Identifying flow defects in amorphous alloys using machine learning outlier detection methods
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1631475
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Scripta Materialia
- Additional Journal Information:
- Journal Name: Scripta Materialia Journal Volume: 186 Journal Issue: C; Journal ID: ISSN 1359-6462
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Tian, Liang, Fan, Yue, Li, Lin, and Mousseau, Normand. Identifying flow defects in amorphous alloys using machine learning outlier detection methods. United States: N. p., 2020.
Web. doi:10.1016/j.scriptamat.2020.05.038.
Tian, Liang, Fan, Yue, Li, Lin, & Mousseau, Normand. Identifying flow defects in amorphous alloys using machine learning outlier detection methods. United States. https://doi.org/10.1016/j.scriptamat.2020.05.038
Tian, Liang, Fan, Yue, Li, Lin, and Mousseau, Normand. Tue .
"Identifying flow defects in amorphous alloys using machine learning outlier detection methods". United States. https://doi.org/10.1016/j.scriptamat.2020.05.038.
@article{osti_1631475,
title = {Identifying flow defects in amorphous alloys using machine learning outlier detection methods},
author = {Tian, Liang and Fan, Yue and Li, Lin and Mousseau, Normand},
abstractNote = {},
doi = {10.1016/j.scriptamat.2020.05.038},
journal = {Scripta Materialia},
number = C,
volume = 186,
place = {United States},
year = {2020},
month = {9}
}
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https://doi.org/10.1016/j.scriptamat.2020.05.038
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