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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:

Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal–Organic Frameworks
Aditya Nandy, Chenru Duan, Heather J. Kulik
Journal of the American Chemical Society (2021) Vol. 143, Iss. 42, pp. 17535-17547
Open Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis
Zhiling Zheng, Oufan Zhang, Christian Borgs, et al.
Journal of the American Chemical Society (2023) Vol. 145, Iss. 32, pp. 18048-18062
Open Access | Times Cited: 237
MOF‐Based Chemiresistive Gas Sensors: Toward New Functionalities
Young‐Moo Jo, Yong Kun Jo, Jong‐Heun Lee, et al.
Advanced Materials (2022) Vol. 35, Iss. 43
Closed Access | Times Cited: 234
Bridging the complexity gap in computational heterogeneous catalysis with machine learning
Tianyou Mou, Hemanth Somarajan Pillai, Siwen Wang, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 122-136
Closed Access | Times Cited: 138
Recent advances in computational modeling of MOFs: From molecular simulations to machine learning
Hakan Demir, Hilal Daglar, Hasan Can Gülbalkan, et al.
Coordination Chemistry Reviews (2023) Vol. 484, pp. 215112-215112
Open Access | Times Cited: 121
Recent progress, mechanisms, and perspectives for crystal and interface chemistry applying to the Zn metal anodes in aqueous zinc‐ion batteries
Zhengchunyu Zhang, Baojuan Xi, Xiaojian Ma, et al.
SusMat (2022) Vol. 2, Iss. 2, pp. 114-141
Open Access | Times Cited: 111
A data-science approach to predict the heat capacity of nanoporous materials
Seyed Mohamad Moosavi, Balázs Álmos Novotny, Daniele Ongari, et al.
Nature Materials (2022) Vol. 21, Iss. 12, pp. 1419-1425
Open Access | Times Cited: 90
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks
Yeonghun Kang, Hyunsoo Park, Berend Smit, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 3, pp. 309-318
Open Access | Times Cited: 87
MOFormer: Self-Supervised Transformer Model for Metal–Organic Framework Property Prediction
Zhonglin Cao, Rishikesh Magar, Yuyang Wang, et al.
Journal of the American Chemical Society (2023) Vol. 145, Iss. 5, pp. 2958-2967
Open Access | Times Cited: 82
MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks
Aditya Nandy, Gianmarco Terrones, N. Arunachalam, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 78
A GPT‐4 Reticular Chemist for Guiding MOF Discovery**
Zhiling Zheng, Zichao Rong, Nakul Rampal, et al.
Angewandte Chemie International Edition (2023) Vol. 62, Iss. 46
Open Access | Times Cited: 78
Covalent organic frameworks for CO2 capture: from laboratory curiosity to industry implementation
He Li, Akhil Dilipkumar, Saifudin Abubakar, et al.
Chemical Society Reviews (2023) Vol. 52, Iss. 18, pp. 6294-6329
Closed Access | Times Cited: 76
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
Organic pollutants removal from aqueous solutions using metal-organic frameworks (MOFs) as adsorbents: A review
Lixin Li, Jiazhen Han, Xiaohui Huang, et al.
Journal of environmental chemical engineering (2023) Vol. 11, Iss. 6, pp. 111217-111217
Closed Access | Times Cited: 63
Machine learning accelerates the investigation of targeted MOFs: Performance prediction, rational design and intelligent synthesis
Jing Lin, Zhimeng Liu, Yujie Guo, et al.
Nano Today (2023) Vol. 49, pp. 101802-101802
Closed Access | Times Cited: 47
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
Building robust metal-organic frameworks with premade ligands
Yunlong Hou, Caoyu Yang, Zhongjie Yang, et al.
Coordination Chemistry Reviews (2024) Vol. 505, pp. 215690-215690
Closed 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
Image and data mining in reticular chemistry powered by GPT-4V
Zhiling Zheng, Zhiguo He, Omar Khattab, et al.
Digital Discovery (2024) Vol. 3, Iss. 3, pp. 491-501
Open Access | Times Cited: 18
Metal–Organic Framework Stability in Water and Harsh Environments from Data-Driven Models Trained on the Diverse WS24 Data Set
Gianmarco Terrones, Shih-Peng Huang, Matthew P. Rivera, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 29, pp. 20333-20348
Closed Access | Times Cited: 18
Large language models for reticular chemistry
Zhiling Zheng, Nakul Rampal, Theo Jaffrelot Inizan, et al.
Nature Reviews Materials (2025)
Closed Access | Times Cited: 4
MOSAEC-DB: a comprehensive database of experimental metal–organic frameworks with verified chemical accuracy suitable for molecular simulations
Marco Gibaldi, Anna Kapeliukha, Andrew J. P. White, et al.
Chemical Science (2025)
Open Access | Times Cited: 3
Application of machine learning in adsorption energy storage using metal organic frameworks: A review
Nokubonga P. Makhanya, Michael Kumi, Charles Mbohwa, et al.
Journal of Energy Storage (2025) Vol. 111, pp. 115363-115363
Closed Access | Times Cited: 2
Porous Organic Framework-Based Materials (MOFs, COFs and HOFs) for Lithium-/Sodium-/Potassium-/Zinc-/Aluminum-/Calcium-Ion Batteries: A Review
Hui Zheng, Wei Yan, Jiujun Zhang
Electrochemical Energy Reviews (2025) Vol. 8, Iss. 1
Closed Access | Times Cited: 2
Conductive Metal–Organic Frameworks and Their Electrocatalysis Applications
Shuhui Tao, John Wang, Jie Zhang
ACS Nano (2025)
Closed Access | Times Cited: 2
Unlocking potential and challenges of MOFs and COFs based energy materials for CO2 reduction and H2 production
Iqra Sadiq, Syed Asim Ali, Saman Shaheen, et al.
International Journal of Hydrogen Energy (2025) Vol. 120, pp. 146-180
Closed Access | Times Cited: 2
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