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RESEARCH PAPER · Journal of Materials Chemistry A · 2024

Comprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classifications

Yutong Liu, Yawen Dong, Hua Wu

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Comprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classificationsOriginalAI-driven advances in metal–organic frameworks: from data to design and applications47Symmetry-informed graph neural networks for carbon dioxide isotherm and adsorption prediction in aluminum-substituted zeolites3Highly Conductive Ni‐Co Based Bimetallic Metal‐Organic Framework and Coordinated Water Induced Selective Adsorption and Separation of Trace Amount of Methyl Blue from Aqueous System0Rational design of two-dimensional nanosheets membranes for lithium extraction from brine: Recent progress and future opportunities12Identification of Metal–Organic Frameworks for near Practical Energy Limit CO 2 Capture from Wet Flue Gases: An Integrated Atomistic and Process Simulation Screening of Experimental MOFs15Transfer learning-based modeling of synthesis-particle size relationships in metal-organic frameworks3Design Guidelines for MOFs in CF4/NF3 Separation Based on Feature Selection with Stacking Ensemble Model0Incremental learning with heterogeneous data for morphology prediction in metal-organic frameworks1Hydrophobic metal–organic frameworks and membranes for enhanced carbon capture14TBHubbard: tight-binding and extended Hubbard model dataset for metal-organic frameworks1Intelligent screening of porous materials: A review of active-learning approaches in MOF research6Manufacturing strategies for metal organic framework-based membrane electrode assemblies in electrolyzers10Application of multi-task learning in analysing the methane working capacity of metal–organic frameworks1Combining chemical, geometric, and novel topological features to develop generalizable machine learning models for predicting mechanically stable MOFs2Economic impacts of green chemistry innovations0Tri-responsive multifunctional metal–organic framework (MuF-MOF) nanozyme-based sensors12A robust multiple linear regression model for accurate density prediction of metal-containing energetic complexes and energetic metal-organic frameworks to enhance detonation performance forecasting0Donor-acceptor type metal-organic frameworks: Synthesis, unique advantages, and applications12Machine Learning Assisted Fluorescent Sensor Array for Sensing Applications11Reaction mechanisms and rational design of MOF catalysts: insights from microscopic simulations2A review of machine learning applications in PFAS environmental behavior and risk management0Data-driven explainable artificial intelligence models for predicting CO2 uptake in metal–organic frameworks1Universal and zero-shot machine learning prediction of gas diffusivity in metal–organic frameworks using XGBoost and FT-transformer0MOF‐Based Materials for Alkaline Hydrogen Evolution Reaction: From Mechanism Foundation to Catalyst Design0Reticular framework architectures for coagulation-flocculation and colloidal separation: Mechanistic insights, structure-performance correlation, and AI-guided discovery0Machine learning-guided design of engineered metal-organic frameworks for sustainable hydrogen storage and production0

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  2. Symmetry-informed graph neural networks for carbon dioxide isotherm and adsorption prediction in aluminum-substituted zeolites

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    Marko Petković, José Manuel Vicent‐Luna, Elīza Beate Dinne, Vlado Menkovski, Sofı́a Calero

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  3. Highly Conductive Ni‐Co Based Bimetallic Metal‐Organic Framework and Coordinated Water Induced Selective Adsorption and Separation of Trace Amount of Methyl Blue from Aqueous System

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  4. Rational design of two-dimensional nanosheets membranes for lithium extraction from brine: Recent progress and future opportunities

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    Yingjie Xia, Ke Liu, Yuan Xiang, Xi Chen, Kun Zhou, Ying Zeng, Shouliang Yi, Guangyong Zeng

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  5. Identification of Metal–Organic Frameworks for near Practical Energy Limit CO 2 Capture from Wet Flue Gases: An Integrated Atomistic and Process Simulation Screening of Experimental MOFs

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    Ohmin Kwon, Marco Gibaldi, Kasturi Nagesh Pai, Arvind Rajendran, Tom K. Woo

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  6. Transfer learning-based modeling of synthesis-particle size relationships in metal-organic frameworks

    Nano Trends · 2025-09-25

    Yuncheng Du

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  7. Design Guidelines for MOFs in CF4/NF3 Separation Based on Feature Selection with Stacking Ensemble Model

    The Journal of Physical Chemistry C · 2025-10-07

    Minhua Zhang, Tong Wu, Kai Song, Yifei Chen, Hao Gong

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  8. Incremental learning with heterogeneous data for morphology prediction in metal-organic frameworks

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  9. Hydrophobic metal–organic frameworks and membranes for enhanced carbon capture

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  10. TBHubbard: tight-binding and extended Hubbard model dataset for metal-organic frameworks

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  11. Intelligent screening of porous materials: A review of active-learning approaches in MOF research

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  12. Manufacturing strategies for metal organic framework-based membrane electrode assemblies in electrolyzers

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    Minaj M. Faras, Satyajeet S. Patil, Suhyeon Lee, Choong Hoo Lee, Yunseong Ji, Dae Woo Kim

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  13. Application of multi-task learning in analysing the methane working capacity of metal–organic frameworks

    Journal of Materials Chemistry A · 2026-01-01

    Junhui Kou, Tianle Liu, Guosheng Jiang, Guokun Yang, Zerang Li, Xiaoyang Ni, Hao Liu

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  14. Combining chemical, geometric, and novel topological features to develop generalizable machine learning models for predicting mechanically stable MOFs

    Journal of Materials Chemistry A · 2026-01-01

    Akash Ball, Changhwan Oh, Gozel Dovranova, Heather J. Kulik

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  15. Economic impacts of green chemistry innovations

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    Abu Bakar, Rehana Ishaq, Abrar Ashraf, Adeena Fatima

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  16. Tri-responsive multifunctional metal–organic framework (MuF-MOF) nanozyme-based sensors

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  17. A robust multiple linear regression model for accurate density prediction of metal-containing energetic complexes and energetic metal-organic frameworks to enhance detonation performance forecasting

    Defence Technology · 2026-01-28

    Mohammad Hossein Keshavarz, Nasser Hassanzadeh, Zeinab Dalirandeh, Mohammad Jafari

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  18. Donor-acceptor type metal-organic frameworks: Synthesis, unique advantages, and applications

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  19. Machine Learning Assisted Fluorescent Sensor Array for Sensing Applications

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  20. Reaction mechanisms and rational design of MOF catalysts: insights from microscopic simulations

    Coordination Chemistry Reviews · 2026-03-09

    Zuoshuai Xi, Xinmeng Xu, Jin Lin, Zhimeng Liu, Wenting Ding, Shuanglong Li, Yuqiao Su, Yujie Guo, Hongyi Gao, Ge Wang

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  21. A review of machine learning applications in PFAS environmental behavior and risk management

    Journal of environmental chemical engineering · 2026-04-04

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  22. Data-driven explainable artificial intelligence models for predicting CO2 uptake in metal–organic frameworks

    Environmental Science and Pollution Research · 2026-04-06

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  23. Universal and zero-shot machine learning prediction of gas diffusivity in metal–organic frameworks using XGBoost and FT-transformer

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  24. MOF‐Based Materials for Alkaline Hydrogen Evolution Reaction: From Mechanism Foundation to Catalyst Design

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  25. Reticular framework architectures for coagulation-flocculation and colloidal separation: Mechanistic insights, structure-performance correlation, and AI-guided discovery

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  26. Machine learning-guided design of engineered metal-organic frameworks for sustainable hydrogen storage and production

    International Journal of Hydrogen Energy · 2026-09-18

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