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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:

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening
Sauradeep Majumdar, Seyed Mohamad Moosavi, Kevin Maik Jablonka, et al.
ACS Applied Materials & Interfaces (2021) Vol. 13, Iss. 51, pp. 61004-61014
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

MOFs-Based Materials for Solid-State Hydrogen Storage: Strategies and Perspectives
Yuting Li, Qifei Guo, Zhao Ding, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 149665-149665
Closed Access | Times Cited: 86
Progress toward the computational discovery of new metal–organic framework adsorbents for energy applications
Peyman Z. Moghadam, Yongchul G. Chung, Randall Q. Snurr
Nature Energy (2024) Vol. 9, Iss. 2, pp. 121-133
Closed Access | Times Cited: 73
ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived Partial Atomic Charges and Descriptors for Machine Learning
Jake Burner, Jun Luo, Andrew J. P. White, et al.
Chemistry of Materials (2023) Vol. 35, Iss. 3, pp. 900-916
Open Access | Times Cited: 72
Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2’s Chemisorption and Diffusion in Mg-MOF-74
Bowen Zheng, Felipe Lopes Oliveira, Rodrigo Neumann Barros Ferreira, et al.
ACS Nano (2023) Vol. 17, Iss. 6, pp. 5579-5587
Closed Access | Times Cited: 43
Recent Developments in the Design and Fabrication of Electrochemical Biosensors Using Functional Materials and Molecules
K. Theyagarajan, Young‐Joon Kim
Biosensors (2023) Vol. 13, Iss. 4, pp. 424-424
Open Access | Times Cited: 43
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture
Anuroop Sriram, Sihoon Choi, Xiaohan Yu, et al.
ACS Central Science (2024) Vol. 10, Iss. 5, pp. 923-941
Open Access | Times Cited: 27
Inverse design of metal–organic frameworks for direct air capture of CO2via deep reinforcement learning
Hyunsoo Park, Sauradeep Majumdar, Xiaoqi Zhang, et al.
Digital Discovery (2024) Vol. 3, Iss. 4, pp. 728-741
Open Access | Times Cited: 21
Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery
Chunhua Li, Luqian Bao, Yixin Ji, et al.
Coordination Chemistry Reviews (2024) Vol. 514, pp. 215888-215888
Closed Access | Times Cited: 19
Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning
Xinyi Wang, Hanna Breunig, Peng Peng
Applied Energy (2025) Vol. 383, pp. 125346-125346
Closed Access | Times Cited: 2
Theoretical studies of metal-organic frameworks: Calculation methods and applications in catalysis, gas separation, and energy storage
Guangtong Hai, Haihui Wang
Coordination Chemistry Reviews (2022) Vol. 469, pp. 214670-214670
Closed Access | Times Cited: 48
Investigation of cryo-adsorption hydrogen storage capacity of rapidly synthesized MOF-5 by mechanochemical method
Zhiwen Zhu, Qiongbin Zheng
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 13, pp. 5166-5174
Closed Access | Times Cited: 41
An Ecosystem for Digital Reticular Chemistry
Kevin Maik Jablonka, Andrew Rosen, Aditi S. Krishnapriyan, et al.
ACS Central Science (2023) Vol. 9, Iss. 4, pp. 563-581
Open Access | Times Cited: 36
A database of ultrastable MOFs reassembled from stable fragments with machine learning models
Aditya Nandy, Shuwen Yue, Changhwan Oh, et al.
Matter (2023) Vol. 6, Iss. 5, pp. 1585-1603
Open Access | Times Cited: 36
Synthesis and modification methods of metal-organic frameworks and their application in modification of polymeric ultrafiltration membranes: A review
Mona Dehghankar, Romina HMTShirazi, Toraj Mohammadi, et al.
Journal of environmental chemical engineering (2023) Vol. 11, Iss. 3, pp. 109954-109954
Closed Access | Times Cited: 34
Exploring the Structural, Dynamic, and Functional Properties of Metal‐Organic Frameworks through Molecular Modeling
Filip Formalik, Kaihang Shi, Faramarz Joodaki, et al.
Advanced Functional Materials (2023) Vol. 34, Iss. 43
Open Access | Times Cited: 33
On the shoulders of high-throughput computational screening and machine learning: Design and discovery of MOFs for H2 storage and purification
Çiğdem Altıntaş, Seda Keskın
Materials Today Energy (2023) Vol. 38, pp. 101426-101426
Open Access | Times Cited: 24
CRAFTED: An exploratory database of simulated adsorption isotherms of metal-organic frameworks
Felipe Lopes Oliveira, Conor Cleeton, Rodrigo Neumann Barros Ferreira, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 23
Computational and Machine Learning Methods for CO2 Capture Using Metal–Organic Frameworks
Hossein Mashhadimoslem, Mohammad Ali Abdol, Peyman Karimi, et al.
ACS Nano (2024) Vol. 18, Iss. 35, pp. 23842-23875
Closed Access | Times Cited: 16
Computational Simulations of Metal–Organic Frameworks to Enhance Adsorption Applications
Hilal Daglar, Hasan Can Gülbalkan, Gokhan Onder Aksu, et al.
Advanced Materials (2024)
Open Access | Times Cited: 15
Informative Training Data for Efficient Property Prediction in Metal–Organic Frameworks by Active Learning
Ashna Jose, Emilie DEVIJVER, N. Jakse, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 9, pp. 6134-6144
Closed Access | Times Cited: 12
Accelerating In Silico Discovery of Metal–Organic Frameworks for Ethane/Ethylene and Propane/Propylene Separation: A Synergistic Approach Integrating Molecular Simulation, Machine Learning, and Active Learning
Varad Daoo, Jayant K. Singh
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 6, pp. 6971-6987
Closed Access | Times Cited: 10
Effect of genes on rheological properties of asphalt binders
Guanyu Li, Xueting Wang, Suining Zheng, et al.
Fuel (2024) Vol. 365, pp. 131324-131324
Closed Access | Times Cited: 10
Trace SO2 capture within the engineered pore space using a highly stable SnF62−-pillared MOF
Weiwei Li, Can Cheng, Guanqun Gao, et al.
Materials Horizons (2024) Vol. 11, Iss. 8, pp. 1889-1898
Closed Access | Times Cited: 9
Machine Learning-Assisted High-Throughput Screening of MOFs for Efficient Adsorption and Separation of CF4/N2
Hong Xu, Liberty L. Mguni, Yali Yao, et al.
Journal of Cleaner Production (2024) Vol. 461, pp. 142634-142634
Open Access | Times Cited: 9
Machine Learning Descriptors for CO2 Capture Materials
Ibrahim Orhan, Yuankai Zhao, Ravichandar Babarao, et al.
Molecules (2025) Vol. 30, Iss. 3, pp. 650-650
Open Access | Times Cited: 1
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