Graph theory based approach to characterize self interstitial defect morphology

No Thumbnail Available

Access rights

openAccess

URL

Journal Title

Journal ISSN

Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2021-07

Major/Subject

Mcode

Degree programme

Language

en

Pages

9

Series

Computational Materials Science, Volume 195

Abstract

The defect morphology is an essential aspect of the evolution of crystal microstructure and its response to stress. While reliable and efficient standard computational algorithms exist for finding defect concentration and size distribution in a crystal, defect morphology identification is still nascent. The need for an efficient and comprehensive algorithm to study defects is becoming more evident with the increase in the amount of simulation data and improvements in data-driven algorithms. We present a method to characterize a defect's morphology precisely by reducing the problem into graph theoretical concepts of finding connected components and cycles. The algorithm can identify the different homogenous components within a defect cluster having mixed morphology. We apply the method to classify morphologies of over a thousand point defect clusters formed in high energy W collision cascades. We highlight our method's comparative advantage for its completeness, computational speed, and quantitative details.

Description

Publisher Copyright: © 2021 Elsevier B.V. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

Collision cascades, Defect morphology, Defects in crystal, Graph applications, Molecular dynamics, Radiation damage

Other note

Citation

Bhardwaj, U, Sand, A E & Warrier, M 2021, ' Graph theory based approach to characterize self interstitial defect morphology ', Computational Materials Science, vol. 195, 110474 . https://doi.org/10.1016/j.commatsci.2021.110474