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Quantifying dislocation-type defects in post irradiation examination via transfer learning.

Michael Wu¹, Jeremy Sharapov¹, Matthew Anderson²

¹Idaho National Laboratory, Idaho Falls, ID, USA.

Scientific Reports

|May 7, 2025

Summary

This summary is machine-generated.

This study introduces an automated method for quantifying dislocation defects in irradiated nuclear materials using a computer vision model. This approach enhances accuracy and efficiency compared to manual analysis, improving materials characterization.

Keywords:

Dislocation defect quantification Machine learning Post irradiation examination

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Area of Science:

Materials Science
Nuclear Engineering
Computer Vision

Background:

Quantitative analysis of dislocation defects in irradiated materials is crucial for nuclear energy applications.
Manual defect identification is time-consuming, subjective, and prone to inconsistencies.

Purpose of the Study:

To develop an automated, accurate, and efficient tool for identifying and quantifying dislocation-type defects in irradiated materials.
To leverage transfer learning with a computer vision model for defect segmentation.

Main Methods:

Utilized the YOLOv11 open-source computer vision model for defect identification and segmentation.
Employed transfer learning with a minimal set of annotated micrographs for training.
Applied the model to transmission electron microscopy images of irradiated alloys with varying noise levels.

Main Results:

The YOLOv11 model successfully segmented dislocation lines and loops concurrently, even in high-noise micrographs.
The model demonstrated effectiveness on alloys not included in the training set.
Achieved high accuracy in defect quantification across diverse irradiated alloys.

Conclusions:

The developed computer vision tool offers a highly effective and reliable method for dislocation defect quantification.
This automated approach significantly improves upon traditional manual analysis in materials characterization for the nuclear industry.
The tool is applicable to practical post-irradiation examination analyses.