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Materials development by interpretable machine learning
Yuma Iwasaki, Ryoto Sawada, Valentin Stanev +7
Machine learning technologies are expected to be great tools for scientific discoveries. In particular, materials development (which has brought a lot of innovation by finding new…
Machine-learning guided discovery of a high-performance spin-driven thermoelectric material
Yuma Iwasaki, Ichiro Takeuchi, Valentin Stanev +10
Thermoelectric conversion using Seebeck effect for generation of electricity is becoming an indispensable technology for energy harvesting and smart thermal management. Recently, t…
Flexible heat-flow sensing sheets based on the longitudinal spin Seebeck effect using one-dimensional spin-current conducting films
A. Kirihara, K. Kondo, M. Ishida +9
We demonstrated a flexible thermoelectric (TE) sheet based on the longitudinal spin Seebeck effect (LSSE) that is especially suitable for heat-flow sensing applications. This TE sh…