Yoshitaka Matsushita

National Institute for Materials Science

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Kazunari Yamaura

National Institute for Materials Science

AА

Alexei А. Belik

National Institute for Materials Science

Masahiko Tanaka

National Institute for Materials Science

Yoshihiro Tsujimoto

National Institute for Materials Science

Katsuhiko Ariga

National Institute for Materials Science

Jonathan P. Hill

National Institute for Materials Science

Yoshio Katsuya

National Institute for Materials Science

Jan Labuta

National Institute for Materials Science

Francis D’Souza

University of North Texas

Masayuki Takeuchi

National Institute for Materials Science

Cooperative Institutions

National Institute for Materials Science

452

The University of Tokyo

251

University of Tsukuba

Tohoku University

Osaka University

Kyoto University

Japan Science and Technology Agency

127

Tokyo Institute of Technology

119

Hokkaido University

National Institute of Advanced Industrial Science and Technology

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Unconventional Luminescent Centers in Metastable Phases Created by Topochemical Reduction Reactions

Angewandte Chemie (2016)

Bo‐Mei Liu Zhigang Zhang Kai Zhang Yoshihiro Kuroiwa Chikako Moriyoshi

Abstract A low‐temperature topochemical reduction strategy is used herein to prepare unconventional phosphors with luminescence covering the biological and/or telecommunications optical windows. This approach is demonstrated by using Bi III ‐doped Y 2 O 3 (Y 2− x Bi x O 3 ) as a model system. Experimental results suggest that topochemical treatment of Y 2− x Bi x O 3 using CaH 2 creates randomly distributed oxygen vacancies in the matrix, resulting in the change of the oxidation states of Bi to lower oxidation states. The change of the Bi coordination environments from the [BiO 6 ] octahedra in Y 2− x Bi x O 3 to the oxygen‐deficient [BiO 6− z ] polyhedra in reduced phases leads to a shift of the emission maximum from the visible to the near‐infrared region. The generality of this approach was further demonstrated with other phosphors. Our findings suggest that this strategy can be used to explore Bi‐doped or other classes of luminescent systems, thus opening up new avenues to develop novel optical materials.

Metastability

10.1002/ange.201601191

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Citations (7)

CSD 2005612: Experimental Crystal Structure Determination

The Cambridge Structural Database (2019)

Motoharu Imai Akira Sato Yoshitaka Matsushita

10.25505/fiz.icsd.cc25b05q

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Citations (0)

CSD 1824962: Experimental Crystal Structure Determination

The Cambridge Structural Database (2018)

Jie Chen Yoshitaka Matsushita Taras Kolodiazhnyi Alexei А. Belik Yoshihiro Tsujimoto

Crystal (programming language)

10.25505/fiz.icsd.cc1z80r0

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Citations (0)

CSD 2213752: Experimental Crystal Structure Determination

The Cambridge Structural Database (2022)

Jie Chen Yasuhisa Tsujimoto Alexei А. Belik Kazunari Yamaura Yoshitaka Matsushita

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Crystal (programming language)

10.25505/fiz.icsd.cc2d9lcp

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Anomalous Peak Effect in the Tl2Ba2CaCu2O8+y Single-Crystal

Springer eBooks (1995)

Hiroshi Ikeda Ryozo Yoshizaki Yoshitaka Matsushita Masashi Hasegawa Humihiko Taker

Hysteresis

Crystal (programming language)

10.1007/978-4-431-68535-7_46

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Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data

Science and Technology of Advanced Materials Methods (2024)

Ryo Murakami Taisuke Sasaki Hideki Yoshikawa Yoshitaka Matsushita Keitaro Sodeyama

