Cargando…
Machine-learning guided discovery of a new thermoelectric material
Thermoelectric technologies are becoming indispensable in the quest for a sustainable future. Recently, an emerging phenomenon, the spin-driven thermoelectric effect (STE), has garnered much attention as a promising path towards low cost and versatile thermoelectric technology with easily scalable m...
Autores principales: | Iwasaki, Yuma, Takeuchi, Ichiro, Stanev, Valentin, Kusne, Aaron Gilad, Ishida, Masahiko, Kirihara, Akihiro, Ihara, Kazuki, Sawada, Ryohto, Terashima, Koichi, Someya, Hiroko, Uchida, Ken-ichi, Saitoh, Eiji, Yorozu, Shinichi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391459/ https://www.ncbi.nlm.nih.gov/pubmed/30808974 http://dx.doi.org/10.1038/s41598-019-39278-z |
Ejemplares similares
-
Flexible heat-flow sensing sheets based on the longitudinal spin Seebeck effect using one-dimensional spin-current conducting films
por: Kirihara, Akihiro, et al.
Publicado: (2016) -
Model-Free Cluster Analysis of Physical Property Data using Information Maximizing Self-Argument Training
por: Sawada, Ryohto, et al.
Publicado: (2020) -
Recent Progress on PEDOT-Based Thermoelectric Materials
por: Wei, Qingshuo, et al.
Publicado: (2015) -
Origami-Type Flexible Thermoelectric Generator Fabricated by Self-Folding
por: Sato, Yusuke, et al.
Publicado: (2023) -
A semi-supervised deep-learning approach for automatic crystal structure classification
por: Lolla, Satvik, et al.
Publicado: (2022)