Papers citing Analysis of Updated Literature Data up to 2019 on the Oxidative Coupling of Methane Using an Extrapolative Machine‐Learning Method to Identify Novel Catalysts
A Data-Science Approach to Experimental Catalyst Discovery: Integrating Exploration, Exploitation, and Serendipity
ACS Catalysis · 2025
Sunao Nakanowatari, KEISUKE G. TAKAHASHI, Hieu‐Chi Dam, Toshiaki Taniike
Read original paper ↗ ·Catalyst Phylogenetic Tree: A Visualization Tool for Exploring Catalyst Research and Development from Tabular Data
The Journal of Physical Chemistry Letters · 2025
Sunao Nakanowatari, Toshiaki Taniike
Read original paper ↗ ·Infrared Spectra‐Based Machine Learning Framework for Photocatalytic Reaction and Performance
Advanced Intelligent Systems · 2025
Yanxia Wang, Yanjuan Sun, Hong Wang, Jing Li, Xinyan Liu, Fan Dong
Read original paper ↗ ·Artificial Intelligence‐assisted Heterogeneous Catalyst Design, Discovery, and Synthesis Utilizing Experimental Data
Venue not supplied by source · 2025
Rasika Jayarathna, Seyed Majid Ghoreishian, Rahat Javaid, Azadeh Mehrani, Thossaporn Onsree, Jochen A. Lauterbach
Read original paper ↗ ·Design and Operation of Copper-Based Heterogeneous Catalysts for CO2 Conversion to Methanol Using Extreme Gradient Boosting
ACS Applied Energy Materials · 2025
Sukanlaya Kornnum, Adisak Boonchun, Varisara Deerattrakul, Pawin Iamprasertkun
Read original paper ↗ ·Development of Highly Active Catalysts for Low-Temperature CO 2 Hydrogenation to Methanol Using a Machine Learning Approach
Journal of the American Chemical Society · 2025
Shirun Zhao, Shinya Mine, Gang Wang, Weiyang Zhang, Abdellah Ait El Fakir, Bin Yang, Zengwei Qin, Nazmul Hasan MD Dostagir, Koichi Matsushita, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Statistical and Predictive Analysis of Supported Catalytically Active Metal Solutions (SCALMS) in Propane Dehydrogenation
ChemCatChem · 2025
Angelika Owsienko, Philipp Stangl, Nnamdi Madubuko, Richard Lenz, Marco Haumann
Read original paper ↗ ·Extrapolative-Machine-Learning-Guided Discovery of Multielemental Heterogeneous Catalysts for Low-Temperature NO Reduction by H 2
ACS Catalysis · 2025
Yuan Jing, Chenyang Zhang, Shinya Mine, Xiupeng Zhang, Chenxi He, Ningqiang Zhang, Xu Ming Guo, Akihiko Anzai, Kohei Oka, Ryo Toyoshima, Hiroshi Kondoh, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Chemical looping oxidative coupling of methane
Elsevier eBooks · 2025
Sudeshna Gun, Falguni Akulwar, Xiaofeng Jiang, Tanay A. Jawdekar, Qichang Meng, Zhuo Cheng, Liang‐Shih Fan
Read original paper ↗ ·Accelerating Discovery of CO2 Reduction Catalysts through Machine Learning–Guided Experiments
Oleoscience · 2026
Shinya Mine
Read original paper ↗ ·Machine Learning-Guided Design of Catalysts with SO 2 Resistance for Low-Temperature NH 3 –SCR Reaction
Environmental Science & Technology · 2026
Huazhen Chang, Xinyi Miao, Haohui Chen, Lei Qiu, Guanglei Li, Chizhong Wang, Junhua Li, Bing Li, Lei Ma
Read original paper ↗ ·Thermo-Catalytic Carbon Dioxide Hydrogenation to Ethanol
Chemistry · 2026
Xianyu Meng, Ying Wang, Jie Li, Hongxing Wang, Chenglong Yu, Jia Guo, Zhuo Zhang, Qingli Qian, Buxing Han
Read original paper ↗ ·Machine-Learning-Guided Discovery and Statistical Analysis of Multielemental Reverse Water–Gas Shift Catalysts
