2 citations · 3 across the 2 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2019★ 1 cited
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…
cond-mat.mtrl-sci2018★ 2 cited
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…
cond-mat.mtrl-sci2016
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…