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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:

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

Showing 26-50 of 175 citing articles:

Organic Superbases in Recent Synthetic Methodology Research
Thomas R. Puleo, Stephen J. Sujansky, Shawn E. Wright, et al.
Chemistry - A European Journal (2020) Vol. 27, Iss. 13, pp. 4216-4229
Closed Access | Times Cited: 94
Inverse methods for design of soft materials
Zachary M. Sherman, Michael P. Howard, Beth A. Lindquist, et al.
The Journal of Chemical Physics (2020) Vol. 152, Iss. 14
Open Access | Times Cited: 88
Molecular Representation: Going Long on Fingerprints
Lagnajit Pattanaik, Connor W. Coley
Chem (2020) Vol. 6, Iss. 6, pp. 1204-1207
Open Access | Times Cited: 87
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
Active learning accelerates ab initio molecular dynamics on reactive energy surfaces
Shi Jun Ang, Wujie Wang, Daniel Schwalbe‐Koda, et al.
Chem (2021) Vol. 7, Iss. 3, pp. 738-751
Open Access | Times Cited: 74
Combining machine learning and high-throughput experimentation to discover photocatalytically active organic molecules
Xiaobo Li, Phillip M. Maffettone, Yu Che, et al.
Chemical Science (2021) Vol. 12, Iss. 32, pp. 10742-10754
Open Access | Times Cited: 74
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
Artificial intelligence and automation in computer aided synthesis planning
Amol Thakkar, Simon Johansson, Kjell Jorner, et al.
Reaction Chemistry & Engineering (2020) Vol. 6, Iss. 1, pp. 27-51
Closed Access | Times Cited: 68
Bayesian optimization of nanoporous materials
Aryan Deshwal, Cory M. Simon, Janardhan Rao Doppa
Molecular Systems Design & Engineering (2021) Vol. 6, Iss. 12, pp. 1066-1086
Open Access | Times Cited: 67
Efficient hyperparameter tuning for kernel ridge regression with Bayesian optimization
Annika Stuke, Patrick Rinke, Milica Todorović
Machine Learning Science and Technology (2021) Vol. 2, Iss. 3, pp. 035022-035022
Open Access | Times Cited: 64
Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space
Stefan Heinen, Guido Falk von Rudorff, O. Anatole von Lilienfeld
The Journal of Chemical Physics (2021) Vol. 155, Iss. 6
Open Access | Times Cited: 64
Data-driven algorithms for inverse design of polymers
Kianoosh Sattari, Yunchao Xie, Jian Lin
Soft Matter (2021) Vol. 17, Iss. 33, pp. 7607-7622
Closed Access | Times Cited: 60
Transition to sustainable chemistry through digitalization
Peter Fantke, Claudio Cinquemani, Polina Yaseneva, et al.
Chem (2021) Vol. 7, Iss. 11, pp. 2866-2882
Open Access | Times Cited: 59
Predicting reaction conditions from limited data through active transfer learning
Eunjae Shim, Joshua Kammeraad, Ziping Xu, et al.
Chemical Science (2022) Vol. 13, Iss. 22, pp. 6655-6668
Open Access | Times Cited: 36
Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide
Xiaoqian Wang, Yang Huang, Xiaoyu Xie, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 28
AI-driven robotic chemist for autonomous synthesis of organic molecules
Taesin Ha, Dongseon Lee, Youngchun Kwon, et al.
Science Advances (2023) Vol. 9, Iss. 44
Open Access | Times Cited: 28
First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis
Rui Xu, Jan Meisner, Alexander M. Chang, et al.
Chemical Science (2023) Vol. 14, Iss. 27, pp. 7447-7464
Open Access | Times Cited: 25
Atlas: A Brain for Self-driving Laboratories
Riley J. Hickman, Malcolm Sim, Sergio Pablo‐García, et al.
(2023)
Open Access | Times Cited: 20
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
Flow Synthesis of Metal Halide Perovskite Quantum Dots: From Rapid Parameter Space Mapping to AI-Guided Modular Manufacturing
Kameel Abdel‐Latif, Fazel Bateni, Steven Crouse, et al.
Matter (2020) Vol. 3, Iss. 4, pp. 1053-1086
Open Access | Times Cited: 57
AI-assisted synthesis prediction
Simon Johansson, Amol Thakkar, Thierry Kogej, et al.
Drug Discovery Today Technologies (2019) Vol. 32-33, pp. 65-72
Closed Access | Times Cited: 53
Machine learning in experimental materials chemistry
Balaranjan Selvaratnam, Ranjit T. Koodali
Catalysis Today (2020) Vol. 371, pp. 77-84
Open Access | Times Cited: 50
Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge
Anna M. Hiszpanski, Brian Gallagher, Karthik Chellappan, et al.
Journal of Chemical Information and Modeling (2020) Vol. 60, Iss. 6, pp. 2876-2887
Open Access | Times Cited: 49
Inferring experimental procedures from text-based representations of chemical reactions
Alain C. Vaucher, Philippe Schwaller, Joppe Geluykens, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 49
Recent progress on the prospective application of machine learning to structure-based virtual screening
Ghita Ghislat, Taufiq Rahman, Pedro J. Ballester
Current Opinion in Chemical Biology (2021) Vol. 65, pp. 28-34
Open Access | Times Cited: 47

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