Graph theory based approach to characterize self interstitial defect morphology

Utkarsh Bhardwaj*, Andrea E. Sand, Manoj Warrier

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
16 Downloads (Pure)


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.

Original languageEnglish
Article number110474
Number of pages9
JournalComputational Materials Science
Publication statusPublished - Jul 2021
MoE publication typeA1 Journal article-refereed


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


Dive into the research topics of 'Graph theory based approach to characterize self interstitial defect morphology'. Together they form a unique fingerprint.

Cite this