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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:

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

Showing 1-25 of 68 citing articles:

A field guide to flow chemistry for synthetic organic chemists
Luca Capaldo, Zhenghui Wen, Timothy Noël
Chemical Science (2023) Vol. 14, Iss. 16, pp. 4230-4247
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: 110
Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 5, pp. 525-535
Open Access | Times Cited: 96
From Platform to Knowledge Graph: Evolution of Laboratory Automation
Jiaru Bai, Liwei Cao, Sebastian Mosbach, et al.
JACS Au (2022) Vol. 2, Iss. 2, pp. 292-309
Open Access | Times Cited: 68
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
Continuous flow synthesis enabling reaction discovery
Antonella Ilenia Alfano, Jorge García‐Lacuna, Oliver Griffiths, et al.
Chemical Science (2024) Vol. 15, Iss. 13, pp. 4618-4630
Open Access | Times Cited: 14
Enhancing preclinical drug discovery with artificial intelligence
Ramachandran Vijayan, Jan Kihlberg, Jason B. Cross, et al.
Drug Discovery Today (2021) Vol. 27, Iss. 4, pp. 967-984
Open Access | Times Cited: 94
Artificial intelligence-powered microfluidics for nanomedicine and materials synthesis
Linbo Liu, Mingcheng Bi, Yunhua Wang, et al.
Nanoscale (2021) Vol. 13, Iss. 46, pp. 19352-19366
Closed Access | Times Cited: 65
Machine learning for design principles for single atom catalysts towards electrochemical reactions
Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, et al.
Journal of Materials Chemistry A (2022) Vol. 10, Iss. 29, pp. 15309-15331
Open Access | Times Cited: 63
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
Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy
Xinyuan Bi, Li Lin, Zhou Chen, et al.
Small Methods (2023) Vol. 8, Iss. 1
Closed Access | Times Cited: 34
Artificial Intelligence in Drug Discovery and Development
Kit‐Kay Mak, Yi-Hang Wong, Mallikarjuna Rao Pichika
Springer eBooks (2023), pp. 1-38
Closed Access | Times Cited: 26
Unbiasing Retrosynthesis Language Models with Disconnection Prompts
Amol Thakkar, Alain C. Vaucher, Andrea Byekwaso, et al.
ACS Central Science (2023) Vol. 9, Iss. 7, pp. 1488-1498
Open Access | Times Cited: 20
Boosting engineering strategies for plastic hydrocracking applications: a machine learning-based multi-objective optimization framework
Zhe Ma, Zhibo Zhang, Changyuan Wang, et al.
Green Chemistry (2025)
Closed Access
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
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application
Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 5
Artificial intelligence in molecular de novo design: Integration with experiment
Jon Paul Janet, Lewis Mervin, Ola Engkvist
Current Opinion in Structural Biology (2023) Vol. 80, pp. 102575-102575
Open Access | Times Cited: 12
Multistep retrosynthesis combining a disconnection aware triple transformer loop with a route penalty score guided tree search
David Kreutter, Jean‐Louis Reymond
Chemical Science (2023) Vol. 14, Iss. 36, pp. 9959-9969
Open Access | Times Cited: 12
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: 12
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: 3
A Review of Large Language Models and Autonomous Agents in Chemistry
Mayk Caldas Ramos, Christopher J. Collison, Andrew Dickson White
Chemical Science (2024)
Open Access | Times Cited: 3
Computational mechanistic study in organometallic catalysis: Why prediction is still a challenge
Natalie Fey, Jason M. Lynam
Wiley Interdisciplinary Reviews Computational Molecular Science (2021) Vol. 12, Iss. 4
Open Access | Times Cited: 26
Putting Chemical Knowledge to Work in Machine Learning for Reactivity
Kjell Jorner
CHIMIA International Journal for Chemistry (2023) Vol. 77, Iss. 1/2, pp. 22-22
Open Access | Times Cited: 10
Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science
Ifra Saifi, Basharat Ahmad Bhat, Syed Suhail Hamdani, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 12, pp. 6523-6541
Closed Access | Times Cited: 10
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
Simon Johansson, Hampus Gummesson Svensson, Esben Jannik Bjerrum, et al.
Molecular Informatics (2022) Vol. 41, Iss. 12
Closed Access | Times Cited: 16
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