Achievements(Media coverage)

FY2023

An introduction video of hypermaterials "It's interesting because I don't understand! What is hypermaterial? IV Physical properties edition"
Takanobu Hiroto(A02), Yutaka Iwasaki, Erina Fujita(A01)
Youtube 22/9/2023
Accelerating the Phase Identification of Multiphase Mixtures with Deep Learning
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
Yomiuri Shimbun Online 17/11/2023
Tokyo University of Science, Institute of Statistical Mathematics, etc. discover new quasicrystals by identifying powder X-ray diffraction patterns using deep learning
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
Nihon Keizai Shimbun electronic version 17/11/2023
Discovery of new quasicrystals by identifying powder X-ray diffraction patterns using deep learning - Detecting the presence of new quasicrystal phases in multiphase mixtures -
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
Japanese studies.com 17/11/2023
Discovery of new quasicrystals by identifying powder X-ray diffraction patterns using deep learning
Link provided：Map information search site Mapion
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
Mapion news 17/11/2023
Accelerating the phase identification of multiphase mixtures with deep learning
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
EurekAlert! 17/11/2023
Deep learning model can detect a previously unknown quasicrystalline phase
URL:https://phys.org/news/2023-11-deep-previously-unknown-quasicrystalline-phase.html
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
PHYS.ORG 17/11/2023
Deep Learning's Role in Phase Identification
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
AZO MATERIALS 17/11/2023
Deep learning model detects a previously unknown quasicrystalline phase
Hirotaka Uryu, Tsunetomo Yamada, Yutaka Iwasaki, Kaoru Kimura, Ryuji Tamura, (A01), Ryo Yoshida(A03)
Hitech Glitz
Institute of Statistical Mathematics, Tokyo University of Science, and the University of Tokyo develop machine learning technology to predict chemical compositions that form thermally stable quasicrystals
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Nihon Keizai Shimbun electronic version 28/09/2023
Quasicrystals discovered by machine learning at National Institute of Statistical Science etc., “First in 40 years”
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Nikkei Tech Foresight 12/10/2023
Quasicrystal discovered using machine learning algorithm "First in 40 years"
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Science Newspaper 20/10/2023

FY2022

Clarification of magnetic dynamics in ferromagnetically ordered phase in quasicrystal
Shinji Watanabe (A04)
TECH+ 29/06/2022
Tokyo University of Science, new ideas for developing functional substances "New physical properties" by controlling the surrounding environment of elements
Ryuji Tamura (A01)
Nikkan Kogyo Shimbun 17/11/2022 (You may need to register as a member to view articles.)
Material that shrinks when heated. Could eliminate thermal expansion when semiconductor devices operate
Takumi Nishikubo, Takashi Imai, Yuki Sakai, Masaichiro Mizumaki, Shogo Kawaguchi,Norihiro Oshime, Ayumu Shimada, Kento Sugawara, Kenji Ohwada, Akihiko Machida, Tetsu Watanuki,Kosuke Kurushima, Shigeo Mori, Takashi Mizokawa, and Masaki Azuma (A02)
Nikkei Science 25/3/2023
Material that shrinks when heated Highest Performance Tokyo Institute of Technology Overcomes Thermal Expansion of Precision Parts
Takumi Nishikubo, Takashi Imai, Yuki Sakai, Masaichiro Mizumaki, Shogo Kawaguchi,Norihiro Oshime, Ayumu Shimada, Kento Sugawara, Kenji Ohwada, Akihiko Machida, Tetsu Watanuki,Kosuke Kurushima, Shigeo Mori, Takashi Mizokawa, and Masaki Azuma (A02)
Nikkei Sangyo Shinbun 6/2/2023
Material that Shrinks without Expanding when Cured Highest performance achieved Tokyo Institute of Technology, etc.
Takumi Nishikubo, Takashi Imai, Yuki Sakai, Masaichiro Mizumaki, Shogo Kawaguchi,Norihiro Oshime, Ayumu Shimada, Kento Sugawara, Kenji Ohwada, Akihiko Machida, Tetsu Watanuki,Kosuke Kurushima, Shigeo Mori, Takashi Mizokawa, and Masaki Azuma (A02)
Nikkei Shinbun Web 27/1/2023

