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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:

Data-driven discovery of small electroactive molecules for energy storage in aqueous redox flow batteries
Qi Zhang, Abhishek Khetan, Elif Sorkun, et al.
Energy storage materials (2022) Vol. 47, pp. 167-177
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations
Juran Noh, Hieu A. Doan, Heather Job, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 15
Accelerating Computation of Acidity Constants and Redox Potentials for Aqueous Organic Redox Flow Batteries by Machine Learning Potential-Based Molecular Dynamics
Feng Wang, Ze-Bing Ma, Jun Cheng
Journal of the American Chemical Society (2024) Vol. 146, Iss. 21, pp. 14566-14575
Closed Access | Times Cited: 8
Machine learning for flow batteries: opportunities and challenges
Tianyu Li, Changkun Zhang, Xianfeng Li
Chemical Science (2022) Vol. 13, Iss. 17, pp. 4740-4752
Open Access | Times Cited: 33
Innovations in stack design and optimization strategies for redox flow batteries in large-scale energy storage
Lyuming Pan, H. Suresh Rao, Jiayou Ren, et al.
Deleted Journal (2024) Vol. 1, Iss. 3, pp. 100040-100040
Closed Access | Times Cited: 5
Investigation of Symmetric and Non-Symmetric Cell Designs for Redox Flow Batteries Utilizing Indigo Carmine as Anolyte
Telma Costa, Daniela Pinheiro, J. Sérgio Seixas de Melo
Deleted Journal (2025), pp. 100027-100027
Open Access
Utilizing Machine Learning to Advance Battery Materials Design: Challenges and Prospects
Souvik Manna, Poulami Paul, Surya Sekhar Manna, et al.
Chemistry of Materials (2025)
Closed Access
RedDB, a computational database of electroactive molecules for aqueous redox flow batteries
Elif Sorkun, Qi Zhang, Abhishek Khetan, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 25
Towards a comprehensive data infrastructure for redox-active organic molecules targeting non-aqueous redox flow batteries
Rebekah Duke, Vinayak Bhat, Parker Sornberger, et al.
Digital Discovery (2023) Vol. 2, Iss. 4, pp. 1152-1162
Open Access | Times Cited: 9
Machine Learning Orchestrating the Materials Discovery and Performance Optimization of Redox Flow Battery
Lina Tang, Puiki Leung, Qian Xu, et al.
ChemElectroChem (2024)
Open Access | Times Cited: 2
A high-capacity viologen-based anolyte for high energy density neutral pH aqueous redox-flow batteries
Anubhav Kumar, Bijay P. Tripathi
Journal of Energy Chemistry (2022) Vol. 78, pp. 222-231
Closed Access | Times Cited: 12
Density Functional Theory‐Based Protocol to Calculate the Redox Potentials of First‐row Transition Metal Complexes for Aqueous Redox Targeting Flow Batteries
Noura Rahbani, Piotr de Silva, Emmanuel Baudrin
ChemSusChem (2023) Vol. 16, Iss. 18
Open Access | Times Cited: 7
Quinones for Aqueous Organic Redox Flow Battery: A Prospective on Redox Potential, Solubility, and Stability
Fuead Hasan, Vivekananda Mahanta, Ahmed Adel A. Abdelazeez
Advanced Materials Interfaces (2023) Vol. 10, Iss. 24
Open Access | Times Cited: 7
Unlocking the Potential: Predicting Redox Behavior of Organic Molecules, from Linear Fits to Neural Networks
Rostislav Fedorov, Ganna Gryn’ova
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 15, pp. 4796-4814
Closed Access | Times Cited: 7
Discovery of lead quinone cathode materials for Li-ion batteries
Xuan Zhou, Abhishek Khetan, Jie Zheng, et al.
Digital Discovery (2023) Vol. 2, Iss. 4, pp. 1016-1025
Open Access | Times Cited: 6
Discovery of aza-aromatic anolytes for aqueous redox flow batteries via high-throughput screening
Qi Zhang, Abhishek Khetan, Elif Sorkun, et al.
Journal of Materials Chemistry A (2022) Vol. 10, Iss. 41, pp. 22214-22227
Closed Access | Times Cited: 10
High-Throughput Virtual Screening of Quinones for Aqueous Redox Flow Batteries: Status and Perspectives
Abhishek Khetan
Batteries (2022) Vol. 9, Iss. 1, pp. 24-24
Open Access | Times Cited: 10
Virtual screening of organic quinones as cathode materials for sodium-ion batteries
Xuan Zhou, René A. J. Janssen, Süleyman Er
Energy Advances (2023) Vol. 2, Iss. 6, pp. 820-828
Open Access | Times Cited: 5
N‐Alkylated Pyridoxal Derivatives as Negative Electrolyte Materials for Aqueous Organic Flow Batteries: Computational Screening**
Andrea Hamza, Flóra Boróka Németh, Ádám Madarász, et al.
Chemistry - A European Journal (2023) Vol. 29, Iss. 44
Open Access | Times Cited: 5
ExpFlow: a graphical user interface for automated reproducible electrochemistry
Rebekah Duke, Siamak Mahmoudi, Aman Preet Kaur, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 163-172
Open Access | Times Cited: 5
Density functional theory and machine learning for electrochemical square-scheme prediction: an application to quinone-type molecules relevant to redox flow batteries
Arsalan Hashemi, Reza Khakpour, Amir Mahdian, et al.
Digital Discovery (2023) Vol. 2, Iss. 5, pp. 1565-1576
Open Access | Times Cited: 4
Towards Reproducible and Automated Electrochemistry
Rebekah Duke, Siamak Mahmoudi, Aman Preet Kaur, et al.
(2023)
Open Access | Times Cited: 2
Beyond conventional batteries: a review on semi-solid and redox targeting flow batteries-LiFePO4 as a case study
Nabil El Halya, Marwa Tayoury, Mohamed Aqil, et al.
Sustainable Energy & Fuels (2024) Vol. 8, Iss. 11, pp. 2330-2356
Closed Access
RedPred, a machine learning model for the prediction of redox reaction energies of the aqueous organic electrolytes
Murat Cihan Sorkun, Elham Nour Ghassemi, Cihan Yatbaz, et al.
Artificial Intelligence Chemistry (2024) Vol. 2, Iss. 1, pp. 100064-100064
Open Access
Influence Of The Concentration and the Dimensions of the Active Surface on the Performance of a Fully Organic Redox Flow Battery Using Indigo Carmine as Anolyte
Telma Costa, Daniela Ribeiro Pinheiro, J. Sérgio Seixas de Melo
(2024)
Closed Access
RedPred, a machine learning model for the prediction of redox reaction energies of the aqueous organic electrolytes
Murat Cihan Sorkun, Elham Nour Ghassemi, Cihan Yatbaz, et al.
(2023)
Open Access | Times Cited: 1
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