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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:

Benchmarking the acceleration of materials discovery by sequential learning
Brian A. Rohr, Helge S. Stein, Dan Guevarra, et al.
Chemical Science (2020) Vol. 11, Iss. 10, pp. 2696-2706
Open Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

Emerging materials intelligence ecosystems propelled by machine learning
Rohit Batra, Le Song, Rampi Ramprasad
Nature Reviews Materials (2020) Vol. 6, Iss. 8, pp. 655-678
Closed Access | Times Cited: 242
Pulsed Laser in Liquids Made Nanomaterials for Catalysis
Ryland C. Forsythe, Connor P. Cox, Madeleine K. Wilsey, et al.
Chemical Reviews (2021) Vol. 121, Iss. 13, pp. 7568-7637
Open Access | Times Cited: 158
Two-step machine learning enables optimized nanoparticle synthesis
Flore Mekki‐Berrada, Zekun Ren, Tan Huang, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 133
A data fusion approach to optimize compositional stability of halide perovskites
Shijing Sun, Armi Tiihonen, Felipe Oviedo, et al.
Matter (2021) Vol. 4, Iss. 4, pp. 1305-1322
Open Access | Times Cited: 122
Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains
Qiaohao Liang, Aldair E. Gongora, Zekun Ren, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 119
Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing
Zhe Liu, Nicholas Rolston, Austin C. Flick, et al.
Joule (2022) Vol. 6, Iss. 4, pp. 834-849
Open Access | Times Cited: 115
A self-driving laboratory advances the Pareto front for material properties
Benjamin P. MacLeod, Fraser G. L. Parlane, Connor C. Rupnow, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 113
Human- and machine-centred designs of molecules and materials for sustainability and decarbonization
Jiayu Peng, Daniel Schwalbe‐Koda, Karthik Akkiraju, et al.
Nature Reviews Materials (2022) Vol. 7, Iss. 12, pp. 991-1009
Closed Access | Times Cited: 84
Autonomous optimization of non-aqueous Li-ion battery electrolytes via robotic experimentation and machine learning coupling
Adarsh Dave, Jared Mitchell, Sven Burke, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 83
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
Kedar Hippalgaonkar, Qianxiao Li, Xiaonan Wang, et al.
Nature Reviews Materials (2023) Vol. 8, Iss. 4, pp. 241-260
Closed Access | Times Cited: 80
Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning
Jianwen Liu, Wenzhi Luo, Lei Wang, et al.
Advanced Functional Materials (2022) Vol. 32, Iss. 17
Closed Access | Times Cited: 71
Recent applications of machine learning in alloy design: A review
Mingwei Hu, Qiyang Tan, Ruth Knibbe, et al.
Materials Science and Engineering R Reports (2023) Vol. 155, pp. 100746-100746
Closed Access | Times Cited: 46
In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science
Joshua Schrier, Alexander J. Norquist, Tonio Buonassisi, et al.
Journal of the American Chemical Society (2023) Vol. 145, Iss. 40, pp. 21699-21716
Open Access | Times Cited: 39
Exploiting redundancy in large materials datasets for efficient machine learning with less data
Kangming Li, Daniel Persaud, Kamal Choudhary, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 38
Self-Driving Laboratories for Chemistry and Materials Science
Gary Tom, Stefan P. Schmid, Sterling G. Baird, et al.
Chemical Reviews (2024) Vol. 124, Iss. 16, pp. 9633-9732
Open Access | Times Cited: 19
Data‐Driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects
Shanling Ji, Jianxiong Zhu, Yaxin Yang, et al.
Small Methods (2024) Vol. 8, Iss. 7
Closed Access | Times Cited: 13
High‐Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research
Anass Benayad, Diddo Diddens, Andreas Heuer, et al.
Advanced Energy Materials (2021) Vol. 12, Iss. 17
Open Access | Times Cited: 86
Autonomous intelligent agents for accelerated materials discovery
Joseph H. Montoya, Kirsten T. Winther, Raul A. Flores, et al.
Chemical Science (2020) Vol. 11, Iss. 32, pp. 8517-8532
Open Access | Times Cited: 74
Machine learning and chemometrics for electrochemical sensors: moving forward to the future of analytical chemistry
Pumidech Puthongkham, Supacha Wirojsaengthong, Akkapol Suea‐Ngam
The Analyst (2021) Vol. 146, Iss. 21, pp. 6351-6364
Closed Access | Times Cited: 71
Olympus: a benchmarking framework for noisy optimization and experiment planning
Florian Häse, Matteo Aldeghi, Riley J. Hickman, et al.
Machine Learning Science and Technology (2021) Vol. 2, Iss. 3, pp. 035021-035021
Open Access | Times Cited: 70
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
Yunchao Xie, Kianoosh Sattari, Chi Zhang, et al.
Progress in Materials Science (2022) Vol. 132, pp. 101043-101043
Open Access | Times Cited: 53
Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration
Fuzhan Rahmanian, Jackson Flowers, Dan Guevarra, et al.
Advanced Materials Interfaces (2022) Vol. 9, Iss. 8
Open Access | Times Cited: 49
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: 40
From materials discovery to system optimization by integrating combinatorial electrochemistry and data science
Helge S. Stein, Alexey O. Sanin, Fuzhan Rahmanian, et al.
Current Opinion in Electrochemistry (2022) Vol. 35, pp. 101053-101053
Closed Access | Times Cited: 36
Toward autonomous materials research: Recent progress and future challenges
Joseph H. Montoya, Muratahan Aykol, Abraham Anapolsky, et al.
Applied Physics Reviews (2022) Vol. 9, Iss. 1
Closed Access | Times Cited: 35
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