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Kei Terayama
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Theoretical and data-driven approaches to semiconductors and dielectrics: from prediction to experiment
Description/Abstract:
Computational approaches using theoretical calculations and data scientific methods have become increasingly important in materials scien...
Keyword:
dielectrics
and
semiconductors
Resource Type:
Article
Author:
Fumiyasu Oba
,
Takayuki Nagai
,
Ryoji Katsube
,
Yasuhide Mochizuki
,
Masatake Tsuji
,
Guillaume Deffrennes
,
Kota Hanzawa
,
Akitoshi Nakano
,
Akira Takahashi
,
Kei Terayama
,
Ryo Tamura
,
Hidenori Hiramatsu
,
Yoshitaro Nose
, and
Hiroki Taniguchi
Journal:
Science and Technology of Advanced Materials
Date Uploaded:
25/12/2024
Performance of uncertainty-based active learning for efficient approximation of black-box functions in materials science
Description/Abstract:
Obtaining a fine approximation of a black-box function is important for understanding and evaluating innovative materials. Active learnin...
Keyword:
active learning
,
black-box function
, and
materials informatics
Resource Type:
Article
Author:
Ai Koizumi
,
Guillaume Deffrennes
,
Kei Terayama
, and
Ryo Tamura
Journal:
Scientific Reports
Date Uploaded:
21/11/2024
Data-driven study of the enthalpy of mixing in the liquid phase
Description/Abstract:
The enthalpy of mixing in the liquid phase is a thermodynamic property reflecting interactions between elements that is key to predict ph...
Keyword:
enthalpy of mixing
,
liquid phase
, and
machine learning
Resource Type:
Article
Author:
Guillaume Deffrennes
,
Bengt Hallstedt
,
Taichi Abe
,
Quentin Bizot
,
Evelyne Fischer
,
Jean-Marc Joubert
,
Kei Terayama
, and
Ryo Tamura
Journal:
Calphad
Date Uploaded:
04/10/2024
AIPHAD, an active learning web application for visual understanding of phase diagrams
Description/Abstract:
Phase diagrams provide considerable information that is vital for materials exploration. However, the determination of multidimensional p...
Keyword:
active learning
,
artificial intelligence
, and
phase diagram
Resource Type:
Article
Author:
Ryo Tamura
,
Haruhiko Morito
,
Guillaume Deffrennes
,
Masanobu Naito
,
Yoshitaro Nose
,
Taichi Abe
, and
Kei Terayama
Journal:
Communications Materials
Date Uploaded:
26/08/2024
Target Material Property‐Dependent Cluster Analysis of Inorganic Compounds
Description/Abstract:
The cluster analysis of materials categorizes them according to similarities based on the features of materials, providing insight into t...
Keyword:
Cluster Analysis
and
Inorganic Compounds
Resource Type:
Article
Author:
Nobuya Sato
,
Akira Takahashi
,
Shin Kiyohara
,
Kei Terayama
,
Ryo Tamura
, and
Fumiyasu Oba
Journal:
Advanced Intelligent Systems
Date Uploaded:
19/08/2024
Ranking Pareto optimal solutions based on projection free energy
Description/Abstract:
Based on available datasets prepared by numerical simulations and machine learning, maps of properties for materials that have not yet be...
Keyword:
Pareto solutions
,
free energy
, and
semiconductor
Resource Type:
Article
Author:
Ryo Tamura
,
Kei Terayama
,
Masato Sumita
, and
Koji Tsuda
Journal:
Physical Review Materials
Date Uploaded:
04/10/2023
Date Modified:
04/10/2023
Topological alternation from structurally adaptable to mechanically stable crosslinked polymer
Description/Abstract:
Stimuli-responsive polymers with complicated but controllable shape-morphing behaviors are critically desirable in several engineering f...
Keyword:
Covalent adaptable network polymer
,
creep deformation
,
shape-morphing polymer material
, and
topological alternation
Resource Type:
Article
Author:
Wei-Hsun Hu
,
Ta-Te Chen
,
Ryo Tamura
,
Kei Terayama
,
Siqian Wang
,
Ikumu Watanabe
, and
Masanobu Naito
Date Uploaded:
02/03/2023
Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring
Description/Abstract:
AIを用いた機能性有機化合物の開発。
Keyword:
De novo molecule generation
,
characteristic functional group monitoring
,
chromophore
, and
deep learning
Resource Type:
Article
Author:
Takehiro Fujita
,
Kei Terayama
,
Masato Sumita
,
Ryo Tamura
,
Yasuyuki Nakamura
,
Masanobu Naito
, and
Koji Tsuda
Date Uploaded:
15/02/2023
Date Modified:
20/03/2024
CrySPY: a crystal structure prediction tool accelerated by machine learning
Description/Abstract:
We have developed an open-source software called CrySPY, which is a crystal structure prediction tool written in Python 3, ...
Keyword:
evolutionary algorithm
,
Bayesian optimization
,
LAQA
,
crystal structure prediction
, and
first-principles calculations
Resource Type:
Article
Author:
Tomoki Yamashita
,
Shinichi Kanehira
,
Nobuya Sato
,
Hiori Kino
,
Kei Terayama
,
Hikaru Sawahata
,
Takumi Sato
,
Futoshi Utsuno
,
Koji Tsuda
,
Takashi Miyake
, and
Tamio Oguchi
Date Uploaded:
10/02/2023
Date Modified:
02/04/2024
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9
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2
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2
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Kei Terayama
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1
Core Research for Evolutional Science and Technology
1
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1
Japan Science and Technology Corporation
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