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Exploratory Research for Advanced Technology
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Designing composition ratio of magnetic alloy multilayer for transverse thermoelectric conversion by Bayesian optimization
Description/Abstract:
Wedemonstrated the effectiveness of the machine learning method combined with first-principles calculations for the enhancement of the an...
Keyword:
Spin-orbit interactions, First-principle calculations, Superlattices, Informatics, Machine learning, Ferromagnetic materials, Multilayers, Thermoelectric effects
Resource Type:
Article
Author:
Naoki Chiba
,
Keisuke Masuda
,
Ken-ichi Uchida
, and
Yoshio Miura
Journal:
APL Machine Learning
Date Uploaded:
24/05/2024
Zero-magnetic-field operation of ordinary-Nernst-effect-based transverse thermoelectric module using embedded permanent magnets
Description/Abstract:
The ordinary Nernst effect enables large transverse thermoelectric conversion in semimetals but its operation requires the application of...
Keyword:
ordinary Nernst effect
,
permanent magnet
, and
transverse thermoelectric conversion
Resource Type:
Article
Author:
Masayuki Murata
,
Takamasa Hirai
,
Takeshi Seki
, and
Ken-ichi Uchida
Journal:
APPLIED PHYSICS LETTERS
Date Uploaded:
15/05/2024
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Spin-orbit interactions, First-principle calculations, Superlattices, Informatics, Machine learning, Ferromagnetic materials, Multilayers, Thermoelectric effects
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ordinary Nernst effect
1
permanent magnet
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transverse thermoelectric conversion
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English
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AIP Publishing
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Rights Statement Sim
Creative Commons BY Attribution 4.0 International
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In Copyright
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Ken-ichi Uchida
2
Keisuke Masuda
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Masayuki Murata
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Naoki Chiba
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Takamasa Hirai
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Core Research for Evolutional Science and Technology
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Exploratory Research for Advanced Technology
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Japan Society for the Promotion of Science
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ACT-X
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New Energy and Industrial Technology Development Organization
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APL Machine Learning
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APPLIED PHYSICS LETTERS
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