J-GLOBAL ID:200901008315137305   Update date: Jun. 08, 2020

Maezono Ryo

マエゾノ リョウ | Maezono Ryo
Affiliation and department:
Homepage URL  (2): http://www.jaist.ac.jp/is/labs/maezono-labhttp://www.jaist.ac.jp/is/labs/maezono-lab
Research field  (8): Computational science ,  Inorganic and coordination chemistry ,  Bio-, chemical, and soft-matter physics ,  Semiconductors, optical and atomic physics ,  Magnetism, superconductivity, and strongly correlated systems ,  Semiconductors, optical and atomic physics ,  Nanobioscience ,  Nanomaterials
Research keywords  (1): Materials Informatics
Research theme for competitive and other funds  (21):
  • 2019 - 2021 Computational phonon analysis for mixed anion compounds
  • 2017 - 2020 Computational studies on Phonon Engineering
  • 2018 - 2019 Artificial intelligence capable to distinguish materials phases from spectrum pictures
  • 2017 - 2019 Materials Informatics applied to spectroscopies and microscopic materials structures
Show all
Papers (66):
  • Takayoshi Oshima, Tom Ichibha, Kenji Oqmhula, Keisuke Hibino, Hiroto Mogi, Shunsuke Yamashita, Kotaro Fujii, Yugo Miseki, Kenta Hongo, Daling Lu, Ryo Maezono, Kazuhiro Sayama, Masatomo Yashima, Koji Kimoto, Hideki Kato, Masato Kakihana, Hiroshi Kageyama, Kazuhiko Maeda. Two-Dimensional Perovskite Oxynitride K2LaTa2O6N with an H+/K+ Exchangeability in Aqueous Solution to Form Stable Photocatalyst for Visible-Light H2 Evolution. Angew. Chem., Int. Ed. 2020. 59
  • Masashi Nakamura, Kenji Oqmhula, Keishu Utimula, Miharu Eguchi, Kengo Oka, Kenta Hongo, Ryo Maezono, Kazuhiko Maeda. Light Absorption Properties and Electronic Band Structures of Lead-Vanadium Oxyhalide Apatites Pb5(VO4)3X (X = F, Cl, Br, I). Chem. Asian J. 2020. 15. 4. 540-545
  • Tom Ichibha, Anouar Benali, Kenta Hongo, Ryo Maezono. Ti interstitial flows giving rutile TiO 2 reoxidation process enhancement in (001) surface. Physical Review Materials. 2019. 3. 125801-125801
  • Hideyuki Takagishi, Takashi Masuda, Tatsuya Shimoda, Ryo Maezono, Kenta Hongo. Method for the Calculation of the Hamakerconstants of Organic Materials by the Lifshitz Macroscopic Approach With DFT. The Journal of Physical ChemistryA. 2019. 123. 40. 8726-8733
  • Yuki Iwasa, Hiraku Ogino, Dongjoon Song, Verdad C. Agulto, Kohei Yamanoi, Toshihiko Shimizu, Jumpei Ueda, Kenta Hongo, Ryo Maezono, Setsuhisa Tanabe, Nobuhiko Sarukura. Synthesis, optical properties, and band structures of a series of layered mixed-anion compounds. Journal of Materials Science: Materials in Electronics. 2019. 30. 18. 16827-16832
MISC (19):
  • Gewinner Senderanto Sinaga, Keishu Utimula, Kousuke Nakano, Kenta Hongo, Ryo Maezono. First Principles Calculations of Superconducting Critical Temperature of ThCr$_2$Si$_2$-Type Structure. 2019
  • Keishu Utimula, Kousuke Nakano, Genki I. Prayogo, Kenta Hongo, Ryo Maezono. SHRY:a $\underline{\rm S}$uite for $\underline{\rm H}$igh-th$\underline{\rm r}$oughput generation of models with atomic substitutions implemented by p$\underline{\rm y}$thon. 2019
  • Kousuke Nakano, Ryo Maezono, Sandro Sorella. Speeding up the ab initio diffusion Monte Carlo by a smart lattice regularization. 2019
  • 本郷研太, 本郷研太, 池端久貴, 磯村哲, 前園涼, 吉田亮, 吉田亮, 吉田亮. ベイズ統計と第一原理計算を基盤とする新規物質構造探査. 日本セラミックス協会秋季シンポジウム講演予稿集(CD-ROM). 2016. 29th. ROMBUNNO.2H24
  • Kenta Hongo, Ryo Maezono. $Ab$ $initio$ evaluation of Hamaker constants. 2016
Lectures and oral presentations  (40):
  • Machine learning clustering technique applied to X-ray diffraction patterns to distinguish alloy substitutions
    (European Advanced Materials Congress, International Association of Advanced Materials (IAAM) 2019)
  • Machine learning clustering technique applied to X-ray diffraction patterns to distinguish alloy substitutions
    (XXXI IUPAP Conference on Computational Physics (CCP2019) 2019)
  • Machine learning clustering technique applied to X-ray diffraction patterns to distinguish alloy substitutions
    (23rd International Annual Symposium on Computational Science and Engineering (ANSCSE23) 2019)
  • Machine learning clustering technique applied to X-ray diffraction patterns to distinguish alloy substitutions
    (WOS AOARD/seminar on Computational Materials Science 2019)
  • Machine Learning Clustering Technique Applied to X-Ray Diffraction Patterns to Distinguish Alloy Substitutions
    (2018 MRS Fall Meeting and Exhibit 2018)
Education (2):
  • 1992 - 1995 University of Tokyo Faculty of Engineering Department of Applied Physics
  • 1987 - 1992 Numazu Collage of Technology Department of Electronics and Control
Professional career (1):
  • Ph.D (Tokyo Univ./2000)
Work history (6):
  • 2017/10 - 現在 Japan Advanced Institute of Science and Technology Professor
  • 2011/04 - 2017/09 Japan Advanced Institute of Science and Technology Associate Professor
  • 2007/03 - 2011/03 Japan Advanced Institute of Science and Technology Lecturer
  • 2001/04 - 2007/02 National Institute for Materials Science Researcher(tenure)
  • 2001/01 - 2002/12 University of Cambridge EPSRC PosdocFellow
Show all
Association Membership(s) (5):
American Chemical Society ,  American Physical Society ,  The Ceramic Society of Japan ,  The Japan Society of Applied Physics ,  THE CHEMICAL SOCIETY OF JAPAN
※ Researcher’s information displayed in J-GLOBAL is based on the information registered in researchmap. For details, see here.

Return to Previous Page