30 citations · 40 across the 5 of their papers we have counts for
5 papers
Bayesian sparse modeling for interpretable prediction of hydroxide ion conductivity in anion-conductive polymer membranes
Ryo Murakami, Kenji Miyatake, Ahmed Mohamed Ahmed Mahmoud +2
Anion-conductive polymer membranes have attracted considerable attention as solid electrolytes for alkaline fuel cells and electrolysis cells. Their hydroxide ion conductivity vari…
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…
Pressure-induced Insulator to Metal Transition of Mixed Valence Compound Ce(O,F)SbS
Ryo Matsumoto, Masanori Nagao, Masayuki Ochi +11
Transport properties of CeF0.15SbS and undoped CeOSbS under high pressure were investigated experimentally and theoretically. Electrical resistivity measuremen…
Data-driven Exploration of New Pressure-induced Superconductivity in PbBiTe with Two Transition Temperatures
Ryo Matsumoto, Zhufeng Hou, Masanori Nagao +10
Candidates compounds for new thermoelectric and superconducting materials, which have narrow band gap and flat bands near band edges, were exhaustively searched by the high-through…