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How to count the number of dislocation junctions

Dear Constanze & Alex,

In this paper:  https://www.nature.com/articles/nature23472 refer Extended Data Figure 7 | Network evolution along a stepwise increase
in the strain rates.

I want to know how to count the number of binary and triadic junctions?

Best wishes

Luling Wang

Uploaded files:
  • 16387776401.png

Hi,

This analysis was performed outside of OVITO, I think. Vasily Bulatov and his co-workers at Lawrence Livermore National Lab developed a workflow (based on Matlab, I think) for parsing CA dislocation files (like those written by OVITO) into a nodal representation, which makes it easier to analyze network topologies. A nodal network representation consists of a list of nodal points. Each node is associated with the list of linear segments connected to it (can be 2, 3, 4, etc. segments). I suggest you contact Vasily Bulatov or Nicolas Bertin if you would like to get access to the analysis tools they developed.

That being said, I've worked on something similar later on. Maybe it can be of use to you too: https://gitlab.com/stuko/dxa

The ca2nodal tool is a small standalone program written in C++, which can parse a .ca file and write out the line network to a nodal representation format. Feel free to use this code or adapt it to your needs.

Within OVITO's DXA implementation, the dislocation line network is still equipped with nodal connectivity information, and counting different kinds of nodes would be straightforward based on this internal representation. However, the CA export file format and the Python scripting interface (see class DislocationNetwork) both use a line-centric representation having no explicit notion of junctions. This makes statistical analyses of the network topology a bit cumbersome. We'll hopefully address this in the future when the DXA function in OVITO will get reworked completely.

-Alex

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