ACS Catalysis · 2026
Duotian Chen, Shinya Mine, Guanghui Wang, Ichigaku Takigawa, Akihiko Anzai, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science
Journal of the Physical Society of Japan · 2026
Hieu‐Chi Dam, Hiori Kino, Takashi Miyake
Read original paper ↗ ·Co-production of ethylene and hydrogen via oxidative coupling of methane: Improving techno-economics and sustainability under emerging hydrogen markets
Resources Environment and Sustainability · 2026
Hegwon Chung, Thai Ngan Do, Yong Tae Kim, Jiyong Kim
Read original paper ↗ ·Machine-Learning-Guided Discovery of CH 4 Combustion Catalysts Operating in the Presence of SO 2
Journal of the American Chemical Society · 2026
Yuan Jing, Kah Wei Ting, Junxian Qin, Katsuya Yamada, Daichi Tajima, Akihiko Anzai, Shinya Mine, Ryo Toyoshima, Hiroshi Kondoh, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Potential, challenges and opportunities of machine learning model for plasma-based gas conversion: a critical review
ENGINEERING Chemical Engineering · 2026
Jiayin Li, Xinpei Lu, Sirui Li, Annemie Bogaerts
Read original paper ↗ ·Artificial Intelligence- and Machine Learning-Driven Strategies for Catalyst Design and Sustainable Chemical Processes
Processes · 2026
Amra Bratovčić, Vesna Tomašić
Read original paper ↗ ·Machine learning accelerated development of CuZn-Based catalysts for syngas to higher alcohols: Virtual screening and experimental validation
Journal of Fuel Chemistry and Technology · 2026
Yifan XU, Luxue Shen, Bing BAI, Qian Zhang, Hui BAI, Wei HUANG
Read original paper ↗ ·Machine Learning-Assisted Development of High-Performance Ethanol Synthesis Catalysts via CO2 Hydrogenation
Journal of the American Chemical Society · 2026
Pengfei Du, Abdellah Ait El Fakir, El Fakir, Shinya Mine, Bin Yang, Hongli Pan, Chenxi He, Nazmul Hasan, Yuriko Ando, Jörg W. A. Fischer, Akihiko Anzai, Giles Allison, Ryo Toyoshima, Hiroshi KONDOH, Wei Zhou, Christophe Copéret, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·A Review on the Application of Machine Learning in Nitrogen Reduction Reaction
ChemistrySelect · 2026
Baskaran Kannan, Saranya Chandrasekaran, Velu Sagadevan, Shankar Raman Dhanushkodi
Read original paper ↗ ·Explainable artificial intelligence shines a light on catalysis: methods, applications, and future directions
Academia Catalysis · 2026
Zixuan Geng, Di Wu, Xu Zhao, Chuqiao Hu, Peilun Qiu, Ce Fu, Jianqiao Liu
Read original paper ↗ ·Reaction-Depth Learning Enables Apparent Yield Extrapolation in Catalyst Informatics
The Journal of Physical Chemistry Letters · 2026
Jeonghan Song, Toshiaki Taniike
Read original paper ↗ ·Descriptor‐Based Zero‐Shot Learning for Predicting Catalytic Constituent Elements
ChemistrySelect · 2026
Jun Maki, Hiromasa Kaneko
Read original paper ↗ ·Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches
AIChE Journal · 2026
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre
Read original paper ↗ ·Engine exhaust waste heat recovery and utilization: synergistic optimization of Cu-based ternary catalysts for hydrogen-rich fuel production from green methanol cracking
Journal of Cleaner Production · 2026
Liangdong Zhao, Yankun Jiang, Chenyue Yang, Liangyu Zhao, Beidong Zhang
Read original paper ↗ ·