To advance the development of materials through data-driven scientific methods, appropriate methods for building machine learning (ML)-ready feature tables from measured and computed data must be established. In materials development, X-ray diffraction (XRD) is an effective technique for analysing crystal structures and other microstructural features that have information that can explain material properties. Therefore, the fully automated extraction of peak features from XRD data without the bias of an analyst is a significant challenge. This study aimed to establish an efficient and robust approach for constructing peak feature tables that follow ML standards (ML-ready) from XRD data. We challenge peak feature extraction in the situation where only the peak function profile is known a priori, without knowledge of the measurement material or crystal structure factor. We utilized Bayesian estimation to extract peak features from XRD data and subsequently performed Bayesian regression analysis with feature selection to predict the material property. The proposed method focused only on the tops of peaks within localized regions of interest (ROIs) and extracted peak features quickly and accurately. This process facilitated the rapid extracting of major peak features from the XRD data and the construction of an ML-ready feature table. We then applied Bayesian linear regression to the maximum energy product (BH)max, using the extracted peak features as the explanatory variable. The outcomes yielded reasonable and robust regression results. Thus, the findings of this study indicated that 004 peak height and area were important features for predicting (BH)max.

Feature (linguistics)

10.1080/27660400.2024.2384352

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Crystal structure and properties of high-pressure-synthesized BiRhO3, LuRhO3, and NdRhO3

Journal of Solid State Chemistry (2013)

Wei Yi Qifeng Liang Yoshitaka Matsushita Masahiko Tanaka Xiao Hu

10.1016/j.jssc.2013.01.035

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Citations (16)

Triple A-Site Cation Ordering in the Ferrimagnetic Y₂CuGaMn₄O₁₂ Perovskite

Inorganic Chemistry (2022)

Alexei А. Belik D. D. Khalyavin Yoshitaka Matsushita Kazunari Yamaura

A new member of A-site columnar-ordered A2A'A″B4O12 quadruple perovskites with the composition of Y2CuGaMn4O12 was prepared by a high-pressure, high-temperature method at 6 GPa and about 1500 K. Its crystal structure and cation distributions were studied by powder synchrotron X-ray and neutron diffraction. There is a triple A-site cation ordering with some degrees of anti-site disorder among sites occupied by 3d transition metals: [Y2]A[Cu0.8Mn0.2]A'[Ga0.8Mn0.2]A″[Mn3.6Cu0.2Ga0.2]BO12. It has the space group P42/nmc (no. 137) between 1.5 and 873 K with a = 7.33884 Å and c = 7.66251 Å at 297 K. Despite anti-site disorder, it exhibits a long-range ferrimagnetic order at TC = 115 K with the ordered moment of 2.19 μB at each B site and 0.89 μB at the A' or A″ site. Magnetic moments are aligned along the c axis; all moments are ordered ferromagnetically at the B sites, and the moments at the A' or A″ site are ordered in the opposite direction. Cu2+ doping drastically changes magnetic properties as "parent" Y2MnGaMn4O12 just shows spin-glass magnetic properties without long-range ordering. Anisotropic thermal expansion was observed in Y2CuGaMn4O12: the lattice parameter a almost linearly decreases from 1.5 K to TC and then monotonically increases up to 873 K (almost linearly from 300 K); the parameter c monotonically increases from 1.5 to 300 K and then decreases up to 600 K.

Ferrimagnetism

Lattice constant

Atmospheric temperature range

10.1021/acs.inorgchem.2c02343

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Citations (10)

A family of oxide–carbide–carbon and oxide–nitride–carbon nanocomposites

Chemical Communications (2013)

Zoë Schnepp Martin J. Hollamby Masahiko Tanaka Yoshitaka Matsushita Yanfei Xu

This paper describes a powerful and versatile approach that combines the benefits of sol-gel processing with controlled phase separation to yield oxide-carbide-carbon or oxide-nitride-carbon nanocomposites.

Carbon nitride

Carbon fibers

10.1039/c3cc47480a

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Citations (9)

Effect of Ca substitution on crystal structure and band gap of solar cell material BaSi2

Journal of Solid State Chemistry (2024)

Motoharu Imai Yoshitaka Matsushita

Crystal (programming language)

Substitution (logic)

10.1016/j.jssc.2024.124549

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Citations (0)