Takuya Taniguchi

Waseda University

Japan

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Articles (12)

Year:

2025

Year:

2025

Machine learning on perovskite photovoltaics reveals the relative importance of material and process information, while data degeneracy limits prediction accuracy.

Year:

2024

Year:

2024

Year:

2024

Year:

2024

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2023

Year:

2023

Year:

2023

Year:

2022

Year:

2021

Year:

2020

Collaborators (4)

Takuya Kurihara

Kanazawa University

JAPAN

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Shun Dekura

Assistant Professor

Tohoku University

JAPAN

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Motohiro Mizuno

Kanazawa University

JAPAN

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Masahiro Kuramochi

Ibaraki University

JAPAN

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Takuya Taniguchi

Research Interests

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Articles (12)

Knowledge distillation of neural network potential for molecular crystals

Machine learning-driven optimization of the output force in photo-actuated organic crystals

Effectiveness and limitation of the performance prediction of perovskite solar cells by process informatics

Proton Conduction in Chiral Molecular Assemblies of Azolium–Camphorsulfonate Salts

Effectiveness and limitation of the performance prediction of perovskite solar cells by process informatics

Exploration of elastic moduli of molecular crystals via database screening by pretrained neural network potential

Unraveling the Structural and Property Differences between Highly Similar Chiral and Racemic Crystals Composed of Analogous Molecules

Molecular screening for solid–solid phase transitions by machine learning

Graph Comparison of Molecular Crystals in Band Gap Prediction Using Neural Networks

Superelasticity of a photo-actuating chiral salicylideneamine crystal

Actuation performance of a photo-bending crystal modeled by machine learning-based regression

Crystal actuator based on a thermal phase transition and photothermal effect

Collaborators (4)

Takuya Kurihara

Shun Dekura

Motohiro Mizuno

Masahiro Kuramochi

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