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 26-50 of 151 citing articles:

Machine learning in experimental materials chemistry
Balaranjan Selvaratnam, Ranjit T. Koodali
Catalysis Today (2020) Vol. 371, pp. 77-84
Open Access | Times Cited: 52

Analysis of Updated Literature Data up to 2019 on the Oxidative Coupling of Methane Using an Extrapolative Machine‐Learning Method to Identify Novel Catalysts
Shinya Mine, Motoshi Takao, Taichi Yamaguchi, et al.
ChemCatChem (2021) Vol. 13, Iss. 16, pp. 3636-3655
Open Access | Times Cited: 48

Learning Catalyst Design Based on Bias-Free Data Set for Oxidative Coupling of Methane
Thanh Nhat Nguyen, Sunao Nakanowatari, Thuy Phuong Nhat Tran, et al.
ACS Catalysis (2021) Vol. 11, Iss. 3, pp. 1797-1809
Closed Access | Times Cited: 44

Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters
Chonghyo Joo, Hyundo Park, Jongkoo Lim, et al.
International Journal of Intelligent Systems (2021) Vol. 37, Iss. 6, pp. 3625-3653
Open Access | Times Cited: 42

New paradigms for exploiting parallel experiments in Bayesian optimization
Leonardo D. González, Ví­ctor M. Zavala
Computers & Chemical Engineering (2022) Vol. 170, pp. 108110-108110
Open Access | Times Cited: 31

Identifying Descriptors for Promoted Rhodium-Based Catalysts for Higher Alcohol Synthesis via Machine Learning
Manu Suvarna, Phil Preikschas, Javier Pérez‐Ramírez
ACS Catalysis (2022) Vol. 12, Iss. 24, pp. 15373-15385
Open Access | Times Cited: 29

Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
Sora Ishioka, Aya Fujiwara, Sunao Nakanowatari, et al.
ACS Catalysis (2022) Vol. 12, Iss. 19, pp. 11541-11546
Closed Access | Times Cited: 28

Complimentary Computational Cues for Water Electrocatalysis: A DFT and ML Perspective
Ahmed Badreldin, O. Bouhali, Ahmed Abdel‐Wahab
Advanced Functional Materials (2023) Vol. 34, Iss. 12
Closed Access | Times Cited: 19

Active learning streamlines development of high performance catalysts for higher alcohol synthesis
Manu Suvarna, Tangsheng Zou, Sok Ho Chong, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7

Synthesis and molecular structure of model silica-supported tungsten oxide catalysts for oxidative coupling of methane (OCM)
Daniyal Kiani, Sagar Sourav, Israel E. Wachs, et al.
Catalysis Science & Technology (2020) Vol. 10, Iss. 10, pp. 3334-3345
Closed Access | Times Cited: 44

Materials Informatics for 2D Materials Combined with Sparse Modeling and Chemical Perspective: Toward Small-Data-Driven Chemistry and Materials Science
Yuya Oaki, Yasuhiko Igarashi
Bulletin of the Chemical Society of Japan (2021) Vol. 94, Iss. 10, pp. 2410-2422
Closed Access | Times Cited: 40

Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective
Annette Trunschke
Catalysis Science & Technology (2022) Vol. 12, Iss. 11, pp. 3650-3669
Open Access | Times Cited: 27

Toward the Golden Age of Materials Informatics: Perspective and Opportunities
Keisuke Takahashi, Lauren Takahashi
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 20, pp. 4726-4733
Closed Access | Times Cited: 15

Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
Jun Fujima, Yuzuru Tanaka, Itsuki Miyazato, et al.
Reaction Chemistry & Engineering (2020) Vol. 5, Iss. 5, pp. 903-911
Closed Access | Times Cited: 36

Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation
Keisuke Takahashi, Lauren Takahashi, Son Dinh Le, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 34, pp. 15735-15744
Closed Access | Times Cited: 20

Autonomous high-throughput computations in catalysis
Stephan N. Steinmann, Angga Hermawan, Mohammed Bin Jassar, et al.
Chem Catalysis (2022) Vol. 2, Iss. 5, pp. 940-956
Open Access | Times Cited: 19

Role and dynamics of transition metal carbides in methane coupling
Seraphine B. X. Y. Zhang, Quentin Pessemesse, Lukas Lätsch, et al.
Chemical Science (2023) Vol. 14, Iss. 22, pp. 5899-5905
Open Access | Times Cited: 11

Hybrid Quantum Neural Network Model with Catalyst Experimental Validation: Application for the Dry Reforming of Methane
Jiwon Roh, Seunghyeon Oh, Donggyun Lee, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 10, pp. 4121-4131
Closed Access | Times Cited: 4

A quantitative investigation on pyrolysis behaviors of metal ion-exchanged coal macerals by interpretable machine learning algorithms
Qiuxiang Yao, Linyang Wang, Mingming Ma, et al.
Energy (2024) Vol. 300, pp. 131614-131614
Closed Access | Times Cited: 4

Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering
Aya Fujiwara, Sunao Nakanowatari, Yohei Cho, et al.
Science and Technology of Advanced Materials (2025) Vol. 26, Iss. 1
Open Access

Redox CeO2 substituted Na2WO4-Mn catalyst for high-throughput chemical looping oxidative coupling of methane
Xiaolin Zhu, Shizhe Liu, Yaqian Li, et al.
Applied Catalysis B Environment and Energy (2025), pp. 125108-125108
Closed Access

Enhancing Catalyst Performance Prediction with Hybrid Quantum Neural Networks: A Comparative Study on Data Consistency Variation
Seunghyeon Oh, Jiwon Roh, Hyundo Park, et al.
ACS Sustainable Chemistry & Engineering (2025)
Closed Access

High-Throughput Optimization of a High-Pressure Catalytic Reaction
Yusuke Tanabe, Hiroki Sugisawa, Tomohisa Miyazawa, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access

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