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Proceedings Paper

Ramification algorithm for graphene sample-defect localization
Author(s): Andre Sokolnikov
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Paper Abstract

Recent development of a new 2D material graphene necessitates sample characterization (in particular localization and distribution of defects). The presence of defects is unavoidable, however, it is possible to determine and predict defect distribution in graphene samples prior to the actual device making. A ramification algorithm is used for the above purpose.

Paper Details

Date Published: 28 May 2015
PDF: 12 pages
Proc. SPIE 9476, Automatic Target Recognition XXV, 947611 (28 May 2015); doi: 10.1117/12.2180380
Show Author Affiliations
Andre Sokolnikov, Visual Solutions and Applications (United States)


Published in SPIE Proceedings Vol. 9476:
Automatic Target Recognition XXV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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