Itsuki Miyazato

Hokkaido University — Japan

Materials Science · Physical Sciences

15h-index915citations29works0.02yr avg
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Research Topics

Machine Learning in Materials Science(20), Catalysis and Oxidation Reactions(16), Catalytic Processes in Materials Science(12), 2D Materials and Applications(5), Graphene research and applications(4)

Publications29 total

Designing transformer oil immersion cooling servers for machine learning and first principle calculations
PLoS ONE·2022· 3 citedOpen Access
Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane via Manganese Promoter
Industrial & Engineering Chemistry Research·2022· 8 cited
High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La<sub>2</sub>O<sub>3</sub>-based catalysts for the oxidative coupling of methane
Catalysis Science & Technology·2022· 16 cited
Designing two-dimensional dodecagonal boron nitride
CrystEngComm·2021· 11 cited
Catalysis Gene Expression Profiling: Sequencing and Designing Catalysts
The Journal of Physical Chemistry Letters·2021· 11 cited
Unveiling gas‐phase oxidative coupling of methane via data analysis
Journal of Computational Chemistry·2021· 7 cited
Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
Scientific Reports·2021· 23 citedOpen Access
Representing Catalytic and Processing Space in Methane Oxidation Reaction via Multioutput Machine Learning
The Journal of Physical Chemistry Letters·2021· 13 cited
Materials Informatics : Summary and Examples
MEMBRANE·2021
Catalytic direct oxidation of methane to methanol by redox of copper mordenite
Catalysis Science & Technology·2021· 30 cited
Direct Design of Catalysts in Oxidative Coupling of Methane via High‐Throughput Experiment and Deep Learning
ChemCatChem·2020· 21 cited
Direct design of active catalysts for low temperature oxidative coupling of methane <i>via</i> machine learning and data mining
Catalysis Science & Technology·2020· 30 cited
Rising Sun Envelope Method: An Automatic and Accurate Peak Location Technique for XANES Measurements
The Journal of Physical Chemistry A·2020· 3 citedOpen Access
Data-Driven Identification of the Reaction Network in Oxidative Coupling of the Methane Reaction via Experimental Data
The Journal of Physical Chemistry Letters·2020· 22 cited
Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
Reaction Chemistry & Engineering·2020· 47 cited
Transition of wide-band gap semiconductor h-BN(BN)/P heterostructure <i>via</i> single-atom-embedding
Journal of Materials Chemistry C·2020· 10 cited
High-Throughput Experimentation and Catalyst Informatics for Oxidative Coupling of Methane
ACS Catalysis·2019· 174 cited
Controlling electronic structure of single-layered $${\hbox {HfX}}_{3}$$ ($$\hbox {X=S}$$, Se) trichalcogenides through systematic Zr doping
Journal of Materials Science·2019· 15 cited
Automatic oxidation threshold recognition of XAFS data using supervised machine learning
Molecular Systems Design & Engineering·2019· 33 cited
The Rise of Catalyst Informatics: Towards Catalyst Genomics
ChemCatChem·2018· 101 cited
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Frequent Co-authors

Keisuke Takahashi(29), Lauren Takahashi(12), Shun Nishimura(11), Junya Ohyama(10), Toshiaki Taniike(8), Thanh Nhat Nguyen(6), Jun Fujima(6), Yuzuru Tanaka(4), Hiroshi Yoshida(3), Masato Machida(3), Takeaki Uno(2), Kenji Hirai(2), Airi Hirayama(2), Nahoko Kondou(2), Sunao Nakanowatari(2), Fatih Ersan(2), Satoshi Maeda(2), Thuy Tran Phuong Nhat(1), Ken Takimoto(1), Ashutosh Thakur(1)