Zobrazeno 1 - 10
of 203
pro vyhledávání: '"Field, Kevin"'
Autor:
Lynch, Matthew J., Jacobs, Ryan, Bruno, Gabriella, Patki, Priyam, Morgan, Dane, Field, Kevin G.
The integration of machine learning (ML) models enhances the efficiency, affordability, and reliability of feature detection in microscopy, yet their development and applicability are hindered by the dependency on scarce and often flawed manually lab
Externí odkaz:
http://arxiv.org/abs/2408.01558
Precipitates are main microstructural features to provide high temperature creep strength and radiation resistance in structural materials for fusion energy systems. However, the mechanisms of precipitate stability under irradiation in candidate stru
Externí odkaz:
http://arxiv.org/abs/2407.19589
Reduced activation ferritic/martensitic (RAFM) steels are the leading candidate structural materials for first-wall and blanket components in fusion reactors. This work is the first in a series to provide a systematic roadmap of MX precipitate stabil
Externí odkaz:
http://arxiv.org/abs/2407.10002
Accurately quantifying swelling of alloys that have undergone irradiation is essential for understanding alloy performance in a nuclear reactor and critical for the safe and reliable operation of reactor facilities. However, typical practice is for r
Externí odkaz:
http://arxiv.org/abs/2208.01460
Autor:
Jacobs, Ryan, Shen, Mingren, Liu, Yuhan, Hao, Wei, Li, Xiaoshan, He, Ruoyu, Greaves, Jacob RC, Wang, Donglin, Xie, Zeming, Huang, Zitong, Wang, Chao, Field, Kevin G., Morgan, Dane
In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional Neural Network (Mask R-CNN) model. We conduct an in-depth analysis of
Externí odkaz:
http://arxiv.org/abs/2110.08244
Autor:
Shen, Mingren, Li, Guanzhao, Wu, Dongxia, Liu, Yuhan, Greaves, Jacob, Hao, Wei, Krakauer, Nathaniel J., Krudy, Leah, Perez, Jacob, Sreenivasan, Varun, Sanchez, Bryan, Torres, Oigimer, Li, Wei, Field, Kevin, Morgan, Dane
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis. In this work, we d
Externí odkaz:
http://arxiv.org/abs/2108.08883
Autor:
Shen, Mingren, Li, Guanzhao, Wu, Dongxia, Yaguchi, Yudai, Haley, Jack C., Field, Kevin G., Morgan, Dane
Videos captured using Transmission Electron Microscopy (TEM) can encode details regarding the morphological and temporal evolution of a material by taking snapshots of the microstructure sequentially. However, manual analysis of such video is tedious
Externí odkaz:
http://arxiv.org/abs/2108.08882
Publikováno v:
In Journal of Nuclear Materials May 2024 593
Autor:
Qu, Haozheng J., Higgins, Maria, Abouelella, Hamdy, Cappia, Fabiola, Burns, Jatuporn, He, Lingfeng, Massey, Caleb, Harp, Jason, Field, Kevin G., Howard, Richard, Umretiya, Rajnikant V., Hoffman, Andrew K., Wharry, Janelle P., Rebak, Raul B.
Publikováno v:
In Journal of Nuclear Materials 15 December 2023 587
Autor:
Patki, Priyam V., Pownell, Timothy J., Bazarbayev, Yerik, Zhang, Dalong, Field, Kevin G., Wharry, Janelle P.
Publikováno v:
In Journal of Nuclear Materials February 2023 574