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Visualization of Self-sorted Local Atomic Motifs in disordered solids

Published online by Cambridge University Press:  08 May 2018

Aly Rahemtulla Open the ORCID record for Aly Rahemtulla [Opens in a new window] ,
Bruno Tomberli  and
Stefan Kycia
Aly Rahemtulla*
Affiliation:
Department of Physics, University of Guelph, Guelph, Ontario, Canada
Bruno Tomberli
Affiliation:
Department of Physics, Capilano University, North Vancouver, British Columbia, Canada
Stefan Kycia
Affiliation:
Department of Physics, University of Guelph, Guelph, Ontario, Canada
*
*(Email: [email protected])
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Abstract

The structural descriptions of even the most basic amorphous materials are under considerable debate. In this work, an intuitive computational technique has been developed to construct 3D statistical density maps to directly visualize and identify local atomic structures from simple monatomic amorphous germanium (a-Ge) to complex multi-atom systems such as copper zirconium metallic glass. We show motifs in copper zirconium that are unresolvable through traditional tools such as Voronoi indexing. This self-sorted local atomic motif (SLAM) method builds upon the Kabsch algorithm incorporating techniques in computer vision to produce least-squares optimized 3D density maps. Simultaneously, the SLAM method incorporates self-contained categorization to define local motifs based upon atomic structures. We present the methodology of the SLAM method and also present resulting motifs comparing models a-Ge and demonstrate its broad capability on metallic glass.

Keywords

amorphousmetalinteratomic arrangementsmodeling
Type
Articles
Information
MRS Advances , Volume 3 , Issue 39: Characterization, Modeling and Theory , 2018 , pp. 2353 - 2358
Copyright
Copyright © Materials Research Society 2018 

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