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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:

An Autonomous Self-Optimizing Flow Reactor for the Synthesis of Natural Product Carpanone
Daniel Cortés‐Borda, Eric Wimmer, Boris Gouilleux, et al.
The Journal of Organic Chemistry (2018) Vol. 83, Iss. 23, pp. 14286-14299
Open Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

Data-science driven autonomous process optimization
Melodie Christensen, Lars P. E. Yunker, Folarin Adedeji, et al.
Communications Chemistry (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 175
Autonomous Discovery in the Chemical Sciences Part I: Progress
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Angewandte Chemie International Edition (2019) Vol. 59, Iss. 51, pp. 22858-22893
Open Access | Times Cited: 175
Bayesian Optimization of Computer-Proposed Multistep Synthetic Routes on an Automated Robotic Flow Platform
Anirudh M. K. Nambiar, C. Breen, Travis Hart, et al.
ACS Central Science (2022) Vol. 8, Iss. 6, pp. 825-836
Open Access | Times Cited: 118
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
Florian Häse, Matteo Aldeghi, Riley J. Hickman, et al.
Applied Physics Reviews (2021) Vol. 8, Iss. 3
Open Access | Times Cited: 104
Accelerated Chemical Reaction Optimization Using Multi-Task Learning
Connor J. Taylor, Kobi Felton, Daniel Wigh, et al.
ACS Central Science (2023) Vol. 9, Iss. 5, pp. 957-968
Open Access | Times Cited: 65
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: 35
Automated self-optimisation of multi-step reaction and separation processes using machine learning
Adam D. Clayton, Artur M. Schweidtmann, Graeme Clemens, et al.
Chemical Engineering Journal (2019) Vol. 384, pp. 123340-123340
Open Access | Times Cited: 134
Automated platforms for reaction self-optimization in flow
Carlos Mateos, María José Nieves‐Remacha, Juan A. Rincón
Reaction Chemistry & Engineering (2019) Vol. 4, Iss. 9, pp. 1536-1544
Closed Access | Times Cited: 133
Algorithms for the self-optimisation of chemical reactions
Adam D. Clayton, Jamie A. Manson, Connor J. Taylor, et al.
Reaction Chemistry & Engineering (2019) Vol. 4, Iss. 9, pp. 1545-1554
Open Access | Times Cited: 133
Progress in low-field benchtop NMR spectroscopy in chemical and biochemical analysis
Martin Grootveld, Benita Percival, Miles Gibson, et al.
Analytica Chimica Acta (2019) Vol. 1067, pp. 11-30
Open Access | Times Cited: 105
Ready, Set, Flow! Automated Continuous Synthesis and Optimization
C. Breen, Anirudh M. K. Nambiar, Timothy F. Jamison, et al.
Trends in Chemistry (2021) Vol. 3, Iss. 5, pp. 373-386
Open Access | Times Cited: 102
Laboratory of the future: a modular flow platform with multiple integrated PAT tools for multistep reactions
Peter Sagmeister, Jason D. Williams, Christopher A. Hone, et al.
Reaction Chemistry & Engineering (2019) Vol. 4, Iss. 9, pp. 1571-1578
Open Access | Times Cited: 100
Autonomous Molecular Design: Then and Now
Tanja Dimitrov, Christoph Kreisbeck, Jill Becker, et al.
ACS Applied Materials & Interfaces (2019) Vol. 11, Iss. 28, pp. 24825-24836
Closed Access | Times Cited: 98
Low‐field benchtop NMR spectroscopy: status and prospects in natural product analysis†
Teris A. van Beek
Phytochemical Analysis (2020) Vol. 32, Iss. 1, pp. 24-37
Open Access | Times Cited: 84
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
The case for data science in experimental chemistry: examples and recommendations
Junko Yano, Kelly J. Gaffney, John M. Gregoire, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 5, pp. 357-370
Open Access | Times Cited: 60
Sampling and Analysis in Flow: The Keys to Smarter, More Controllable, and Sustainable Fine‐Chemical Manufacturing
Mathieu Morin, Wenyao Zhang, Debasis Mallik, et al.
Angewandte Chemie International Edition (2021) Vol. 60, Iss. 38, pp. 20606-20626
Closed Access | Times Cited: 59
Bayesian Self‐Optimization for Telescoped Continuous Flow Synthesis
Adam D. Clayton, Edward O. Pyzer‐Knapp, Mark Purdie, et al.
Angewandte Chemie International Edition (2022) Vol. 62, Iss. 3
Open Access | Times Cited: 57
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: 54
Machine learning directed multi-objective optimization of mixed variable chemical systems
Oliver J. Kershaw, Adam D. Clayton, Jamie A. Manson, et al.
Chemical Engineering Journal (2022) Vol. 451, pp. 138443-138443
Open Access | Times Cited: 53
Flow chemistry in the multi-step synthesis of natural products
Li Wan, Gaopan Kong, Minjie Liu, et al.
Green Synthesis and Catalysis (2022) Vol. 3, Iss. 3, pp. 243-258
Open Access | Times Cited: 45
Analytical Tools Integrated in Continuous-Flow Reactors: Which One for What?
Mireia Rodriguez‐Zubiri, François‐Xavier Felpin
Organic Process Research & Development (2022) Vol. 26, Iss. 6, pp. 1766-1793
Open Access | Times Cited: 41
Quid Pro Flow
Andrea Laybourn, Karen Robertson, Anna G. Slater
Journal of the American Chemical Society (2023) Vol. 145, Iss. 8, pp. 4355-4365
Open Access | Times Cited: 40
Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning
John H. Dunlap, Jeffrey G. Ethier, Amelia A. Putnam‐Neeb, et al.
Chemical Science (2023) Vol. 14, Iss. 30, pp. 8061-8069
Open Access | Times Cited: 28
Flow synthesis approaches to privileged scaffolds – recent routes reviewed for green and sustainable aspects
Antonella Ilenia Alfano, Margherita Brindisi, Heiko Lange
Green Chemistry (2021) Vol. 23, Iss. 6, pp. 2233-2292
Closed Access | Times Cited: 45
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