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- Revolutional material development by fusion of strong experiments with theory/data science/
- [Revolutional Materials Development] Year Started : 2019
Senior Researcher
Center for Basic Research on Materials
National Institute for Materials Science
Masakazu Akiyama | Associate Professor Faculty of Science, Academic Assembly University of Toyama |
Tohru Sugahara | Professor Faculty of Materials Science and Engineering Kyoto Institute of Technology |
Masaya Fujioka | Senior Researcher Innovative Functional Materials Research Institute Advanced Industrial Science and Technology |
Haruhiko Morito | Associate Professor Institute for Materials Research Tohoku University |
We change the experimental searches for new inorganic materials more efficient and innovative, with the data science. From mathematics and machine learning, we develop an original simulator like a 3D puzzle, which assists us to design periodic crystal structures. Large-scale experimental searches for new compounds are carried out by Na-flux method and proton-driven ion implantation. Out of the newly-investigated compounds, we select the candidate functional materials such as thermoelectric materials, by first-principles calculations and machine learning of literature data. We will then design the best electrodes for the material, to fabricate an application device made of the new material.
Group Leader
Research Center for Electronic and Photonic Materials
National Institute for Materials Science
Hidekazu Ikeno | Associate Professor Graduate School of Engineering Osaka Metropolitan University |
Satoru Matsuishi | Principal Researcher Research Center for Materials Nanoarchitectonics National Institute for Materials Science |
We built a cyclic system of experimental, calculation and data science, and develop high performance phosphors by synthesizing and characterizing all candidates proposed form data science. By a combination of experimental design proposed from data science, high-throughput experiments that can realize many trials more than 1000 samples in one year and multiplet calculations, and we explore unknown area beyond human idea.
Field Director
Research Center for Macromolecules and Biomaterials
National Institute for Materials Science
Chiaki Sato | Professor Institute of Innovative Research Tokyo Institute of Technology |
Keitaro Sodeyama | Group Leader Center for Basic Research on Materials National Institute for Materials Science |
We will establish data-centric molecular design for development of supercomposite materials with extraordinary properties that cannot be achieved by combination of existing materials. In this project, artificial intelligence (AI) plays key role on prediction of chemical reactions and polymer properties. Various physical / chemical data of the AI-predicted materials are fastly and efficiently collected at an automated smart laboratory. Synergetic collaboration of AI and smart lab enables us to accelarete the development period of the supercomposite materials.
Professor
Faculty of Science and Technology
Keio University
Hiroaki Sukegawa | Group Leader Research Center for Magnetic and Spintronic Materials National Institute for Materials Science |
Seiji Yunoki | Chief Scientist Advanced Science Institute RIKEN |
Shinichi Watanabe | Professor Faculty of Science and Technology Keio University |
The conventional spin current generation relies on the spin-dependent scattering effect inherent in rare materials. Consequently, the degree of freedom in material design for spin devices has been seriously restricted. In this project, we develop a novel technology to generate spin current in functionally graded materials consisting of two or more conventional materials with controlled interfaces where electrical conductivity is highly modulated in nanometer scale. We improve the flexibility in material design of spin devices by providing a novel control axis called non-uniform spin-dependent scattering. We will demonstrate the practical operation of spin devices utilizing the functionally graded materials developed in this project.