Keisuke Takahashi

Hokkaido University

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Research Interests

Materials Chemistry

Petrochemical Engineering

Mechanistic Chemistry

Computational Science

Chemical Engineering

Solid State Physics

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Recent Grants

Grant: Close

実験・計算・データ科学の統合によるメタン変換触媒の探索・発見と反応機構の解明・制御

Open Date: 2017-04-01

Close Date: 2022-03-31

Articles18

Collaborators3

Lauren Takahashi

Assistant Professor

Hokkaido University

Masato Machida

Hiroshi Yoshida

Kanazawa University

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Keisuke Takahashi

Professor

How do I reach out?

Contact this professor

Research Interests

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Recent Grants

Articles18

Development of graphical user interface for design of experiments via Gaussian process regression and its case study

MonteCat: A Basin-Hopping-Inspired Catalyst Descriptor Search Algorithm for Machine Learning Models

Theoretical Investigation of Cyanographene and Cyanographite for Potential Sodium Ion Battery

Automatic feature engineering for catalyst design using small data without prior knowledge of target catalysis

High-throughput calculation for screening of Formamidinium Halide Perovskite for Solar Cells

High-throughput calculation for the screening of formamidinium halide perovskite for solar cells

Unveiling the relation between multiple chemical products and process conditions for trichloroethylene and perchloroethylene production via catalysis network analysis

Unveiling the relation between multiple chemical products and process conditions for trichloroethylene and perchloroethylene production <i>via</i> catalysis network analysis

Investigation of the Active-Site Structure of Cu-CHA Catalysts for the Direct Oxidation of Methane to Methanol Using In Situ UV–Vis Spectroscopy

Water Purification by 2‐Dimensional Dodecagonal Nitride and Graphenylene via First Principles Calculations

Toward the Golden Age of Materials Informatics: Perspective and Opportunities

Data-Driven Design and Understanding of Noble Metal-Based Water–Gas Shift Catalysts from Literature Data

The value of negative results in data-driven catalysis research

Catalysts informatics: paradigm shift towards data-driven catalyst design

Improving scientific image processing accessibility through development of graphical user interfaces for scikit-image

Indirect design of OCM catalysts through machine learning of catalyst surface oxygen species

Leveraging machine learning engineering to uncover insights into heterogeneous catalyst design for oxidative coupling of methane

Searching chemical action and network (SCAN): an interactive chemical reaction path network platform

Collaborators3

Lauren Takahashi

Masato Machida

Hiroshi Yoshida

How do I reach out?