Updated on 2026/06/18

写真a

 
IHARA MANABU
 
Organization
School of Materials and Chemical Technology Professor
Title
Professor
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News & Media

Degree

  • Doctor of Engineering ( The University of Tokyo )

Research Interests

  • Energy Science General

  • Chemical engineering in general

  • Energy conversion

  • 電気化学

  • 光デバイス

  • 無機化合物

  • エネルギー学一般

  • 化学工学一般

  • エネルギー変換

  • Electrochemistry

  • Optics devices

  • Inorganic compounds

Research Areas

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Transport phenomena and unit operations

  • Nanotechnology/Materials / Energy chemistry

  • Nanotechnology/Materials / Inorganic/coordination chemistry

Education

  • 東京大学 大学院   工学系研究科   化学工学専攻

    - 1994

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    Country: Japan

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  • The University of Tokyo   Graduate School, Division of Engineering

    - 1994

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  • Meiji University

    - 1989

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    Country: Japan

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Research History

  • 東京工業大学 エネルギー・情報卓越教育院 教育院長

    2020.12

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  • 東京工業大学 InfoSyEnergy研究/教育コンソーシアム 代表

    2019.11

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  • 東京工業大学 物質理工学院応用化学系 教授(改組)

    2016

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  • 中国 四川大学 客員教授(称号付与)

    2015

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Professional Memberships

Papers

  • Comparison of Voronoi Tessellation‐Derived and Molecular Dynamics‐Derived Atomistic Models of Polycrystalline Titania: A Computational Study of Structures, Band Structures, and Mechanical Properties

    Takuma Okamoto, Keisuke Kameda, Hao Wang, Manabu Ihara, Sergei Manzhos

    Advanced Theory and Simulations   9 ( 1 )   2025.9

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    Publishing type:Research paper (scientific journal)   Publisher:Wiley  

    Abstract

    Grain boundaries (GB) affect properties of polycrystalline ceramics, including mechanical and electronic properties. While often individual postulated GBs are considered in atomistic models, a distribution of GBs present in real ceramics should be accounted for. An often‐used method to build polycrystalline models is geometry‐based Voronoi tessellation. With it, random grain orientations generally obtain in atomistic models of GBs with non‐physically high Miller index grain surfaces. Recently, models of polycrystalline rutile TiO 2 were constructed with molecular dynamics (MD) using computational heat treatment, a procedurally nature‐like approach resulting in a distribution of GBs dominated by low‐index surfaces. It is important to understand the similarities and differences in GB‐affected properties with MD‐ and Voronoi tessellation‐based models for informed selection of an appropriate model for specific applications. Such a comparison is presented. Structural properties and the effect of grainy structures on mechanical properties and band structure are compared. High‐index surfaces prevalent in Voronoi structures lead to the formation of amorphous interlayers, and fracture stress is lower than with MD‐based structures. Band structures of GBs are analyzed in large‐scale electronic structure calculations. It is found that while low‐index surfaces do not result in trap states, high‐index surfaces and amorphous interlayers may introduce such states.

    DOI: 10.1002/adts.202501245

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    Other Link: https://advanced.onlinelibrary.wiley.com/doi/full-xml/10.1002/adts.202501245

  • A novel encoding method for high-dimensional categorical data for electricity demand forecasting in distributed energy systems

    HyoJae Lee, Keisuke Kameda, Sergei Manzhos, Manabu Ihara

    Applied Energy   392   125989 - 125989   2025.8

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    Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.apenergy.2025.125989

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  • Natural-like generation of grain boundary models and the combined effects of microstructural elements and lithiation on the plastic behavior of TiO2: A computational study

    Takuma Okamoto, Anastassia Sorkin, Keisuke Kameda, Manabu Ihara, Hao Wang, Sergei Manzhos

    Computational Materials Science   239   112989 - 112989   2024.4

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    Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.commatsci.2024.112989

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  • Machine learning of properties of lead-free perovskites with a neural network with additive kernel regression-based neuron activation functions

    Methawee Nukunudompanich, Heejoo Yoon, Lee Hyojae, Keisuke Kameda, Manabu Ihara, Sergei Manzhos

    MRS Advances   2024.1

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    Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    DOI: 10.1557/s43580-023-00749-1

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    Other Link: https://link.springer.com/article/10.1557/s43580-023-00749-1/fulltext.html

Research Projects

  • 設置角度に着目した農地共用型太陽光発電と、国内への導入ポテンシャルの算出

    Grant number:22K04999  2022.4 - 2025.3

    日本学術振興会  科学研究費助成事業  基盤研究(C)

    長谷川 馨, 伊原 学, MANZHOS SERGEI

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    Grant amount:\4160000 ( Direct Cost: \3200000 、 Indirect Cost:\960000 )

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  • エネルギービッグデータをコアとするカーボンニュートラルデジタルツイン

    Grant number:22713987  2022 - 2024

    科学技術振興機構  戦略的な研究開発の推進/未来社会創造事業/探索加速型

    伊原 学

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    東工大大岡山キャンパスに2011年に、竣工した「東工大環境エネルギーイノベーション棟」(研究代表者がエネルギーシステム設計及びプロジェクトリーダー)のエネルギーデータ、人流データ、及び、東工大大岡山キャンパス内の他研究棟の電力、太陽光発電データなど、クラウドデータベースにすでに10年分のデータが蓄積されている。この毎秒、もしく毎分、14000pt以上のエネルギーシステム-ビッグデータを基礎に、カーボンニュートラルシステムとして提案する“系統協調/分散型エネルギーシステム”を開発する。さらに、そのシステム開発の観点から必要となる要素技術開発(エネルギーデバイス/エネルギーマテリアル)および、シナリオ研究を、集約したデータや手法を共通化し、連動させることでカーボンニュートラル研究を飛躍的に加速させる「エネルギービッグデータをコアとするカーボンニュートラルデジタルツイン」を構築する。

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  • 低コスト高効率半導体薄膜太陽電池の開発

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    Grant type:Competitive

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  • Development of high efficient dye sensitized solar cells

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    Grant type:Competitive

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  • Studies of solid oxide fuel cells

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    Grant type:Competitive

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  • Development of low cost high efficient semiconductor solar cells

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    Grant type:Competitive

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  • 色素増感太陽電池に関する研究

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    Grant type:Competitive

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  • 半導体薄膜太陽電池に関する研究

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    Grant type:Competitive

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  • 色素増感太陽電池の高効率化に関する研究

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    Grant type:Competitive

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  • 固体酸化物燃料電池に関する研究

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    Grant type:Competitive

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