[Revolutional Materials Development] Year Started : 2019

Yukari Katsura

Development of innovative functional materials based on large-scale search for new crystals

Grant No.:JPMJCR19J1
Research Director
Yukari Katsura

Senior Researcher
Center for Basic Research on Materials
National Institute for Materials Science

Collaborator
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
Outline

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.

Takashi Takeda

Development of phosphors based on experiment and data science

Grant No.:JPMJCR19J2
Research Director
Takashi Takeda

Group Leader
Research Center for Electronic and Photonic Materials
National Institute for Materials Science

Collaborator
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
Outline

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.

Masanobu Naito

Data-centric Molecular Design for Development of Supercomposite Materials

Grant No.:JPMJCR19J3
Research Director
Masanobu Naito

Field Director
Research Center for Macromolecules and Biomaterials
National Institute for Materials Science

Collaborator
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
Outline

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.

Yukio Nozaki

Development of functionally graded materials and application to spin devices by combining nano-structure control and computational science

Grant No.:JPMJCR19J4
Research Director
Yukio Nozaki

Professor
Faculty of Science and Technology
Keio University

Collaborator
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
Outline

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.

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