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Itsuki Miyazato
Itsuki Miyazato
Verified email at sci.hokudai.ac.jp - Homepage
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Cited by
Year
High-throughput experimentation and catalyst informatics for oxidative coupling of methane
TN Nguyen, TTP Nhat, K Takimoto, A Thakur, S Nishimura, J Ohyama, ...
Acs Catalysis 10 (2), 921-932, 2019
1262019
The rise of catalyst informatics: towards catalyst genomics
K Takahashi, L Takahashi, I Miyazato, J Fujima, Y Tanaka, T Uno, ...
ChemCatChem 11 (4), 1146-1152, 2019
832019
Searching for hidden perovskite materials for photovoltaic systems by combining data science and first principle calculations
K Takahashi, L Takahashi, I Miyazato, Y Tanaka
ACS Photonics 5 (3), 771-775, 2018
792018
Unveiling hidden catalysts for the oxidative coupling of methane based on combining machine learning with literature data
K Takahashi, I Miyazato, S Nishimura, J Ohyama
ChemCatChem 10 (15), 3223-3228, 2018
732018
Rapid estimation of activation energy in heterogeneous catalytic reactions via machine learning
K Takahashi, I Miyazato
Journal of computational chemistry 39 (28), 2405-2408, 2018
542018
Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
J Fujima, Y Tanaka, I Miyazato, L Takahashi, K Takahashi
Reaction Chemistry & Engineering 5 (5), 903-911, 2020
302020
Accelerating the discovery of hidden two-dimensional magnets using machine learning and first principle calculations
I Miyazato, Y Tanaka, K Takahashi
Journal of Physics: Condensed Matter 30 (6), 06LT01, 2018
302018
Automatic oxidation threshold recognition of XAFS data using supervised machine learning
I Miyazato, L Takahashi, K Takahashi
Molecular Systems Design & Engineering 4 (5), 1014-1018, 2019
282019
Data-driven identification of the reaction network in oxidative coupling of the methane reaction via experimental data
I Miyazato, S Nishimura, L Takahashi, J Ohyama, K Takahashi
The journal of physical chemistry letters 11 (3), 787-795, 2020
232020
Redesigning the materials and catalysts database construction process using ontologies
L Takahashi, I Miyazato, K Takahashi
Journal of chemical information and modeling 58 (9), 1742-1754, 2018
222018
Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
J Ohyama, A Hirayama, N Kondou, H Yoshida, M Machida, S Nishimura, ...
Scientific Reports 11 (1), 2067, 2021
212021
Direct design of active catalysts for low temperature oxidative coupling of methane via machine learning and data mining
J Ohyama, T Kinoshita, E Funada, H Yoshida, M Machida, S Nishimura, ...
Catalysis Science & Technology 11 (2), 524-530, 2021
202021
Catalytic direct oxidation of methane to methanol by redox of copper mordenite
J Ohyama, A Hirayama, Y Tsuchimura, N Kondou, H Yoshida, M Machida, ...
Catalysis Science & Technology 11 (10), 3437-3446, 2021
162021
Direct Design of Catalysts in Oxidative Coupling of Methane via High‐Throughput Experiment and Deep Learning
K Sugiyama, TN Nguyen, S Nakanowatari, I Miyazato, T Taniike, ...
ChemCatChem 13 (3), 952-957, 2021
152021
Controlling electronic structure of single-layered (, Se) trichalcogenides through systematic Zr doping
I Miyazato, S Sarikurt, K Takahashi, F Ersan
Journal of Materials Science 55, 660-669, 2020
132020
Catalysis gene expression profiling: sequencing and designing catalysts
K Takahashi, J Fujima, I Miyazato, S Nakanowatari, A Fujiwara, ...
The Journal of Physical Chemistry Letters 12 (30), 7335-7341, 2021
122021
Representing catalytic and processing space in methane oxidation reaction via multioutput machine learning
I Miyazato, TN Nguyen, L Takahashi, T Taniike, K Takahashi
The Journal of Physical Chemistry Letters 12 (2), 808-814, 2021
102021
High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La 2 O 3-based catalysts for the oxidative coupling of methane
S Nishimura, SD Le, I Miyazato, J Fujima, T Taniike, J Ohyama, ...
Catalysis Science & Technology 12 (9), 2766-2774, 2022
82022
Designing two-dimensional dodecagonal boron nitride
H Suzuki, I Miyazato, T Hussain, F Ersan, S Maeda, K Takahashi
CrystEngComm 24 (3), 471-474, 2022
72022
Transition of wide-band gap semiconductor h-BN (BN)/P heterostructure via single-atom-embedding
I Miyazato, T Hussain, K Takahashi
Journal of Materials Chemistry C 8 (28), 9755-9762, 2020
72020
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