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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 Perovskites' Reap-Rest-Recovery Cycle
John M. Howard, Elizabeth M. Tennyson, Bernardo R. A. Neves, et al.
Joule (2018) Vol. 3, Iss. 2, pp. 325-337
Open Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

Consensus statement for stability assessment and reporting for perovskite photovoltaics based on ISOS procedures
Mark Khenkin, Eugene A. Katz, Antonio Abate, et al.
Nature Energy (2020) Vol. 5, Iss. 1, pp. 35-49
Open Access | Times Cited: 1180
Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis
Shijing Sun, Noor Titan Putri Hartono, Zekun Ren, et al.
Joule (2019) Vol. 3, Iss. 6, pp. 1437-1451
Open Access | Times Cited: 271
Passivation and process engineering approaches of halide perovskite films for high efficiency and stability perovskite solar cells
Abd. Rashid bin Mohd Yusoff, Maria Vasilopoulou, Dimitra G. Georgiadou, et al.
Energy & Environmental Science (2021) Vol. 14, Iss. 5, pp. 2906-2953
Open Access | Times Cited: 254
Heterogeneity at multiple length scales in halide perovskite semiconductors
Elizabeth M. Tennyson, Tiarnan A. S. Doherty, Samuel D. Stranks
Nature Reviews Materials (2019) Vol. 4, Iss. 9, pp. 573-587
Closed Access | Times Cited: 251
An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles
T. Jesper Jacobsson, Adam Hultqvist, Alberto García‐Fernández, et al.
Nature Energy (2021) Vol. 7, Iss. 1, pp. 107-115
Open Access | Times Cited: 218
Data-Driven Safety Envelope of Lithium-Ion Batteries for Electric Vehicles
Wei Li, Juner Zhu, Yong Xia, et al.
Joule (2019) Vol. 3, Iss. 11, pp. 2703-2715
Open Access | Times Cited: 181
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: 151
Machine Learning for Predicting the Band Gaps of ABX3 Perovskites from Elemental Properties
Vladislav Gladkikh, Dong Yeon Kim, Amir Hajibabaei, et al.
The Journal of Physical Chemistry C (2020) Vol. 124, Iss. 16, pp. 8905-8918
Closed Access | Times Cited: 140
Synergy of 3D and 2D Perovskites for Durable, Efficient Solar Cells and Beyond
Isaac Metcalf, Siraj Sidhik, Hao Zhang, et al.
Chemical Reviews (2023) Vol. 123, Iss. 15, pp. 9565-9652
Open Access | Times Cited: 112
Data‐Driven Materials Innovation and Applications
Zhuo Wang, Zhehao Sun, Hang Yin, et al.
Advanced Materials (2022) Vol. 34, Iss. 36
Closed Access | Times Cited: 106
Recent Progress in Interfacial Dipole Engineering for Perovskite Solar Cells
Yinyi Ma, Jue Gong, Peng Zeng, et al.
Nano-Micro Letters (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 48
Development on inverted perovskite solar cells: A review
Emmanuel A. Nyiekaa, Timothy A. Aika, Patience E. Orukpe, et al.
Heliyon (2024) Vol. 10, Iss. 2, pp. e24689-e24689
Open Access | Times Cited: 23
Advancements in Perovskites for Solar Cell Commercialization: A Review
Tejas Dhanalaxmi Raju, Vignesh Murugadoss, Kiran A. Nirmal, et al.
Advanced Powder Materials (2025), pp. 100275-100275
Open Access | Times Cited: 2
How machine learning can help select capping layers to suppress perovskite degradation
Noor Titan Putri Hartono, Janak Thapa, Armi Tiihonen, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 129
Machine-Learning-Accelerated Perovskite Crystallization
Jeffrey Kirman, Andrew Johnston, D.A. Kuntz, et al.
Matter (2020) Vol. 2, Iss. 4, pp. 938-947
Open Access | Times Cited: 122
Wide-bandgap, low-bandgap, and tandem perovskite solar cells
Zhaoning Song, Cong Chen, Chongwen Li, et al.
Semiconductor Science and Technology (2019) Vol. 34, Iss. 9, pp. 093001-093001
Closed Access | Times Cited: 107
Interface Engineering Driven Stabilization of Halide Perovskites against Moisture, Heat, and Light for Optoelectronic Applications
Aditya Narayan Singh, Sandeep Kajal, Junu Kim, et al.
Advanced Energy Materials (2020) Vol. 10, Iss. 30
Closed Access | Times Cited: 98
Critical review of machine learning applications in perovskite solar research
Beyza Yılmaz, Ramazan Yıldırım
Nano Energy (2020) Vol. 80, pp. 105546-105546
Closed Access | Times Cited: 98
Machine learning for halide perovskite materials
Lei Zhang, Mu He, Shaofeng Shao
Nano Energy (2020) Vol. 78, pp. 105380-105380
Closed Access | Times Cited: 92
Machine Learning Roadmap for Perovskite Photovoltaics
Meghna Srivastava, John M. Howard, Tao Gong, et al.
The Journal of Physical Chemistry Letters (2021) Vol. 12, Iss. 32, pp. 7866-7877
Closed Access | Times Cited: 68
Assessment of uncertainties and variations in PV modules degradation rates and lifetime predictions using physical models
Ismail Kaaya, Julián Ascencio‐Vásquez, Karl‐Anders Weiß, et al.
Solar Energy (2021) Vol. 218, pp. 354-367
Open Access | Times Cited: 66
Topological feature engineering for machine learning based halide perovskite materials design
D. Vijay Anand, Qiang Xu, JunJie Wee, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 40
Mechanical energy metamaterials in interstellar travel
Pengcheng Jiao
Progress in Materials Science (2023) Vol. 137, pp. 101132-101132
Closed Access | Times Cited: 34
Machine Learning Enables Prediction of Halide Perovskites’ Optical Behavior with >90% Accuracy
Meghna Srivastava, Abigail R. Hering, Yu An, et al.
ACS Energy Letters (2023) Vol. 8, Iss. 4, pp. 1716-1722
Open Access | Times Cited: 27
Lead-free perovskite-inspired semiconductors for indoor light-harvesting – the present and the future
G. Krishnamurthy Grandhi, Lethy Krishnan Jagadamma, Vipinraj Sugathan, et al.
Chemical Communications (2023) Vol. 59, Iss. 56, pp. 8616-8625
Open Access | Times Cited: 24
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