研究者詳細 - 旭　良司

論文 - 旭　良司

分割表示 170 件中 1 - 20 件目／全件表示 >>

Enhancing fluoride-ion conduction via doping-induced anionic ordering in an n = 1 Ba-based Ruddlesden-Popper oxyfluoride structure 査読有り

Chanachai Pattanathummasid, Ryoji Asahi, Alex Kutana, Kazuhiro Mori, Toshiyuki Matsunaga, Tsuyoshi Takami

Solid State Ionics 424 巻頁： 116866 2025年4月

Polyvalent machine-learned potential for cobalt: From bulk to nanoparticles 査読有り国際共著

Marthe Bideault, Jérôme Creuze, Ryoji Asahi, Erich Wimmer

Physical Review Materials 8 巻頁： 123803 2024年12月

Realization of Ideal Ba Promoter State by Simultaneous Incorporation with Co into Carbon-protective Framework for Ammonia Synthesis Catalyst 査読有り

K. Kanishka H. De Silva, Katsutoshi Sato, Takahiro Naito, Takaaki Toriyama, Tomokazu Yamamoto, Ryotaro Aso, Yasukazu Murakami, Pradeep R. Varadwaj, Ryoji Asahi, Koji Inazu, Katsutoshi Nagaoka

Advanced Energy Materials 頁： 2404030 2024年12月

Roadmap on methods and software for electronic structure based simulations in chemistry and materials 招待有り査読有り国際共著

Volker Blum, Ryoji Asahi et al.

Electronic Structure 6 巻 ( 4 ) 頁： 042501 2024年11月

Topochemical Fluoride Exchange Reaction with Anionic Electrons toward Fluoride-Ion Conduction in Layered Ba2–xAxNF1–x (A = Na, K) 査読有り

Chanachai Pattanathummasid, Nozomu Yasufuku, Ryoji Asahi, Alex Kutana, Masato Hagihara, Kazuhiro Mori, and Tsuyoshi Takami

Chemistry of Materials 36 巻 ( 11 ) 頁： 5671 - 5677 2024年5月

Machine learning and atomistic origin of high dielectric permittivity in oxides. 査読有り

Shimano Y, Kutana A, Asahi R

Scientific reports 13 巻 ( 1 ) 頁： 22236 2023年12月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（その他学術会議資料等）出版者・発行元：Scientific Reports

Discovering new stable materials with large dielectric permittivity is important for future energy storage and electronics applications. Theoretical and computational approaches help design new materials by elucidating microscopic mechanisms and establishing structure–property relations. Ab initio methods can be used to reliably predict the dielectric response, but for fast materials screening, machine learning (ML) approaches, which can directly infer properties from the structural information, are needed. Here, random forest and graph convolutional neural network models are trained and tested to predict the dielectric constant from the structural information. We create a database of the dielectric properties of oxides and design, train, and test the two ML models. Both approaches show similar performance and can successfully predict response based on the structure. The analysis of the feature importance allows identification of local geometric features leading to the high dielectric permittivity of the crystal. Dimensionality reduction and clustering further confirms the relevance of descriptors and compositional features for obtaining high dielectric permittivity.

DOI： 10.1038/s41598-023-49603-2

Scopus

PubMed

Molecular dynamics simulations using machine learning potential for a-Si:H/c-Si interface: Effects of oxygen and hydrogen on interfacial defect states 招待有り査読有り国際共著

Semba, T; Mckibbin, J; Jinnouchi, R; Asahi, R

JOURNAL OF MATERIALS RESEARCH ( 38 ) 頁： 5151 - 5160 2023年9月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（その他学術会議資料等）出版者・発行元：Journal of Materials Research

Molecular dynamics simulations of a-Si:H/c-Si models with and without an oxygen layer at the interface were performed using a machine learning potential (MLP) that was efficiently trained using an on-the-fly scheme with ab initio molecular dynamics. The relaxation processes up to 1 ns at 500 and 700 K were simulated using MLP, and snapshots were evaluated using ab initio calculations to examine the in-gap states that could significantly affect the solar cell performance. The results showed that oxygen atoms passivated surface dangling bonds on c-Si, but simultaneously generated strain-induced in-gap states at the Si–O/a-Si interface. The hydrogen atoms suppressed the recrystallization of a-Si, distributed in a-Si particularly at the Si–O/a-Si interface because of the repulsive potential of the Si–O layer and contributed to the reduction of the in-gap states. Our results support experimental observation where optimization of the a-Si:H/O/c-Si interface could improve the performance of solar cells. Graphical abstract: [Figure not available: see fulltext.]

