7 citations · 7 across the 5 of their papers we have counts for
5 papers
Control of Covalent Bond Enables Efficient Magnetic Cooling
Xin Tang, Yoshio Miura, Noriki Terada +14
Magnetic cooling, harnessing the temperature change in matter when exposed to a magnetic field, presents an energy-efficient and climate-friendly alternative to traditional vapor-c…
Rapid, Comprehensive Search of Crystalline Phases from X-ray Diffraction in Seconds via GPU-Accelerated Bayesian Variational Inference
Ryo Murakami, Kenji Nagata, Yoshitaka Matsushita +1
In analysis of X-ray diffraction data, identifying the crystalline phase is important for interpreting the material. The typical method is identifying the crystalline phase from th…
Rapid and Robust construction of an ML-ready peak feature table from X-ray diffraction data using Bayesian peak-top fitting
Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa +5
To advance the development of materials through data-driven scientific methods, appropriate methods for building machine learning (ML)-ready feature tables from measured and comput…
Bayesian inference to identify crystalline structures for XRD
Ryo Murakami, Yoshitaka Matsushita, Kenji Nagata +2
Crystalline phase structure is essential for understanding the performance and properties of a material. Therefore, this study identified and quantified the crystalline phase struc…
Magnetic behavior of spin-chain compounds, Sr3ZnRhO6 and Ca3NiMnO6, from heat capacity and ac susceptibility studies
S. Rayaprol, Kausik Sengupta, E. V. Sampathkumaran +1
Heat-capacity (C) and ac susceptibility measurements have been performed on the spin-chain compounds, Sr3ZnRhO6 and Ca3NiMnO6, to establish their magnetic behavior and to explore w…