scholarly journals Front Cover: Unveiling Hidden Catalysts for the Oxidative Coupling of Methane based on Combining Machine Learning with Literature Data (ChemCatChem 15/2018)

ChemCatChem ◽  
2018 ◽  
Vol 10 (15) ◽  
pp. 3133-3133 ◽  
Author(s):  
Keisuke Takahashi ◽  
Itsuki Miyazato ◽  
Shun Nishimura ◽  
Junya Ohyama
Keyword(s):  
Machine Learning ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane ◽  
Front Cover

scholarly journals Unveiling Hidden Catalysts for the Oxidative Coupling of Methane based on Combining Machine Learning with Literature Data

ChemCatChem ◽  
2018 ◽  
Vol 10 (15) ◽  
pp. 3223-3228 ◽  
Author(s):  
Keisuke Takahashi ◽  
Itsuki Miyazato ◽  
Shun Nishimura ◽  
Junya Ohyama
Keyword(s):  
Machine Learning ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane

scholarly journals Front Cover: Intelligent Optimization of Na−Mn−W/SiO2 Catalysts for the Oxidative Coupling of Methane (ChemNanoMat 5/2018)

ChemNanoMat ◽  
2018 ◽  
Vol 4 (5) ◽  
pp. 430-430
Author(s):  
Zhinian Li ◽  
Shenliang Wang ◽  
Wei Hong ◽  
Shihui Zou ◽  
Liping Xiao ◽  
...  
Keyword(s):  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane ◽  
Front Cover ◽  
Intelligent Optimization

scholarly journals Revisiting Machine Learning Predictions for Oxidative Coupling of Methane (OCM) based on Literature Data

ChemCatChem ◽  
2020 ◽  
Vol 12 (23) ◽  
pp. 5888-5892
Author(s):  
Shun Nishimura ◽  
Junya Ohyama ◽  
Takaaki Kinoshita ◽  
Son Dinh Le ◽  
Keisuke Takahashi
Keyword(s):  
Machine Learning ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane

scholarly journals Unveiling Hidden Catalysts for the Oxidative Coupling of Methane based on Combining Machine Learning with Literature Data

ChemCatChem ◽  
2018 ◽  
Vol 10 (15) ◽  
pp. 3135-3135
Author(s):  
Keisuke Takahashi ◽  
Itsuki Miyazato ◽  
Shun Nishimura ◽  
Junya Ohyama
Keyword(s):  
Machine Learning ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane

Direct design of active catalysts for low temperature oxidative coupling of methane via machine learning and data mining

2021 ◽  
Author(s):  
Junya Ohyama ◽  
Takaaki Kinoshita ◽  
Eri Funada ◽  
Hiroshi Yoshida ◽  
Masato Machida ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Low Temperature ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane ◽  
Direct Design

Direct design of low temperature oxidative coupling of methane catalysts is proposed via machine learning and data mining.

Multidimensional Classification of Catalysts in Oxidative Coupling of Methane through Machine Learning and High-Throughput Data

2020 ◽  
Vol 11 (16) ◽  
pp. 6819-6826
Author(s):  
Keisuke Takahashi ◽  
Lauren Takahashi ◽  
Thanh Nhat Nguyen ◽  
Ashutosh Thakur ◽  
Toshiaki Taniike
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane ◽  
High Throughput Data

scholarly journals Cover Feature: Revisiting Machine Learning Predictions for Oxidative Coupling of Methane (OCM) based on Literature Data (ChemCatChem 23/2020)

ChemCatChem ◽  
2020 ◽  
Vol 12 (23) ◽  
pp. 5836-5836
Author(s):  
Shun Nishimura ◽  
Junya Ohyama ◽  
Takaaki Kinoshita ◽  
Son Dinh Le ◽  
Keisuke Takahashi
Keyword(s):  
Machine Learning ◽  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane

scholarly journals Identification of the structure of the Bi promoted Pt non-oxidative coupling of methane catalyst: a nanoscale Pt3Bi intermetallic alloy

2019 ◽  
Vol 9 (6) ◽  
pp. 1349-1356 ◽  
Author(s):  
Johnny Zhu Chen ◽  
Zhenwei Wu ◽  
Xiaoben Zhang ◽  
Slgi Choi ◽  
Yang Xiao ◽  
...  
Keyword(s):  
Oxidative Coupling ◽  
Oxidative Coupling Of Methane ◽  
Intermetallic Alloy ◽  
Alloy Catalyst

Identification of a Pt3Bi nanoscale, surface intermetallic alloy catalyst for non-oxidative coupling of methane (NOCM).

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