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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:

Designing and understanding light-harvesting devices with machine learning
Florian Häse, Loı̈c M. Roch, Pascal Friederich, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 100

Showing 1-25 of 100 citing articles:

Machine Learning for Electronically Excited States of Molecules
Julia Westermayr, Philipp Marquetand
Chemical Reviews (2020) Vol. 121, Iss. 16, pp. 9873-9926
Open Access | Times Cited: 343
Unsupervised Learning Methods for Molecular Simulation Data
Aldo Glielmo, Brooke E. Husic, Álex Rodríguez, et al.
Chemical Reviews (2021) Vol. 121, Iss. 16, pp. 9722-9758
Open Access | Times Cited: 299
The principles, design and applications of fused-ring electron acceptors
Jiayu Wang, Peiyao Xue, Yiting Jiang, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 9, pp. 614-634
Closed Access | Times Cited: 298
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: 277
Sleep and human cognitive development
Gina M. Mason, Sanna Lokhandwala, Tracy Riggins, et al.
Sleep Medicine Reviews (2021) Vol. 57, pp. 101472-101472
Open Access | Times Cited: 169
Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES
AkshatKumar Nigam, Robert Pollice, Mario Krenn, et al.
Chemical Science (2021) Vol. 12, Iss. 20, pp. 7079-7090
Open Access | Times Cited: 106
Evaluation guidelines for machine learning tools in the chemical sciences
Andreas Bender, Nadine Schneider, Marwin Segler, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 6, pp. 428-442
Closed Access | Times Cited: 105
Optimizing biodiesel production from waste with computational chemistry, machine learning and policy insights: a review
Ahmed I. Osman, Mahmoud Nasr, Mohamed Farghali, et al.
Environmental Chemistry Letters (2024) Vol. 22, Iss. 3, pp. 1005-1071
Open Access | Times Cited: 55
A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management
Maria Drogkoula, Konstantinos Kokkinos, Nicholas Samaras
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12147-12147
Open Access | Times Cited: 51
Artificial intelligence interventions in 2D MXenes-based photocatalytic applications
Durga Madhab Mahapatra, Ashish Kumar, Rajesh Kumar, et al.
Coordination Chemistry Reviews (2025) Vol. 529, pp. 216460-216460
Closed Access | Times Cited: 2
Experiment‐Oriented Machine Learning of Polymer:Non‐Fullerene Organic Solar Cells
Kakaraparthi Kranthiraja, Akinori Saeki
Advanced Functional Materials (2021) Vol. 31, Iss. 23
Closed Access | Times Cited: 73
Machine Learning-Assisted Development of Organic Solar Cell Materials: Issues, Analyses, and Outlooks
Yuta Miyake, Akinori Saeki
The Journal of Physical Chemistry Letters (2021) Vol. 12, Iss. 51, pp. 12391-12401
Closed Access | Times Cited: 73
High-throughput oxygen chemical potential engineering of perovskite oxides for chemical looping applications
Xijun Wang, Yunfei Gao, Emily Krzystowczyk, et al.
Energy & Environmental Science (2022) Vol. 15, Iss. 4, pp. 1512-1528
Open Access | Times Cited: 69
Self-assembled supramolecular artificial light-harvesting nanosystems: construction, modulation, and applications
Xu‐Man Chen, Xiao Dong Chen, Xiaofang Hou, et al.
Nanoscale Advances (2022) Vol. 5, Iss. 7, pp. 1830-1852
Open Access | Times Cited: 57
The atomistic modeling of light-harvesting complexes from the physical models to the computational protocol
Edoardo Cignoni, Vladislav Sláma, Lorenzo Cupellini, et al.
The Journal of Chemical Physics (2022) Vol. 156, Iss. 12
Open Access | Times Cited: 54
Dimensional heterojunction design: The rising star of 2D bismuth-based nanostructured photocatalysts for solar-to-chemical conversion
Joel Jie Foo, Sue‐Faye Ng, Wee‐Jun Ong
Nano Research (2022)
Closed Access | Times Cited: 52
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: 38
In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back
Abdulrahman Aldossary, Jorge A. Campos-Gonzalez-Angulo, Sergio Pablo‐García, et al.
Advanced Materials (2024) Vol. 36, Iss. 30
Closed Access | Times Cited: 15
Identifying structure–absorption relationships and predicting absorption strength of non-fullerene acceptors for organic photovoltaics
Jun Yan, Xabier Rodríguez‐Martínez, Drew Pearce, et al.
Energy & Environmental Science (2022) Vol. 15, Iss. 7, pp. 2958-2973
Open Access | Times Cited: 35
Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics
Arif Ullah, Pavlo O. Dral
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 34
Analysis and evaluation of machine learning applications in materials design and discovery
Mahsa Golmohammadi, Masoud Aryanpour
Materials Today Communications (2023) Vol. 35, pp. 105494-105494
Closed Access | Times Cited: 20
Exploring KGeCl3 material for perovskite solar cell absorber layer through different machine learning models
Nikhil Shrivastav, Mir Aamir Hamid, Jaya Madan, et al.
Solar Energy (2024) Vol. 278, pp. 112784-112784
Closed Access | Times Cited: 8
Lanthanide-Metal-Doped Light-Harvesting Quantum Dots for Exceptional X-ray Imaging Scintillators
Xin Zhu, Renqian Zhou, Zhi Wang, et al.
ACS Energy Letters (2024), pp. 5137-5144
Closed Access | Times Cited: 8
Multi‐Fidelity High‐Throughput Optimization of Electrical Conductivity in P3HT‐CNT Composites
Daniil Bash, Yongqiang Cai, Vijila Chellappan, et al.
Advanced Functional Materials (2021) Vol. 31, Iss. 36
Open Access | Times Cited: 39
Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells
Brianna Greenstein, Geoffrey Hutchison
The Journal of Physical Chemistry Letters (2022) Vol. 13, Iss. 19, pp. 4235-4243
Open Access | Times Cited: 28
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