FY2021

The Institute of Statistical Mathematics, AI to identify chemical composition of quasicrystals Accelerate search for new substances
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Nikkan Kogyo Shimbun　　27/07/2021
Discovered the law of predicting quasicrystal phase formation using machine learning, such as the Institute of Statistical Mathematics
Ryo Yoshida, Yukari Katsura (A03)
Mynavi News　　21/07/2021
The Institute of Statistical Mathematics, The University of Tokyo, Tokyo University of Science identifies the chemical composition that forms quasicrystals by machine learning
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Nihon Keizai Shimbun　　21/07/2021
Tokyo University of Science et al. Predict the chemical composition of quasicrystals by machine learning
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
OPTRONICS ONLINE　　21/07/2021
Discovered the law of predicting quasicrystal phase formation using machine learning, such as the Institute of Statistical Mathematics
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Mapion News * Reprinted from Mynavi News　　21/07/2021
The Institute of Statistical Mathematics, The University of Tokyo, Tokyo University of Science identifies the chemical composition that forms quasicrystals by machine learning
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
NEWS PICKS * Reprinted from Nihon Keizai Shimbun　　21/07/2021
Identifying the chemical composition that forms quasicrystals by machine learning The first step toward elucidating the stabilization mechanism of quasicrystals
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
Japanese studies.com　　21/07/2021
Machine learning to predict new quasicrystals
Ryo Yoshida, Yukari Katsura (A03), Kaoru Kimura, Ryuji Tamura (A01)
EurekAlert　　29/07/2021
Topics of "Solid State Physics": Two-Dimensional Extension of Thouless Pumping and Diophantine Equation in Ultracold Atoms
Fuyuki Matsuda, Masaki Tezuka(A04), Norio Kawakami
Solid State Physics Vol.56 No.8　　15/08/2021
Editor's choice of "Materials": "Reduction of Thermal Conductivity for Icosahedral Al-Cu-Fe Quasicrystal through Heavy Element Substitution"
Yoshiki Takagiwa(A04), Ryota Maeda, Satoshi Ohhashi and An-Pang Tsai
Materials Vol.14(18)　　12/09/2021
Discovery of magnetism in quasicrystal alloys Possibility of developing the world's first new material by Professor Tamura of Tokyo University of Science (From Fuchu)
R. Tamura　(A01)
Kita Nihon Shimbun　　24/01/2022
New trends in change from the perspective of nice-step researchers
Division of Integrated Materials Development and Information Technology, National Institute for Materials Science
Interview with Senior Researcher Yukari Katsura
-Construct a large-scale material physical properties database by collecting past experimental data from papers-
Yukari Katsura(A03)
STI Horizon National Institute for Science and Technology Policy (NISTEP)　　15/11/2021
"Thermoelectric power generation" that takes advantage of the temperature difference, safe and low cost without using rare metals with familiar materials (Asahi Shimbun Digital (3/29) Membership registration is required to subscribe to the electronic version.)
Yoshiki Takagiwa　(A04)
Asahi Shimbun　　29/03/2022
'Quasicrystals': Intricate orders
Nobuhisa Fujita (A02)
Yomiuri Shinbun (Evening edition)　　24/02/2022

FY2020

MI accelerates material development
Y. Takagiwa　(A04)
BS Fuji "Galileo X"　　12/4/2020
Chuo University announces publication of a paper on current-driven tricritical points in Physical Review Letters
S. Nakamura　(A04)
Nihon Keizai Shimbun　　04/06/2020
Person zoom up Toyama
R. Tamura　(A01)
Kita Nihon Shimbun　　05/11/2020
Independent power supply for sensor drive Realized with general-purpose elements
Y. Takagiwa　(A04)
The Nikkan Kogyo Shimbun　　02/12/2020
Thermoelectric conversion, two new materials
Y. Takagiwa　(A04)
The Nikkei Sangyo Shimbun　　15/12/2020
Featured papers in the November 2020 issue of JPSJ: Extension of Thouless pump in cold atom systems to two dimensions and Diophantine equations
M. Tezuka　(A04)
Butsuri　　05/01/2021
Featured papers in the November 2020 issue of JPSJ: Extension of Thouless pump in cold atom systems to two dimensions and Diophantine equations
M. Tezuka　(A04)
Website of the Physical Society of Japan　　November/2020
Explore the mystery of a mysterious object has fallen from the sky
Y.Matsushita　(A02)
ABC "Detective! Knight scoop"　　29/01/2021
Succeeded in developing a calculation method that can theoretically predict complex magnetic structures with high accuracy and efficiency, such as the University of Tokyo, RIKEN, and Tohoku University.
M.-T. Suzuki　(A04)
Nihon Keizai Shimbun　　18/2/2021
A difference of one hundred billionth of a meter dramatically changes the properties of matter!
-Discover new functions of regular icosahedron cluster-
K. Imura　(A04)
Japanese reseach.com　　21/10/2020
The mysterious nature of quasicrystals fascinated by beautiful mathematical models
K. Imura　(A04)
academist Journal　　10/02/2021

