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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:

Optimum catalyst selection over continuous and discrete process variables with a single droplet microfluidic reaction platform
Lorenz M. Baumgartner, Connor W. Coley, Brandon J. Reizman, et al.
Reaction Chemistry & Engineering (2018) Vol. 3, Iss. 3, pp. 301-311
Open Access | Times Cited: 103

Showing 1-25 of 103 citing articles:

Using Machine Learning To Predict Suitable Conditions for Organic Reactions
Hanyu Gao, Thomas J. Struble, Connor W. Coley, et al.
ACS Central Science (2018) Vol. 4, Iss. 11, pp. 1465-1476
Open Access | Times Cited: 360
Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
Artur M. Schweidtmann, Adam D. Clayton, Nicholas Holmes, et al.
Chemical Engineering Journal (2018) Vol. 352, pp. 277-282
Open Access | Times Cited: 298
A Brief Introduction to Chemical Reaction Optimization
Connor J. Taylor, Alexander Pomberger, Kobi Felton, et al.
Chemical Reviews (2023) Vol. 123, Iss. 6, pp. 3089-3126
Open Access | Times Cited: 183
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
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: 168
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
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: 98
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: 59
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: 18
High Throughput Strategies for the Discovery and Optimization of Catalytic Reactions
Eric S. Isbrandt, Ryan J. Sullivan, Stephen G. Newman
Angewandte Chemie International Edition (2018) Vol. 58, Iss. 22, pp. 7180-7191
Closed Access | Times Cited: 136
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: 130
Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis
Yehia Amar, Artur M. Schweidtmann, Paul Deutsch, et al.
Chemical Science (2019) Vol. 10, Iss. 27, pp. 6697-6706
Open Access | Times Cited: 116
Continuous Synthesis of Nanocrystals via Flow Chemistry Technology
Jinsong Sui, Junyu Yan, Di Liu, et al.
Small (2019) Vol. 16, Iss. 15
Closed Access | Times Cited: 92
Use of a Droplet Platform To Optimize Pd-Catalyzed C–N Coupling Reactions Promoted by Organic Bases
Lorenz M. Baumgartner, Joseph M. Dennis, Nicholas A. White, et al.
Organic Process Research & Development (2019) Vol. 23, Iss. 8, pp. 1594-1601
Closed Access | Times Cited: 77
Iterative experimental design based on active machine learning reduces the experimental burden associated with reaction screening
Natalie S. Eyke, William H. Green, Klavs F. Jensen
Reaction Chemistry & Engineering (2020) Vol. 5, Iss. 10, pp. 1963-1972
Open Access | Times Cited: 72
Chemputation and the Standardization of Chemical Informatics
Alexander Hammer, Artem I. Leonov, Nicola L. Bell, et al.
JACS Au (2021) Vol. 1, Iss. 10, pp. 1572-1587
Open Access | Times Cited: 60
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: 52
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: 52
Machine-Learning-Guided Discovery of Electrochemical Reactions
Andrew F. Zahrt, Yiming Mo, Kakasaheb Y. Nandiwale, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 49, pp. 22599-22610
Open Access | Times Cited: 45
Continuous stirred-tank reactor cascade platform for self-optimization of reactions involving solids
Kakasaheb Y. Nandiwale, Travis Hart, Andrew F. Zahrt, et al.
Reaction Chemistry & Engineering (2022) Vol. 7, Iss. 6, pp. 1315-1327
Open Access | Times Cited: 40
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: 38
Atlas: A Brain for Self-driving Laboratories
Riley J. Hickman, Malcolm Sim, Sergio Pablo‐García, et al.
(2023)
Open Access | Times Cited: 20
Open-Source Chromatographic Data Analysis for Reaction Optimization and Screening
Christian P. Haas, Maximilian Lübbesmeyer, Edward H. Jin, et al.
ACS Central Science (2023) Vol. 9, Iss. 2, pp. 307-317
Open Access | Times Cited: 19
Autonomous chemistry: Navigating self-driving labs in chemical and material sciences
Oliver Bayley, Elia Savino, Aidan Slattery, et al.
Matter (2024) Vol. 7, Iss. 7, pp. 2382-2398
Closed Access | Times Cited: 6
Adaptive Optimization of Chemical Reactions with Minimal Experimental Information
Daniel Reker, Emily Hoyt, Gonçalo J. L. Bernardes, et al.
Cell Reports Physical Science (2020) Vol. 1, Iss. 11, pp. 100247-100247
Open Access | Times Cited: 65
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