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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:

Automation and machine learning augmented by large language models in a catalysis study
Yuming Su, Xue Wang, Yuanxiang Ye, et al.
Chemical Science (2024) Vol. 15, Iss. 31, pp. 12200-12233
Open Access | Times Cited: 13

Showing 13 citing articles:

Large language models for reticular chemistry
Zhiling Zheng, Nakul Rampal, Theo Jaffrelot Inizan, et al.
Nature Reviews Materials (2025)
Closed Access | Times Cited: 4
AI in single-atom catalysts: a review of design and applications
Qijun Yu, Ninggui Ma, Chihon Leung, et al.
Journal of Materials Informatics (2025) Vol. 5, Iss. 1
Open Access | Times Cited: 2
Recent developments in the use of machine learning in catalysis: A broad perspective with applications in kinetics
Leandro Goulart de Araujo, Léa Vilcocq, Pascal Fongarland, et al.
Chemical Engineering Journal (2025), pp. 160872-160872
Closed Access | Times Cited: 1
A New Era in Catalysis: Combining Al, DFT, Single Atom Catalysis, and Comprehensive Characterizations applied to Catalytic Oxidation of C1-C4 Volatile Organic Compounds
Suryamol Nambyaruveettil, Labeeb Ali, Mohammednoor Altarawneh
Journal of environmental chemical engineering (2025) Vol. 13, Iss. 1, pp. 115282-115282
Closed Access
Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts
Benjamin W. J. Chen, Manos Mavrikakis
Nature Chemical Engineering (2025)
Open Access
Interpretable physics-informed machine learning approaches to accelerate electrocatalyst development
Hao Wu, Mingxuan Chen, Hao Cheng, et al.
Journal of Materials Informatics (2025) Vol. 5, Iss. 2
Open Access
Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies
Justin P. Edaugal, Difan Zhang, Dupeng Liu, et al.
Chem & Bio Engineering (2025) Vol. 2, Iss. 4, pp. 210-228
Open Access
Leveraging Prompt Engineering in Large Language Models for Accelerating Chemical Research
Feifei Luo, Jinglang Zhang, Qilong Wang, et al.
ACS Central Science (2025) Vol. 11, Iss. 4, pp. 511-519
Open Access
Intelligent Systems for Inorganic Nanomaterial Synthesis
Cunhao Han, Xinghua Dong, Wang Zhang, et al.
Nanomaterials (2025) Vol. 15, Iss. 8, pp. 631-631
Open Access
Using machine learning to guide the synthesis of supported palladium catalysts with desired palladium dispersion
Kubra Tiras, Burcu Oral, Nazlinur Koparipek Arslan, et al.
Journal of Catalysis (2025), pp. 116176-116176
Closed Access
Application of graph neural network in computational heterogeneous catalysis
Zihao Jiao, Ya Liu, Ziyun Wang
The Journal of Chemical Physics (2024) Vol. 161, Iss. 17
Closed Access | Times Cited: 2
A Risk-based Model for Human-Artificial Intelligence Conflict Resolution in Process Systems
He Wen, Faisal Khan
Digital Chemical Engineering (2024) Vol. 13, pp. 100194-100194
Open Access | Times Cited: 1
A Well‐Advanced High‐Throughput Test System for Electrocatalytic Screening Applications Under Industrial Relevant Conditions – A Perspective to Accelerate Electrolysis Research and Development
Deniz Dogan, Burkhard Hecker, Xiaorong Hou, et al.
Electrochemical Science Advances (2024)
Open Access | Times Cited: 1
Engineering the Invisible
K Madhukumar, Manikala Vinod Kumar, Nivedita Kumar, et al.
Advances in chemical and materials engineering book series (2024), pp. 271-328
Closed Access
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