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Filtering by: Author Keisuke Masuda Author Ken-ichi Uchida Funder Core Research for Evolutional Science and Technology

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