DOI： 10.1557/s43578-023-01155-x

Web of Science

Scopus

Polymorphs of Titanium Dioxide: An Assessment of the Variants of Projector Augmented Wave Potential of Titanium on Their Geometric and Dielectric Properties 査読有り

Pradeep R. Varadwaj, Van An Dinh, Yoshitada Morikawa, Ryoji Asahi

ACS Omega 8 巻 ( 24 ) 頁： 220003 - 22017 2023年6月

Automatic knowledge acquisition from superconductivity information in literature 査読有り

Kento Mitsui, Yutaka Sasaki, Ryoji Asahi

Science and Technology of Advanced Materials: Methods 3 巻頁： 2206532 2023年5月

Challenges for fluoride superionic conductors: fundamentals, design, and applications 招待有り査読有り

Tsuyoshi Takami, Chanachai Pattanathummasid, Alex Kutana, Ryoji Asahi

Journal of Physics: Condensed Matter 35 巻頁： 293002 2023年4月

Permittivity boosting by induced strain from local doping in titanates from first principles 査読有り

A. Kutana, Y. Shimano, R. Asahi

Scientific Reports 13 巻頁： 3761 2023年3月

Ultrafast charge-transfer dynamics in a visible-light-excited iridium(III) terpyridine 2-phenylpyridine complex studied by femtosecond X-ray absorption spectroscopy 査読有り国際共著

K. Yamanaka, T. Morikawa, R. Asahi

JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY 435 巻頁： 114267 2023年2月

Superconductivity information extraction from the literature: A new corpus and its evaluations 査読有り

Kyosuke Yamaguchi, Ryoji Asahi, Yutaka Sasaki

Advanced Engineering Informatics 54 巻頁： 101768 2022年10月

See d-assiste d epitaxy of intermetallic compounds with interface-determined orientation: Incommensurate Nowotny chimney-ladder FeGe? epitaxial film 査読有り

Terada Tsukasa, Kitaura Reona, Ishigaki Shintaro, Ishibe Takafumi, Naruse Nobuyasu, Mera Yutaka, Asahi Ryoji, Nakamura Yoshiaki

ACTA MATERIALIA 236 巻 2022年9月

Doping Effect and Li-Ion Conduction Mechanism of ALi<inf>6</inf>XO<inf>6</inf>(A = K or Rb and X = Pentavalent): A First-Principles Study 査読有り

Lee J., Asahi R.

Journal of Physical Chemistry C 126 巻 ( 32 ) 頁： 13548 - 13559 2022年8月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Journal of Physical Chemistry C

Recent theoretical and experimental evaluations demonstrated that KLi6TaO6 is a good Li-ion conductor. In this study, the energetics and detailed mechanism of Li-ion migration, relevant to the point defects of KLi6TaO6, were analyzed by first-principles calculations. Defect formation energy analysis suggested that it has limited chemical potential conditions for attaining Li-excess conditions through doping (substituting tetravalent elements for Ta). The formation of other native defects, such as Li vacancies, hinders the stabilization of the dopant and compensates for the interstitial Li. When the doping is successful, the interactions between the coexisting dopant and interstitial Li can increase the migration energy barrier of the interstitial Li. This phenomenon limits the factors responsible for achieving high Li-ion conductivity in this material. Based on the results of the investigations on KLi6TaO6, isostructural materials of the form ALi6XO6, with various combinations of constituent elements A and X, were each screened on the basis of high stability and low Li-ion migration energy. Twelve structures of the form (A = K or Rb)Li6XO6 were suggested, of which X was pentavalent. They also exhibited limited chemical potential conditions for achieving Li-excess conditions through doping. Combinations of the suggested isostructural oxides and dopants were identified to reduce the interactions between interstitial Li and dopant. Some isostructural oxides were doped using Sn and were evaluated using first-principles molecular dynamics; their Li-ion conductivities at room temperature were found to be comparable with those of garnet-type Li-ion conductors.

DOI： 10.1021/acs.jpcc.2c02357

Scopus

Theoretical and Experimental Studies of KLi6TaO6 as a Li-Ion Solid Electrolyte 査読有り

Suzuki Nobuaki, Lee Joohwi, Masuoka Yumi, Ohta Shingo, Kobayashi Tetsuro, Asahi Ryoji

INORGANIC CHEMISTRY 60 巻 ( 14 ) 頁： 10371 - 10379 2021年7月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（その他学術会議資料等）出版者・発行元：Inorganic Chemistry

We study a hexagonal oxide KLi6TaO6 (KLTO), proposed as a Li-ion solid electrolyte, by using a recently developed screening method. First-principles calculations predict that KLTO presents a good Li-ion conductivity (σLi) and a low activation energy (Ea). Li migration is enhanced by the presence of excess Li ions in the interstitial region via a kick-out mechanism. Our experimental results demonstrate that Sn-doped KLTO presents a conductivity of 1 × 10-5 S cm-1, a σLi of 6 × 10-6 S cm-1, and a relatively low Ea of 36 kJ mol-1, which confirm the validity of the proposed screening method. Conversely, detailed analyses of the microstructure and X-ray diffraction patterns of KLTO samples indicate that a stable Li-excess condition is not achieved, therefore leaving potential improvement of the performance of KLTO as a Li-ion solid electrolyte by optimizing extrinsic doping and fabrication processes.

DOI： 10.1021/acs.inorgchem.1c00902

Web of Science

Scopus

PubMed

Transfer learning for materials informatics using crystal graph convolutional neural network 査読有り

Lee Joohwi, Asahi Ryoji

COMPUTATIONAL MATERIALS SCIENCE 190 巻 2021年4月