Computer Vision-aided in situ TEM Studies of Microstructure Evolution under Irradiation
Author:
Affiliation:
1. Argonne National Laboratory , Lemont, IL , United States
2. University of Illinois – Urbana-Champaign , Urbana, IL , United States
3. University of Pennsylvania , Philadelphia, PA , United States
Publisher
Oxford University Press (OUP)
Subject
Instrumentation
Link
https://academic.oup.com/mam/article-pdf/29/Supplement_1/1495/50934901/ozad067.768.pdf
Reference5 articles.
1. DefectTrack: a deep learning-based multi-object tracking algorithm for quantitative defect analysis of in-situ TEM videos in real-time;Sainju;Scientific Report
2. A deep learning based automatic defect analysis framework for In-situ TEM ion irradiations;Shen;Comput. Mater. Sci,2021
3. Recent Studies on Void Shrinkage in Metallic Materials Subjected to In Situ Heavy Ion Irradiations;Niu;JOM,2020
4. The use of the high voltage electron microscope to simulate fast neutron-induced void swelling in metals;Norris;J. Nucl. Mater,1971
5. Void shrinkage in 21Cr32Ni austenitic model alloy during in-situ ion irradiation;Ayanoglu;J. Nucl. Mater.,2021
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