infrared microscopy (IRM) in combination with a pre-trained neural network to visualise and analyse the defect distribution in Cadmium Telluride crystals
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Author / Creator
Kirschenmann, S , Bharthuar, S , Brücken, E , Golovleva, M , Gädda, A , Kalliokoski, M , Luukka, P , Ott, J and Winkler, A
Publisher
Ithaca: Cornell University Library, arXiv.org
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Language
English
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Ithaca: Cornell University Library, arXiv.org
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Contents
While Cadmium Telluride (CdTe) excels in terms of photon radiation absorption properties and outperforms silicon (Si) in this respect, the crystal growth, characterization and processing into a radiation detector is much more complicated. Additionally, large concentrations of extended crystallographic defects, such as grain boundaries, twins, and t...
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Full title
Employing infrared microscopy (IRM) in combination with a pre-trained neural network to visualise and analyse the defect distribution in Cadmium Telluride crystals
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Record Identifier
TN_cdi_proquest_journals_2562648399
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2562648399
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2108.08279