FY2019

Major events in the chemical and related industries in the second half of 2019 Small-scale thermoelectric power generation module with general-purpose elements 1 / 5th cost IoT sensor
Y. Takagiwa　(A04)
The Chemical Daily　　27/12/2019
Thermoelectric power generation materials that generate electricity by using a slight temperature difference in the environment
Y. Takagiwa　(A04)
TBS "Origin of the Future"　　27/10/2019
There's more! Promising Science & Venture (Ryo Yoshida Laboratory, Institute of Statistical Mathematics)
R. Yoshida　(A03)
Weekly Diamond Vol. 107, No. 41　　26/10/2019
"Small temperature difference power generation" that produces electricity with the warmth of the palm is a strong ally of the sensor
Y. Takagiwa　(A04)
DG LAB HAUS　　3/10/2019
Realized IoT battery-free technology
Y. Takagiwa　(A04)
Nikkei Electronics　　1/10/2019
Developed a thermoelectric power generation module that is both economical and environmentally friendly
Y. Takagiwa　(A04)
New Enegy News　　19/9/2019
Generator that does not waste body temperature
Y. Takagiwa　(A04)
TV Tokyo "the Trend Egg corner" of World Business Satellite　　9/9/2019
Expected for independent power sources such as IoT devices Thermoelectric power generation module with general-purpose elements
Y. Takagiwa　(A04)
The Science News　　30/8/2019
Temperature difference power generation with common materials
Y. Takagiwa　(A04)
NIKKEI BUSINESS DAILY　　30/8/2019
What is the world's first "temperature difference power generation" that realizes low cost of less than 1/5?
Y. Takagiwa　(A04)
Yahoo! News　　25/8/2019
Modules that generate thermoelectric power with common elements and slight temperature differences
Y. Takagiwa　(A04)
EE Times Japan　　23/8/2019
Power generation with a slight temperature difference-no rare elements included
Y. Takagiwa　(A04)
NIKKEI　　22/8/2019
Developed "thermoelectric generator" device-composed of readily available alloy
Y. Takagiwa　(A04)
NIKKAN KOGYO SHIMBUN　　22/8/2019
Thermoelectric power generation module-Developed only with general-purpose elements such as iron and aluminum
Y. Takagiwa　(A04)
Japan Metal Daily　　22/8/2019
Aluminium-Iron-Silicon thermoelectric material Succeeded in the world's first power generation module
Y. Takagiwa　(A04)
NIKKEI BUSINESS DAILY　　22/8/2019
Small thermoelectric power generation module, low cost with general-purpose elements
Y. Takagiwa　(A04)
The Chemical Daily　　22/8/2019
Developed the world's first thermoelectric power generation module with NEDO, Aisin Seiki, etc ... Power generation by body temperature is also possible
Y. Takagiwa　(A04)
Response 20th　　22/8/2019
What's amazing？"Thermoelectric power generation" module developed by NEDO , Aisin Seiki, etc.
Y. Takagiwa　(A04)
NEWSWITCH　　22/8/2019
Thermoelectric power generation with common elements, IoT devices move even with a temperature difference of 5 ° C
Y. Takagiwa　(A04)
MONOist　　22/8/2019
Developed thermoelectric power generation module consisting only of general-purpose elements-Significantly reduced material costs, does not contain rare or toxic elements, and can generate power in low temperature range
Y. Takagiwa　(A04)
fab cross for engineer　　22/8/2019
What materials are required to improve thermoelectric power generation efficiency?
Y. Takagiwa　(A04)
Daily Chemical News　　5/9/2019