Keisuke Takahashi
Cited by
Cited by
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
Materials informatics: a journey towards material design and synthesis
K Takahashi, Y Tanaka
Dalton Transactions 45 (26), 10497-10499, 2016
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
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
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
Material synthesis and design from first principle calculations and machine learning
K Takahashi, Y Tanaka
Computational materials science 112, 364-367, 2016
Graphene decorated with Fe nanoclusters for improving the hydrogen sorption kinetics of MgH 2–experimental and theoretical evidence
MSL Hudson, K Takahashi, A Ramesh, S Awasthi, AK Ghosh, ...
Catalysis Science & Technology 6 (1), 261-268, 2016
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
Data driven determination of reaction conditions in oxidative coupling of methane via machine learning
J Ohyama, S Nishimura, K Takahashi
ChemCatChem 11 (17), 4307-4313, 2019
Creating machine learning-driven material recipes based on crystal structure
K Takahashi, L Takahashi
The journal of physical chemistry letters 10 (2), 283-288, 2019
Reversible Hydrogen Uptake by BN and BC3 Monolayers Functionalized with Small Fe Clusters: A Route to Effective Energy Storage
T Hussain, DJ Searles, K Takahashi
The Journal of Physical Chemistry A 120 (12), 2009-2013, 2016
Low temperature pollutant trapping and dissociation over two-dimensional tin
L Takahashi, K Takahashi
Physical Chemistry Chemical Physics 17 (33), 21394-21396, 2015
Learning catalyst design based on bias-free data set for oxidative coupling of methane
TN Nguyen, S Nakanowatari, TP Nhat Tran, A Thakur, L Takahashi, ...
ACS Catalysis 11 (3), 1797-1809, 2021
The catalytic effect of Nb, NbO and Nb2O5 with different surface planes on dehydrogenation in MgH2: Density functional theory study
K Takahashi, S Isobe, S Ohnuki
Journal of alloys and compounds 580, S25-S28, 2013
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
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
Revealing the multibonding state between hydrogen and graphene-supported Ti clusters
K Takahashi, S Isobe, K Omori, T Mashoff, D Convertino, V Miseikis, ...
The Journal of Physical Chemistry C 120 (24), 12974-12979, 2016
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
Aryl fluoride functionalized graphene oxides for excellent room temperature ammonia sensitivity/selectivity
F Khurshid, M Jeyavelan, K Takahashi, MSL Hudson, S Nagarajan
RSC advances 8 (36), 20440-20449, 2018
Chemisorption of hydrogen on Fe clusters through hybrid bonding mechanisms
K Takahashi, S Isobe, S Ohnuki
Applied Physics Letters 102 (11), 2013
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