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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:

Machine Learning for Catalysis Informatics: Recent Applications and Prospects
Takashi Toyao, Zen Maeno, Satoru Takakusagi, et al.
ACS Catalysis (2019) Vol. 10, Iss. 3, pp. 2260-2297
Closed Access | Times Cited: 433

Showing 1-25 of 433 citing articles:

Machine learning for alloys
Gus L. W. Hart, Tim Mueller, Cormac Toher, et al.
Nature Reviews Materials (2021) Vol. 6, Iss. 8, pp. 730-755
Closed Access | Times Cited: 406
Open Catalyst 2020 (OC20) Dataset and Community Challenges
Lowik Chanussot, Abhishek Das, Siddharth Goyal, et al.
ACS Catalysis (2021) Vol. 11, Iss. 10, pp. 6059-6072
Open Access | Times Cited: 388
Emerging applications of zeolites in catalysis, separation and host–guest assembly
Yi Li, Jihong Yu
Nature Reviews Materials (2021) Vol. 6, Iss. 12, pp. 1156-1174
Closed Access | Times Cited: 333
The Sabatier Principle in Electrocatalysis: Basics, Limitations, and Extensions
Hideshi Ooka, Jun Huang, Kai S. Exner
Frontiers in Energy Research (2021) Vol. 9
Open Access | Times Cited: 302
Machine learning for perovskite materials design and discovery
Qiuling Tao, Pengcheng Xu, Minjie Li, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 290
Single-atom site catalysts for environmental catalysis
Ningqiang Zhang, Chenliang Ye, Han Yan, et al.
Nano Research (2020) Vol. 13, Iss. 12, pp. 3165-3182
Closed Access | Times Cited: 286
Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
Haoxin Mai, Tu C. Le, Dehong Chen, et al.
Chemical Reviews (2022) Vol. 122, Iss. 16, pp. 13478-13515
Closed Access | Times Cited: 242
ZnIn2S4‐Based Photocatalysts for Energy and Environmental Applications
Ruijie Yang, Liang Mei, Yingying Fan, et al.
Small Methods (2021) Vol. 5, Iss. 10
Closed Access | Times Cited: 223
Interpretable machine learning for knowledge generation in heterogeneous catalysis
Jacques A. Esterhuizen, Bryan R. Goldsmith, Suljo Linic
Nature Catalysis (2022) Vol. 5, Iss. 3, pp. 175-184
Closed Access | Times Cited: 223
The reverse water gas shift reaction: a process systems engineering perspective
Miriam González‐Castaño, Bogdan Dorneanu, Harvey Arellano-Garćıa
Reaction Chemistry & Engineering (2021) Vol. 6, Iss. 6, pp. 954-976
Closed Access | Times Cited: 221
Bimetallic Sites for Catalysis: From Binuclear Metal Sites to Bimetallic Nanoclusters and Nanoparticles
Lichen Liu, Avelino Corma
Chemical Reviews (2023) Vol. 123, Iss. 8, pp. 4855-4933
Open Access | Times Cited: 220
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
John A. Keith, Valentín Vassilev-Galindo, Bingqing Cheng, et al.
Chemical Reviews (2021) Vol. 121, Iss. 16, pp. 9816-9872
Open Access | Times Cited: 176
Perspective on integrating machine learning into computational chemistry and materials science
Julia Westermayr, Michael Gastegger, Kristof T. Schütt, et al.
The Journal of Chemical Physics (2021) Vol. 154, Iss. 23
Open Access | Times Cited: 157
Machine Learning for Atomic Simulation and Activity Prediction in Heterogeneous Catalysis: Current Status and Future
Sicong Ma, Zhi‐Pan Liu
ACS Catalysis (2020) Vol. 10, Iss. 22, pp. 13213-13226
Closed Access | Times Cited: 144
Machine learning for advanced energy materials
Liu Yun, Oladapo Christopher Esan, Zhefei Pan, et al.
Energy and AI (2021) Vol. 3, pp. 100049-100049
Open Access | Times Cited: 143
Transfer learning for solvation free energies: From quantum chemistry to experiments
Florence H. Vermeire, William H. Green
Chemical Engineering Journal (2021) Vol. 418, pp. 129307-129307
Open Access | Times Cited: 141
Developing sustainable, high-performance perovskites in photocatalysis: design strategies and applications
Haoxin Mai, Dehong Chen, Yasuhiro Tachibana, et al.
Chemical Society Reviews (2021) Vol. 50, Iss. 24, pp. 13692-13729
Closed Access | Times Cited: 140
Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, et al.
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 28, pp. 9901-9949
Open Access | Times Cited: 133
Roadmap on Machine learning in electronic structure
Heather J. Kulik, Thomas Hammerschmidt, Jonathan Schmidt, et al.
Electronic Structure (2022) Vol. 4, Iss. 2, pp. 023004-023004
Open Access | Times Cited: 123
The role of machine learning to boost the bioenergy and biofuels conversion
Zheng‐Xin Wang, Xinggan Peng, Ao Xia, et al.
Bioresource Technology (2021) Vol. 343, pp. 126099-126099
Closed Access | Times Cited: 118
Accelerated dinuclear palladium catalyst identification through unsupervised machine learning
Julian A. Hueffel, Theresa Sperger, Ignacio Funes‐Ardoiz, et al.
Science (2021) Vol. 374, Iss. 6571, pp. 1134-1140
Closed Access | Times Cited: 106
A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation
Manu Suvarna, Thaylan Pinheiro Araújo, Javier Pérez‐Ramírez
Applied Catalysis B Environment and Energy (2022) Vol. 315, pp. 121530-121530
Open Access | Times Cited: 88
Materials Nanoarchitectonics from Atom to Living Cell: A Method for Everything
Katsuhiko Ariga, Rawil Fakhrullin
Bulletin of the Chemical Society of Japan (2022) Vol. 95, Iss. 5, pp. 774-795
Closed Access | Times Cited: 85
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: 85
Interfacing single-atom catalysis with continuous-flow organic electrosynthesis
Mark A. Bajada, Jesús Sanjosé‐Orduna, Giovanni Di Liberto, et al.
Chemical Society Reviews (2022) Vol. 51, Iss. 10, pp. 3898-3925
Open Access | Times Cited: 82
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