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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:

Organic reactivity from mechanism to machine learning
Kjell Jorner, Anna Tomberg, Christoph Bauer, et al.
Nature Reviews Chemistry (2021) Vol. 5, Iss. 4, pp. 240-255
Closed Access | Times Cited: 142

Showing 1-25 of 142 citing articles:

Late-stage C–H functionalization offers new opportunities in drug discovery
Lucas Guillemard, Nikolaos Kaplaneris, Lutz Ackermann, et al.
Nature Reviews Chemistry (2021) Vol. 5, Iss. 8, pp. 522-545
Closed Access | Times Cited: 579
C–H activation
Torben Rogge, Nikolaos Kaplaneris, Naoto Chatani, et al.
Nature Reviews Methods Primers (2021) Vol. 1, Iss. 1
Closed Access | Times Cited: 426
SELFIES and the future of molecular string representations
Mario Krenn, Qianxiang Ai, Senja Barthel, et al.
Patterns (2022) Vol. 3, Iss. 10, pp. 100588-100588
Open Access | Times Cited: 154
Using Data Science To Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical Sources
Stavros K. Kariofillis, Shutian Jiang, A. Zuranski, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 2, pp. 1045-1055
Open Access | Times Cited: 129
Late-stage Functionalization for Improving Drug-like Molecular Properties
Nathan J. Castellino, Andrew P. Montgomery, Jonathan J. Danon, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8127-8153
Closed Access | Times Cited: 98
Biocatalysed synthesis planning using data-driven learning
Daniel Probst, Matteo Manica, Yves Gaëtan Nana Teukam, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 94
Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, R.I. Zubatyuk, Maksim Kulichenko, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 9, pp. 653-672
Closed Access | Times Cited: 90
Accelerated chemical science with AI
Seoin Back, Alán Aspuru-Guzik, Michele Ceriotti, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 23-33
Open Access | Times Cited: 43
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: 15
Catalytic Asymmetric Hydroalkoxylation of C–C Multiple Bonds
Jennifer L. Kennemur, Rajat Maji, Manuel J. Scharf, et al.
Chemical Reviews (2021) Vol. 121, Iss. 24, pp. 14649-14681
Open Access | Times Cited: 97
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: 67
Machine learning activation energies of chemical reactions
Toby Lewis‐Atwell, Piers A. Townsend, Matthew N. Grayson
Wiley Interdisciplinary Reviews Computational Molecular Science (2021) Vol. 12, Iss. 4
Open Access | Times Cited: 60
Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings
Jules Schleinitz, Maxime Langevin, Yanis Smail, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 32, pp. 14722-14730
Open Access | Times Cited: 53
Reactions in single-molecule junctions
Hongliang Chen, Chuancheng Jia, Xin Zhu, et al.
Nature Reviews Materials (2022) Vol. 8, Iss. 3, pp. 165-185
Closed Access | Times Cited: 52
Genetic Optimization of Homogeneous Catalysts
Rubén Laplaza, Simone Gallarati, Clémence Corminbœuf
Chemistry - Methods (2022) Vol. 2, Iss. 6
Open Access | Times Cited: 43
When machine learning meets molecular synthesis
João C. A. Oliveira, Johanna Frey, Shuo‐Qing Zhang, et al.
Trends in Chemistry (2022) Vol. 4, Iss. 10, pp. 863-885
Closed Access | Times Cited: 40
A generalized-template-based graph neural network for accurate organic reactivity prediction
Shuan Chen, Yousung Jung
Nature Machine Intelligence (2022) Vol. 4, Iss. 9, pp. 772-780
Closed Access | Times Cited: 39
Machine learning integrated photocatalysis: progress and challenges
Luyao Ge, Yuanzhen Ke, Xiaobo Li
Chemical Communications (2023) Vol. 59, Iss. 39, pp. 5795-5806
Closed Access | Times Cited: 34
Hybrid Machine Learning Approach to Predict the Site Selectivity of Iridium-Catalyzed Arene Borylation
Eike Caldeweyher, Masha Elkin, Golsa Gheibi, et al.
Journal of the American Chemical Society (2023) Vol. 145, Iss. 31, pp. 17367-17376
Closed Access | Times Cited: 34
Molecular Machine Learning for Chemical Catalysis: Prospects and Challenges
Sukriti Singh, Raghavan B. Sunoj
Accounts of Chemical Research (2023) Vol. 56, Iss. 3, pp. 402-412
Closed Access | Times Cited: 32
Deep learning metal complex properties with natural quantum graphs
Hannes Kneiding, Ruslan Lukin, Lucas Lang, et al.
Digital Discovery (2023) Vol. 2, Iss. 3, pp. 618-633
Open Access | Times Cited: 22
Structural design of organic battery electrode materials: from DFT to artificial intelligence
Tingting Wu, Gaole Dai, Jinjia Xu, et al.
Rare Metals (2023) Vol. 42, Iss. 10, pp. 3269-3303
Closed Access | Times Cited: 22
Directional multiobjective optimization of metal complexes at the billion-system scale
Hannes Kneiding, Ainara Nova, David Balcells
Nature Computational Science (2024) Vol. 4, Iss. 4, pp. 263-273
Open Access | Times Cited: 12
Automated Transition Metal Catalysts Discovery and Optimisation with AI and Machine Learning
S. Macé, Yingjian Xu, Bao N. Nguyen
ChemCatChem (2024) Vol. 16, Iss. 10
Open Access | Times Cited: 9
Data Generation for Machine Learning Interatomic Potentials and Beyond
Maksim Kulichenko, Benjamin Nebgen, Nicholas Lubbers, et al.
Chemical Reviews (2024) Vol. 124, Iss. 24, pp. 13681-13714
Closed Access | Times Cited: 9
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