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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:

AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning
Amanda A. Volk, Robert W. Epps, Daniel T. Yonemoto, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 84

Showing 1-25 of 84 citing articles:

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali, et al.
Digital Discovery (2023) Vol. 2, Iss. 5, pp. 1233-1250
Open Access | Times Cited: 114
Self-driving laboratories to autonomously navigate the protein fitness landscape
Jacob Rapp, Bennett J. Bremer, Philip A. Romero
Nature Chemical Engineering (2024) Vol. 1, Iss. 1, pp. 97-107
Open Access | Times Cited: 59
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back
Brent A. Koscher, Richard B. Canty, Matthew A. McDonald, et al.
Science (2023) Vol. 382, Iss. 6677
Open Access | Times Cited: 51
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: 46
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: 33
Machine intelligence-accelerated discovery of all-natural plastic substitutes
Tianle Chen, Zhenqian Pang, Shuaiming He, et al.
Nature Nanotechnology (2024) Vol. 19, Iss. 6, pp. 782-791
Open Access | Times Cited: 30
Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures
Vera Kuznetsova, Áine Coogan, Dmitry Botov, et al.
Advanced Materials (2024) Vol. 36, Iss. 18
Open Access | Times Cited: 22
Preventing cation intermixing enables 50% quantum yield in sub-15 nm short-wave infrared-emitting rare-earth based core-shell nanocrystals
Fernando Arteaga-Cardona, Noopur Jain, Radian Popescu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 22
Performance metrics to unleash the power of self-driving labs in chemistry and materials science
Amanda A. Volk, Milad Abolhasani
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Machine intelligence accelerated design of conductive MXene aerogels with programmable properties
Snehi Shrestha, Kieran Barvenik, Tianle Chen, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation
Sumner B. Harris, Arpan Biswas, Seok Joon Yun, et al.
Small Methods (2024) Vol. 8, Iss. 9
Open Access | Times Cited: 10
Roles of mechanistic, data-driven, and hybrid modeling approaches for pharmaceutical process design and operation
Mohamed Rami Gaddem, Junu Kim, Kensaku Matsunami, et al.
Current Opinion in Chemical Engineering (2024) Vol. 44, pp. 101019-101019
Closed Access | Times Cited: 8
3D printing and artificial intelligence tools for droplet microfluidics: Advances in the generation and analysis of emulsions
Sibilla Orsini, Marco Lauricella, Andrea Montessori, et al.
Applied Physics Reviews (2025) Vol. 12, Iss. 1
Closed Access | Times Cited: 1
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 18
Using Data-Driven Learning to Predict and Control the Outcomes of Inorganic Materials Synthesis
Emily M. Williamson, Richard L. Brutchey
Inorganic Chemistry (2023) Vol. 62, Iss. 40, pp. 16251-16262
Open Access | Times Cited: 17
Smart Dope: A Self‐Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots
Fazel Bateni, Sina Sadeghi, Negin Orouji, et al.
Advanced Energy Materials (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 17
Artificial Intelligence (AI) Workflow for Catalyst Design and Optimization
Nung Siong Lai, Yi Shen Tew, Xialin Zhong, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 43, pp. 17835-17848
Open Access | Times Cited: 16
Compositional design of multicomponent alloys using reinforcement learning
Yuehui Xian, Pengfei Dang, Yuan Tian, et al.
Acta Materialia (2024) Vol. 274, pp. 120017-120017
Open Access | Times Cited: 7
Opportunities for Machine Learning and Artificial Intelligence to Advance Synthetic Drug Substance Process Development
Daniel J. Griffin, Connor W. Coley, Scott A. Frank, et al.
Organic Process Research & Development (2023) Vol. 27, Iss. 11, pp. 1868-1879
Open Access | Times Cited: 15
Recent Developments in Reactor Automation for Multistep Chemical Synthesis
Adam D. Clayton
Chemistry - Methods (2023) Vol. 3, Iss. 12
Open Access | Times Cited: 14
Accelerating the Design of Multishell Upconverting Nanoparticles through Bayesian Optimization
Xiaojing Xia, Eric Sivonxay, Brett A. Helms, et al.
Nano Letters (2023) Vol. 23, Iss. 23, pp. 11129-11136
Closed Access | Times Cited: 13
Toward Microfluidic Continuous-flow and Intelligent Downstream Processing of Biopharmaceuticals
Vikas Sharma, Amirreza Mottafegh, Jeong‐Un Joo, et al.
Lab on a Chip (2024) Vol. 24, Iss. 11, pp. 2861-2882
Open Access | Times Cited: 5
Designing semiconductor materials and devices in the post-Moore era by tackling computational challenges with data-driven strategies
Jiahao Xie, Yansong Zhou, Muhammad Faizan, et al.
Nature Computational Science (2024) Vol. 4, Iss. 5, pp. 322-333
Closed Access | Times Cited: 5
Scientific Discovery Framework Accelerating Advanced Polymeric Materials Design
Ran Wang, Teng Fu, Yajie Yang, et al.
Research (2024) Vol. 7
Open Access | Times Cited: 5
Machine learning-guided strategies for reaction conditions design and optimization
Lung-Yi Chen, Yi‐Pei Li
Beilstein Journal of Organic Chemistry (2024) Vol. 20, pp. 2476-2492
Open Access | Times Cited: 5
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