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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 with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing
Zhe Liu, Nicholas Rolston, Austin C. Flick, et al.
Joule (2022) Vol. 6, Iss. 4, pp. 834-849
Open Access | Times Cited: 122

Showing 1-25 of 122 citing articles:

The rise of self-driving labs in chemical and materials sciences
Milad Abolhasani, Eugenia Kumacheva
Nature Synthesis (2023) Vol. 2, Iss. 6, pp. 483-492
Open Access | Times Cited: 259
Enhancing property prediction and process optimization in building materials through machine learning: A review
Konstantinos I. Stergiou, Charis Ntakolia, Paris Varytis, et al.
Computational Materials Science (2023) Vol. 220, pp. 112031-112031
Open Access | Times Cited: 92
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
Kedar Hippalgaonkar, Qianxiao Li, Xiaonan Wang, et al.
Nature Reviews Materials (2023) Vol. 8, Iss. 4, pp. 241-260
Closed Access | Times Cited: 85
Scope of machine learning in materials research—A review
Md Hosne Mobarak, Mariam Akter Mimona, Md Aminul Islam, et al.
Applied Surface Science Advances (2023) Vol. 18, pp. 100523-100523
Open Access | Times Cited: 61
Active learning guides discovery of a champion four-metal perovskite oxide for oxygen evolution electrocatalysis
Junseok Moon, Wiktor Beker, Marta Siek, et al.
Nature Materials (2023) Vol. 23, Iss. 1, pp. 108-115
Closed Access | Times Cited: 51
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: 46
Self-Driving Laboratories for Chemistry and Materials Science
Gary Tom, Stefan P. Schmid, Sterling G. Baird, et al.
Chemical Reviews (2024) Vol. 124, Iss. 16, pp. 9633-9732
Open Access | Times Cited: 35
Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics
Ying Shang, Ziyu Xiong, Kang An, et al.
Materials Genome Engineering Advances (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 18
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: 54
Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives
Nitin Bansal, Snehangshu Mishra, Himanshu Dixit, et al.
Energy Technology (2023) Vol. 11, Iss. 12
Open Access | Times Cited: 34
Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells
Jiyun Zhang, Bowen Liu, Ziyi Liu, et al.
Advanced Energy Materials (2023) Vol. 13, Iss. 48
Open Access | Times Cited: 29
Machine learning for perovskite solar cell design
Hui Zhan, Min Wang, Xiang Yin, et al.
Computational Materials Science (2023) Vol. 226, pp. 112215-112215
Closed Access | Times Cited: 28
Meticulous research for design of plasmonics sensors for cancer detection and food contaminants analysis via machine learning and artificial intelligence
Fatemeh Jafrasteh, Ali Farmani, J Mohamadi
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 26
Photochemical Shield Enabling Highly Efficient Perovskite Photovoltaics
Run‐Jun Jin, Yanhui Lou, Lei Huang, et al.
Advanced Materials (2024) Vol. 36, Iss. 21
Closed Access | Times Cited: 15
Predicting photovoltaic efficiency in Cs-based perovskite solar cells: A comprehensive study integrating SCAPS simulation and machine learning models
Nikhil Shrivastav, Jaya Madan, Rahul Pandey
Solid State Communications (2024) Vol. 380, pp. 115437-115437
Closed Access | Times Cited: 14
Advances in materials informatics: a review
Dawn Sivan, K. Satheesh Kumar, Aziman Abdullah, et al.
Journal of Materials Science (2024) Vol. 59, Iss. 7, pp. 2602-2643
Closed Access | Times Cited: 12
The Future of Material Scientists in an Age of Artificial Intelligence
Ayman Maqsood, Chen Chen, T. Jesper Jacobsson
Advanced Science (2024) Vol. 11, Iss. 19
Open Access | Times Cited: 12
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs
Kai Yuan Andre Low, Flore Mekki‐Berrada, Abhishek Gupta, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 12
Machine Learning for Screening Small Molecules as Passivation Materials for Enhanced Perovskite Solar Cells
Xin Zhang, Bin Ding, Yao Wang, et al.
Advanced Functional Materials (2024) Vol. 34, Iss. 30
Closed Access | Times Cited: 10
Artificial Intelligence-Based, Wavelet-Aided Prediction of Long-Term Outdoor Performance of Perovskite Solar Cells
Ioannis Kouroudis, Kenedy Tabah Tanko, Masoud Karimipour, et al.
ACS Energy Letters (2024) Vol. 9, Iss. 4, pp. 1581-1586
Open Access | Times Cited: 9
Autonomous Optimization of Air‐Processed Perovskite Solar Cell in a Multidimensional Parameter Space
Jiyun Zhang, Vincent M. Le Corre, Jianchang Wu, et al.
Advanced Energy Materials (2025)
Open Access | Times Cited: 1
Accelerated Discovery of Solvation Structure Engineering for Stable Aqueous Rechargeable Zinc Batteries via Physics‐Guided Bayesian Active Learning
Minsu Kim, Minji Lee, Inyoung Choi, et al.
Small (2025)
Closed Access | Times Cited: 1
The Impact of Machine Learning in Energy Materials Research: The Case of Halide Perovskites
Filippo De Angelis
ACS Energy Letters (2023) Vol. 8, Iss. 2, pp. 1270-1272
Closed Access | Times Cited: 21
Selecting an appropriate machine-learning model for perovskite solar cell datasets
Mohamed M. Salah, Zahraa Ismail, Sameh O. Abdellatif
Materials for Renewable and Sustainable Energy (2023) Vol. 12, Iss. 3, pp. 187-198
Open Access | Times Cited: 21
The role of machine learning in perovskite solar cell research
Chen Chen, Ayman Maqsood, T. Jesper Jacobsson
Journal of Alloys and Compounds (2023) Vol. 960, pp. 170824-170824
Closed Access | Times Cited: 19
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