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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

High-Throughput Experimentation and Catalyst Informatics for Oxidative Coupling of Methane
Thanh Nhat Nguyen, Thuy Tran Phuong Nhat, Ken Takimoto, et al.
ACS Catalysis (2019) Vol. 10, Iss. 2, pp. 921-932
Closed Access | Times Cited: 151

Showing 1-25 of 151 citing articles:

Bridging the complexity gap in computational heterogeneous catalysis with machine learning
Tianyou Mou, Hemanth Somarajan Pillai, Siwen Wang, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 122-136
Closed Access | Times Cited: 134
Surface and Interface Coordination Chemistry Learned from Model Heterogeneous Metal Nanocatalysts: From Atomically Dispersed Catalysts to Atomically Precise Clusters
Wentong Jing, Hui Shen, Ruixuan Qin, et al.
Chemical Reviews (2022) Vol. 123, Iss. 9, pp. 5948-6002
Closed Access | Times Cited: 127
Thermochemical Conversion of Plastic Waste into Fuels, Chemicals, and Value‐Added Materials: A Critical Review and Outlooks
Ren‐Xuan Yang, Kalsoom Jan, Ching‐Tien Chen, et al.
ChemSusChem (2022) Vol. 15, Iss. 11
Open Access | Times Cited: 98
A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation
Manu Suvarna, Thaylan Pinheiro Araújo, Javier Pérez‐Ramírez
Applied Catalysis B Environment and Energy (2022) Vol. 315, pp. 121530-121530
Open Access | Times Cited: 93
Machine Learning Descriptors for Data‐Driven Catalysis Study
Li‐Hui Mou, TianTian Han, Pieter E. S. Smith, et al.
Advanced Science (2023) Vol. 10, Iss. 22
Open Access | Times Cited: 47
Embracing data science in catalysis research
Manu Suvarna, Javier Pérez‐Ramírez
Nature Catalysis (2024) Vol. 7, Iss. 6, pp. 624-635
Closed Access | Times Cited: 27
Recent developments and current trends on catalytic dry reforming of Methane: Hydrogen Production, thermodynamics analysis, techno feasibility, and machine learning
Mohammed Mosaad Awad, Esraa Kotob, Omer Ahmed Taialla, et al.
Energy Conversion and Management (2024) Vol. 304, pp. 118252-118252
Closed Access | Times Cited: 24
Atomic Design of Alkyne Semihydrogenation Catalysts via Active Learning
Xiaohu Ge, Jun Yin, Zhouhong Ren, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 7, pp. 4993-5004
Closed Access | Times Cited: 23
From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design
Jorge Benavides-Hernández, Franck Dumeignil
ACS Catalysis (2024) Vol. 14, Iss. 15, pp. 11749-11779
Closed Access | Times Cited: 23
High-throughput experimentation meets artificial intelligence: a new pathway to catalyst discovery
Katherine B. McCullough, Travis Williams, Kathleen Mingle, et al.
Physical Chemistry Chemical Physics (2020) Vol. 22, Iss. 20, pp. 11174-11196
Closed Access | Times Cited: 125
Catalyst design and tuning for oxidative dehydrogenation of propane – A review
Yahya Gambo, Sagir Adamu, Abdulrahman A. Abdulrasheed, et al.
Applied Catalysis A General (2020) Vol. 609, pp. 117914-117914
Closed Access | Times Cited: 107
High Throughput Methods in the Synthesis, Characterization, and Optimization of Porous Materials
Ivan G. Clayson, Daniel Hewitt, Martin Hutereau, et al.
Advanced Materials (2020) Vol. 32, Iss. 44
Open Access | Times Cited: 81
Photocatalytic Conversion of Methane: Recent Advancements and Prospects
Qi Li, Yuxing Ouyang, Hongliang Li, et al.
Angewandte Chemie (2021) Vol. 134, Iss. 2
Closed Access | Times Cited: 68
Machine learning for design principles for single atom catalysts towards electrochemical reactions
Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, et al.
Journal of Materials Chemistry A (2022) Vol. 10, Iss. 29, pp. 15309-15331
Open Access | Times Cited: 68
Autonomous chemical science and engineering enabled by self-driving laboratories
Jeffrey A. Bennett, Milad Abolhasani
Current Opinion in Chemical Engineering (2022) Vol. 36, pp. 100831-100831
Open Access | Times Cited: 42
The value of negative results in data-driven catalysis research
Toshiaki Taniike, Keisuke Takahashi
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 108-111
Closed Access | Times Cited: 40
Oxidative Coupling of Methane: Examining the Inactivity of the MnOx‐Na2WO4/SiO2 Catalyst at Low Temperature
Jiaqi Si, Guofeng Zhao, Weidong Sun, et al.
Angewandte Chemie International Edition (2022) Vol. 61, Iss. 18
Closed Access | Times Cited: 39
Catalysts informatics: paradigm shift towards data-driven catalyst design
Keisuke Takahashi, Junya Ohyama, Shun Nishimura, et al.
Chemical Communications (2023) Vol. 59, Iss. 16, pp. 2222-2238
Open Access | Times Cited: 37
Addressing complexity in catalyst design: From volcanos and scaling to more sophisticated design strategies
Sarah M. Stratton, Shengjie Zhang, M. M. Montemore
Surface Science Reports (2023) Vol. 78, Iss. 3, pp. 100597-100597
Open Access | Times Cited: 31
Interpretable machine learning framework for catalyst performance prediction and validation with dry reforming of methane
Jiwon Roh, Hyundo Park, Hyukwon Kwon, et al.
Applied Catalysis B Environment and Energy (2023) Vol. 343, pp. 123454-123454
Open Access | Times Cited: 24
Impacts of catalyst and process parameters on Ni-catalyzed methane dry reforming via interpretable machine learning
Keerthana Vellayappan, Yifei Yue, Kang Hui Lim, et al.
Applied Catalysis B Environment and Energy (2023) Vol. 330, pp. 122593-122593
Closed Access | Times Cited: 23
Automatic feature engineering for catalyst design using small data without prior knowledge of target catalysis
Toshiaki Taniike, Aya Fujiwara, Sunao Nakanowatari, et al.
Communications Chemistry (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 15
Machine learning enabled exploration of multicomponent metal oxides for catalyzing oxygen reduction in alkaline media
Xue Jia, Hao Li
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 21, pp. 12487-12500
Open Access | Times Cited: 8
Innovative Catalysis Approaches for Methane Utilization
Jedy Prameswari, Yu‐Chuan Lin
ACS ES&T Engineering (2025)
Open Access | Times Cited: 1
Towards Experimental Handbooks in Catalysis
Annette Trunschke, Giulia Bellini, Maxime Boniface, et al.
Topics in Catalysis (2020) Vol. 63, Iss. 19-20, pp. 1683-1699
Open Access | Times Cited: 58
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