Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Naohiro Fujinuma"'
Publikováno v:
Communications Materials, Vol 3, Iss 1, Pp 1-9 (2022)
Machine learning is an increasingly important tool for materials science. Here, the authors suggest that its contextual use, including careful assessment of resources and bias, judicious model selection, and an understanding of its limitations, will
Externí odkaz:
https://doaj.org/article/92ea40334d394a9784760a26b7c35f56
Autor:
Naohiro Fujinuma, Samuel E. Lofland
Publikováno v:
Advanced Intelligent Systems, Vol 5, Iss 5, Pp n/a-n/a (2023)
Machine learning (ML) can be a powerful tool to expedite materials research, but the deployment for experimental research is often hindered by data scarcity and model uncertainty. An human‐in‐the‐loop procedure to tailor the implementation of M
Externí odkaz:
https://doaj.org/article/a276dc412fe24f4085557a914382bc89
Publikováno v:
Molecules, Vol 26, Iss 7, p 1962 (2021)
To address the issue of global warming and climate change issues, recent research efforts have highlighted opportunities for capturing and electrochemically converting carbon dioxide (CO2). Despite metal doped polymers receiving widespread attention
Externí odkaz:
https://doaj.org/article/2c4de2b831c94416894f4d52d9d8106e
Autor:
Samuel Lofland, Naohiro Fujinuma
Publikováno v:
Advanced Intelligent Systems. 5
Autor:
Naohiro Fujinuma, Samuel E. Lofland
Publikováno v:
ECS Meeting Abstracts. :1848-1848
Publikováno v:
Advanced Energy Materials. 10:2070164
Publikováno v:
Advanced Energy Materials. 10:2001645
Autor:
Katsutoshi Endo, Masahiro Yamashita, Hiroyuki Matsuzaki, Taishi Takenobu, Jinpeng Li, Naohiro Fujinuma, Yoshihiro Iwasa, Kosuke Sawabe, Shinya Takaishi, Hiroshi Okamoto
Publikováno v:
Journal of Materials Chemistry. 21:17662
A new molecule, 1,3,6,8-tetramethylpyrene (TMPY), with a similar shape to the luminescent material perylene has been successfully synthesized. The co-crystals with perylene doping have been grown and their crystal structure has been clarified by X-ra