4) Kenya Tanaka, Taishi Nishihara, Akira Takakura, Yasutomo Segawa, Kazunari Matsuda, and Yuhei Miyauchi

Polarized Raman spectroscopy on topological semimetal Co3Sn2S2

submitted.(2022)

doi.org/

3) Wenjin Zhang, Kenya Tanaka, Yusuke Hasegawa, Keisuke Shinokita, Kazunari Matsuda and Yuhei Miyauchi

Bright and highly valley polarized trions in chemically doped monolayer MoS2

Applied Physics Express 13, 035002 (2020).

doi.org/10.35848/1882-0786/ab7485

2) Kenya Tanaka, Kengo Hachiya, Wenjin Zhang, Kazunari Matsuda and Yuhei Miyauchi

Machine-Learning Analysis to Predict the Exciton Valley Polarization Landscape of 2D Semiconductors

ACS Nano 13, 11, 12687-12693 (2019).

doi.org/10.1021/acsnano.9b04220

1) Fengjiu Yang, Jiewei Liu, Xiaofan Wang, Kenya Tanaka, Keisuke Shinokita, Yuhei Miyauchi, Atsushi Wakamiya, and Kazunari Matsuda

Planar Perovskite Solar Cells with High Efficiency and Fill Factor Obtained Using Two-Steps Growth Process

ACS Appl. Mater. Interfaces 11, 17, 15680-15687 (2019).

doi.org/10.1021/acsami.9b02948

[4] Machine Learning Analysis of Valley Exciton Physics in Monolayer WSe2

○Kenya Tanaka, Kengo Hachiya, Wenjin Zhang, Kazunari Matsuda and Yuhei Miyauchi

Institute of Advanced Energy, Kyoto University, Uji 611-0011, Japan,

The 8th International Workshop on 2D Materials, 29-30 June 2021, Online, China.

[3] Optical Simulation of Diffraction Characteristics of Eccentric Fresnel Lenses for a Compact Spectrometer

○Kenya Tanaka (1), Ryo Ohara (2), Takashi Fukuda (3), and Akira Emoto (4)

(1)Institute of Advanced Energy, Kyoto University

(2)Graduate School of Science and Engineering, Doshisha University

(3)Sensing System Research Center, National Institute of Advanced Industrial Science and Technology

(4)Institute of Post-LED Photonics (pLED), Tokushima University

The 24th Microoptics Conference (MOC2019), 17-20 November 2019, Toyama, Japan.

[2] Prediction of low temperature valley polarization characteristics in 2D semiconductors using machine-learning approach

○Kenya Tanaka, Kengo Hachiya, Wenjin Zhang, Kazunari Matsuda and Yuhei Miyauchi

Institute of Advanced Energy, Kyoto University, Uji 611-0011, Japan,

NT19: International Conference on the Science and Application of Nanotubes and Low-Dimensional Materials , 21-26 July 2019, Würzburg, Germany

[1]Design and Fabrication of Eccentric Fresnel Lenses for a Compact Spectrometer Based on a Inline Optical Arrangement

○Kenya Tanaka (1), Tsuyoshi Aburatani (2), Takashi Fukuda (3), Akira Emoto (2)

1 : Institute of Advanced Energy, Kyoto University, Japan

2 : Department of Electrical Engineering, Doshisha University, Japan

3 : Electronics and Photonics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Japan

11th International Conference on Optics-photonics Design & Fabrication, Hiroshima, November 28 – 30, 2018

[6] Raman spectroscopy of Weyl semimetal Co₃Sn₂S₂

○Kenya Tanaka, Akira Takakura, Yasumoto Segawa, Taishi Nishihara, Kazunari Matsuda, Yuhei Miyauchi

Institute of Advanced Energy, Kyoto University, Japan
Institute for Molecular Science, Japan

The 61th Fullerenes-Nanotubes-Graphene General Symposium, 1P-23, 1-3 August 2021, Osaka(Online), Japan

[5]機械学習解析による二次元半導体の局所バレー分極決定要因の特定

○田中絢也, 八谷 健吾, Zhang Wenjin, 松田 一成, 宮内 雄平

Institute of Advanced Energy, Kyoto University, Japan

応用物理学会秋季学術講演会, 10p-Z29-9, Tokyo, 8-11 August, 2020

[4]空間不均一性を利用した二次元半導体バレー光物性の機械学習解析

○田中絢也, 八谷 健吾, Zhang Wenjin, 松田 一成, 宮内 雄平

Institute of Advanced Energy, Kyoto University, Japan

応用物理学会春期学術講演会, 13p-A401-8, Tokyo, 12-15 March, 2020

[3]機械学習による原子層バレー光物性の解析・予測手法の開拓

○田中絢也, Zhang Wenjin, 八谷 健吾, 松田 一成, 宮内 雄平

Institute of Advanced Energy, Kyoto University, Japan

応用物理学会秋季学術講演会 , 21p-E201-3, Sapporo, 18-21 August, 2019

[2] Machine-learning approach for predicting low temperature valley polarization landscapes in 2D semiconductors

○Kenya Tanaka, Kengo Hachiya, Wenjin Zhang, Kazunari Matsuda and Yuhei Miyauchi

Institute of Advanced Energy, Kyoto University, Uji 611-0011, Japan,

The 57th Fullerenes-Nanotubes-Graphene General Symposium, 3-5 August 2019, Nagoya, Japan.

[1]機械学習による原子層材料物性予測モデルの構築

○田中絢也, Zhang Wenjin, 八谷 健吾, 松田 一成, 宮内 雄平

Institute of Advanced Energy, Kyoto University, Japan

MATLAB EXPO 2019 JAPAN, Tokyo, 28 May, 2019