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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:

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: 16

Showing 16 citing articles:

Recent developments in polymer semiconductors with excellent electron transport performances
Yunchao Zhang, Weifeng Zhang, Zhihui Chen, et al.
Chemical Society Reviews (2025)
Closed Access | Times Cited: 1
π-Conjugated Materials: Here, There, and Everywhere
Aurelio Mateo‐Alonso
Chemistry of Materials (2023) Vol. 35, Iss. 4, pp. 1467-1469
Closed Access | Times Cited: 21
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
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
Advancing organic photovoltaic cells for a sustainable future: The role of artificial intelligence (AI) and deep learning (DL) in enhancing performance and innovation
Hussein Togun, Ali Basem, Muhsin J. Jweeg, et al.
Solar Energy (2025) Vol. 291, pp. 113378-113378
Closed Access
Opportunities and challenges for machine learning to select combination of donor and acceptor materials for efficient organic solar cells
Prateek Malhotra, Kanupriya Khandelwal, Subhayan Biswas, et al.
Journal of Materials Chemistry C (2022) Vol. 10, Iss. 47, pp. 17781-17811
Closed Access | Times Cited: 17
Strategies and Mechanisms To Minimize Energy Loss in Non-Fullerene Bulk Heterojunction Organic Solar Cells: Experimental and Computational Approaches
Hemraj Dahiya, Rakesh Suthar, Supravat Karak, et al.
Energy & Fuels (2025)
Closed Access
Investigation of Short‐Circuit Current Density in Non‐Fullerene‐Based Ternary Organic Solar Cells by Incorporating Machine Learning Algorithms with Effective Descriptors
Min‐Hsuan Lee, Ying‐Chun Chen, Yi‐Ming Chang, et al.
Solar RRL (2025)
Closed Access
Data‐Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top‐Down/Bottom‐Up Design
J. Terence Blaskovits, Rubén Laplaza, Sergi Vela, et al.
Advanced Materials (2023) Vol. 36, Iss. 2
Open Access | Times Cited: 8
Impact of Alkyl-Based Side Chains in Conjugated Materials for Bulk Heterojunction Organic Photovoltaic Cells—A Review
Kathleen I. Chane‐Ching
Energies (2023) Vol. 16, Iss. 18, pp. 6639-6639
Open Access | Times Cited: 6
Predicting the multiple parameters of organic acceptors through machine learning using RDkit descriptors: An easy and fast pipeline
Khadijah Mohammedsaleh Katubi, Muhammad Saqib, Tayyaba Mubashir, et al.
International Journal of Quantum Chemistry (2023) Vol. 123, Iss. 23
Open Access | Times Cited: 5
Effectiveness and limitation of the performance prediction of perovskite solar cells by process informatics
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
Energy Advances (2024) Vol. 3, Iss. 4, pp. 812-820
Open Access | Times Cited: 1
Beyond Molecular Structure: Critically Assessing Machine Learning for Designing Organic Photovoltaic Materials and Devices
Martin Seifrid, Stanley Lo, Dylan G. Choi, et al.
(2024)
Open Access | Times Cited: 1
Machine Learning and Small Data-Guided Optimization of Silica Shell Morphology on Gold Nanorods
Akhlak U. Mahmood, Melanie M. Ghelardini, Joseph B. Tracy, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 19, pp. 9330-9340
Closed Access | Times Cited: 1
Predictive Modeling and Design of Organic Solar Cells: A Data-Driven Approach for Material Innovation
Bibhas Das, Anirban Mondal
ACS Applied Energy Materials (2024) Vol. 7, Iss. 20, pp. 9349-9363
Closed Access | Times Cited: 1
Data-driven discovery of organic electronic materials enabled by hybrid top-down/bottom-up design
J. Terence Blaskovits, Rubén Laplaza, Sergi Vela, et al.
(2022)
Open Access | Times Cited: 5
Beyond Molecular Structure: Critically Assessing Machine Learning for Designing Organic Photovoltaic Materials and Devices
Martin Seifrid, Stanley Lo, Dylan G. Choi, et al.
(2024)
Open Access
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