Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 73 citing articles:

A time and resource efficient machine learning assisted design of non-fullerene small molecule acceptors for P3HT-based organic solar cells and green solvent selection
Asif Mahmood, Jin‐Liang Wang
Journal of Materials Chemistry A (2021) Vol. 9, Iss. 28, pp. 15684-15695
Closed Access | Times Cited: 184
Machine Learning for Organic Photovoltaic Polymers: A Minireview
Asif Mahmood, Ahmad Irfan, Jin‐Liang Wang
Chinese Journal of Polymer Science (2022) Vol. 40, Iss. 8, pp. 870-876
Closed Access | Times Cited: 138
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: 88
A bibliometric analysis of machine learning techniques in photovoltaic cells and solar energy (2014–2022)
Abdelhamid Zaïdi
Energy Reports (2024) Vol. 11, pp. 2768-2779
Open Access | Times Cited: 26
Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm
Chunhui Xie, Haoke Qiu, Lu Liu, et al.
SmartMat (2025) Vol. 6, Iss. 1
Open Access | Times Cited: 4
Machine Learning in Polymer Research
Wei Ge, R. Silva‐González, Yanan Fan, et al.
Advanced Materials (2025)
Open Access | Times Cited: 2
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
Predicting power conversion efficiency of binary organic solar cells based on Y6 acceptor by machine learning
Qiming Zhao, Yuqing Shan, Chongchen Xiang, et al.
Journal of Energy Chemistry (2023) Vol. 82, pp. 139-147
Closed Access | Times Cited: 27
Machine learning strategies for small sample size in materials science
Qiuling Tao, Jinxin Yu, Xiangyu Mu, et al.
Science China Materials (2025)
Closed Access | Times Cited: 1
Development of Organic Semiconductor Materials for Organic Solar Cells via the Integration of Computational Quantum Chemistry and AI-Powered Machine Learning
Shafidah Shafian, Faizus Salehin, Sojeong Lee, et al.
ACS Applied Energy Materials (2025)
Closed Access | Times Cited: 1
Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms
Brianna Greenstein, Geoffrey Hutchison
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 13, pp. 6179-6191
Open Access | Times Cited: 22
Twisted-graphene-like perylene diimide with dangling functional chromophores as tunable small-molecule acceptors in binary-blend active layers of organic photovoltaics
Yu‐Che Lin, Chung-Hao Chen, Nian-Zu She, et al.
Journal of Materials Chemistry A (2021) Vol. 9, Iss. 36, pp. 20510-20517
Closed Access | Times Cited: 38
Designs and understanding of small molecule-based non-fullerene acceptors for realizing commercially viable organic photovoltaics
Minjun Kim, Seung Un Ryu, Sang Ah Park, et al.
Chemical Science (2021) Vol. 12, Iss. 42, pp. 14004-14023
Open Access | Times Cited: 35
Singlet‐Triplet Energy Gap as a Critical Molecular Descriptor for Predicting Organic Photovoltaic Efficiency
Guangchao Han, Yuanping Yi
Angewandte Chemie International Edition (2022) Vol. 61, Iss. 49
Closed Access | Times Cited: 25
Performance Prediction and Experimental Optimization Assisted by Machine Learning for Organic Photovoltaics
Zhi‐Wen Zhao, Yun Geng, Alessandro Troisi, et al.
Advanced Intelligent Systems (2022) Vol. 4, Iss. 6
Open Access | Times Cited: 23
Machine learning in energy chemistry: introduction, challenges and perspectives
Yuzhi Xu, Jiankai Ge, Cheng‐Wei Ju
Energy Advances (2023) Vol. 2, Iss. 7, pp. 896-921
Open Access | Times Cited: 15
Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques
Satyam Bhatti, Habib Ullah Manzoor, Bruno Michel, et al.
Advanced Energy and Sustainability Research (2023) Vol. 4, Iss. 10
Open Access | Times Cited: 15
Machine-learning-guided prediction of photovoltaic performance of non-fullerene organic solar cells using novel molecular and structural descriptors
Rakesh Suthar, T. Abhijith, Supravat Karak
Journal of Materials Chemistry A (2023) Vol. 11, Iss. 41, pp. 22248-22258
Closed Access | Times Cited: 15
Advancements in Organic-Based Hybrid Tandem Solar Cells Considering Light Absorption and Spectral Matching of Organic Materials
Hyuntae Choi, Seung Un Ryu, Dae Hwan Lee, et al.
ACS Energy Letters (2024) Vol. 9, Iss. 6, pp. 3136-3168
Closed Access | Times Cited: 5
Computational Identification of Novel Families of Nonfullerene Acceptors by Modification of Known Compounds
Zhi‐Wen Zhao, Ömer H. Omar, Daniele Padula, et al.
The Journal of Physical Chemistry Letters (2021) Vol. 12, Iss. 20, pp. 5009-5015
Open Access | Times Cited: 29
Accelerating the discovery of high-performance donor/acceptor pairs in photovoltaic materials via machine learning and density functional theory
Xiujuan Liu, Yueyue Shao, Tian Lu, et al.
Materials & Design (2022) Vol. 216, pp. 110561-110561
Open Access | Times Cited: 21
Machine Learning-Assisted Polymer Design for Improving the Performance of Non-Fullerene Organic Solar Cells
Kakaraparthi Kranthiraja, Akinori Saeki
ACS Applied Materials & Interfaces (2022) Vol. 14, Iss. 25, pp. 28936-28944
Closed Access | Times Cited: 21
Recent advances in the development of flexible dye-sensitized solar cells: fabrication, challenges and applications-a review
Chandan Dawo, Harsh Chaturvedi
Flexible and Printed Electronics (2023) Vol. 8, Iss. 1, pp. 013001-013001
Closed Access | Times Cited: 12
Beyond molecular structure: critically assessing machine learning for designing organic photovoltaic materials and devices
Martin Seifrid, Stanley Lo, Dylan G. Choi, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 24, pp. 14540-14558
Open Access | Times Cited: 4
Improved Predictions of Organic Photovoltaic Performance through Machine Learning Models Empowered by Artificially Generated Failure Data
Yuta Miyake, Kakaraparthi Kranthiraja, Fumitaka Ishiwari, et al.
Chemistry of Materials (2022) Vol. 34, Iss. 15, pp. 6912-6920
Closed Access | Times Cited: 17
Page 1 - Next Page

Scroll to top