Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Adam M. Krajewski"'
Autor:
Shun-Li Shang, Hui Sun, Bo Pan, Yi Wang, Adam M. Krajewski, Mihaela Banu, Jingjing Li, Zi-Kui Liu
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
Abstract Forming metallurgical phases has a critical impact on the performance of dissimilar materials joints. Here, we shed light on the forming mechanism of equilibrium and non-equilibrium intermetallic compounds (IMCs) in dissimilar aluminum/steel
Externí odkaz:
https://doaj.org/article/b68a38ee573649ef94441fb0dd41cb05
Autor:
Shun Li Shang, Hui Sun, Shanshank Priya, Shuang Lin, Allison M. Beese, Zi Kui Liu, Wenjie Li, Adam M. Krajewski, Wesley F. Reinhart, Marcia Ahn, Jogender Singh, Arindam Debnath
Generative deep learning is powering a wave of new innovations in materials design. In this article, we discuss the basic operating principles of these methods and their advantages over rational design through the lens of a case study on refractory h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::527df515c8a0ba2d36d78edb7e4414b8
http://arxiv.org/abs/2108.12019
http://arxiv.org/abs/2108.12019
Autor:
Hui Sun, Zi Kui Liu, Timothy Lichtenstein, Nathan D. Smith, Brandon Bocklund, Adam M. Krajewski, Sanghyeok Im, Shun Li Shang, Hojong Kim
Publikováno v:
SSRN Electronic Journal.
Thermodynamic properties of the Nd-Bi system were investigated using a combination of experimental measurements, first-principles calculations based on density functional theory (DFT), machine learning (ML) predictions, and calculation of phase diagr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc76221c9e05b08f954e069c7fc18033
https://doi.org/10.2139/ssrn.3894900
https://doi.org/10.2139/ssrn.3894900
Publikováno v:
SSRN Electronic Journal.
In recent years, numerous studies have employed machine learning (ML) techniques to enable orders of magnitude faster high-throughput materials discovery by augmentation of existing methods or as standalone tools. In this paper, we introduce a new ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3005cdc1e5537e0b5256983e8ff28d5a
https://doi.org/10.2139/ssrn.3721830
https://doi.org/10.2139/ssrn.3721830
Autor:
Shun Li Shang, Brandon Bocklund, Sanghyeok Im, Adam M. Krajewski, Nathan D. Smith, Hojong Kim, Timothy Lichtenstein, Hui Sun, Zi Kui Liu
Publikováno v:
Acta Materialia. 223:117448
Thermodynamic properties of the Nd-Bi system were investigated using a combination of experimental measurements, first-principles calculations based on density functional theory (DFT), data mining and machine learning (DM + ML) predictions, and calcu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67365a97dbeac689f664c64669b8a918
https://doi.org/10.1016/j.actamat.2021.117448
https://doi.org/10.1016/j.actamat.2021.117448