A generalized method for constructing hypothetical nanoporous materials of any net topology from graph theory

Cited by (156)

Items 101–156 of 156

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6. Hierarchical Computational Screening of Quantum Metal–Organic Framework Database to Identify Metal–Organic Frameworks for Volatile Organic-Compound Capture from Air
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9. Discovering robust metal-organic frameworks with open copper sites for precombustion CO2 capture: Data-efficient exploration and exploitation by active learning
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10. Machine‐Learning Prediction of Metal–Organic Framework Guest Accessibility from Linker and Metal Chemistry
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11. Database Design for Double-Linker Metal–Organic Frameworks
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12. Predictive models on potential energies of zeolite ZK-5 using bond weighted information entropy measures
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13. Microporous mixed-metal mixed-ligand metal organic framework for selective CO 2 capture
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14. Improving materials property predictions for graph neural networks with minimal feature engineering *
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15. Computer-aided metal–organic framework screening and design approaches toward efficient carbon capture processes
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16. Tuning Pore Chemistry of Metal–Organic Frameworks Using Anionic Pillars for Humid-Tolerant CO 2 Capture
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17. Building Unit Extractor for Metal–Organic Frameworks
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18. Unveiling the synthesis patterns of nanomaterials: a text mining and meta-analysis approach with ZIF-8 as a case study
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19. Machine learning guided tuning charge distribution by composition in MOFs for oxygen evolution reaction
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20. Machine Learning Predictions of Methane Storage in MOFs: Diverse Materials, Multiple Operating Conditions, and Reverse Models
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21. Extracting Metal‐Organic Frameworks Data from the Cambridge Structural Database
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22. A human-in-the-loop approach for visual clustering of overlapping materials science data
    Satyanarayana Bonakala, Michael J Marie Aupetit, Halima Bensmail, Fedwa El‐Mellouhi · 2024 · Digital Discovery
23. Leveraging Cross-Diversity Machine Learning to Unveil Metal–Organic Frameworks with Open Copper Sites for Biogas Upgrading
    Xiaoyu Wu, Rui Zheng, Jianwen Jiang · 2025 · Journal of Chemical Theory and Computation
24. Inverse Design of Metal‐Organic Frameworks for CH 4 /N 2 Separation Enabled by Coupled Machine Learning and Genetic Algorithms
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25. High-Throughput Virtual Screening of Biometal–Organic Frameworks for O2/N2 Separation
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26. Predicting the Thermodynamic Limits of Metal–Organic Framework Metastability
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27. Accelerating Discovery of Mechanically Stable Metal–Organic Frameworks for Vinylidene Fluoride Storage by Active Learning
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28. Symmetry is the Key to the Design of Reticular Frameworks
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29. Quantum Computing Based Design of Multivariate Porous Materials
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30. Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery
    Guojing Cong, Talia Ben-Naim, Victor Fung, Anshul Gupta, Rodrigo Neumann Barros Ferreira, Mathias Bernhard Steiner · 2022 · IEEE ... International Conference on Data Mining workshops
31. Structural analysis of bond information entropy and HOMO-LUMO gap in CLO and KFI zeolites
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32. Persistent homology advances interpretable machine learning for nanoporous materials.
    Aditi S. Krishnapriyan, Joseph H. Montoya, Jens S. Hummelshøj, Dmitriy Morozov · 2020 · arXiv (Cornell University)
33. An ecosystem for digital reticular chemistry
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34. Machine Learning‐Aided Discovery of Nanoporous Materials for Energy‐ and Environmental‐Related Applications
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35. The transformative role of machine learning in advancing MOF membranes for gas separations
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36. Machine Learning for Predicting Gas Adsorption Capacities of Metal Organic Framework
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37. Fragment to framework: automatic fragmentation of covalent organic frameworks into building blocks for band gap analysis
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38. Integrating crystallographic and computational approaches to carbon-capture materials for the mitigation of climate change
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39. A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
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40. Digital design and discovery of biological metal–organic frameworks for gas signaling
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41. Identifying phase transitions in zeolitic imidazolate frameworks: microscopic insight from molecular simulations
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42. Toward comprehensive exploration of the physisorption space in porous pseudomaterials using an iterative mutation search algorithm
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43. Perfect quantum state transfer on generalized honeycomb nanotori
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44. Predicting Hydrogen Storage in Mofs via Machine Learning
    Alauddin Ahmed, Donald J. Siegel · 2020 · SSRN Electronic Journal
45. Machine learning prediction of open metal sites in metal-organic framework catalysts
    Huixuan Guo, Jiahao Ma, Yueshan Zhong, Yuhui Yin, Mingcan Chen · 2022 · ChemRxiv
46. Design and Screening of Hypothetical Charged Metal-organic Frameworks for Carbon Dioxide Capture
    Jason Wai-Ho Lo · 2016 · uO Research (University of Ottawa)
47. Diversifying databases of metal organic frameworks for high-throughput computational screening
    Sauradeep Majumdar, Seyed Mohamad Moosavi, Kevin Maik Jablonka, Daniele Ongari, Berend Smit · 2021
48. Understanding MOF nucleation from solution with Evolving Graphs
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49. Data-Driven Mapping of Inorganic Chemical Space for the Design of Transition Metal Complexes and Metal-Organic Frameworks
    Jon Paul Janet · 2022 · ACS symposium series
50. A divide-and-conquer solution for the closest-pair problem in computer-aided MOF assembly
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51. Inverse Design of Metal–Organic Polyhedra through Molecular Fragmentation and Evolutionary Optimisation
    Patrick W.V. Butler, Simon D. Rihm, Sebastian Mosbach, Jethro Akroyd, Markus Kraft · 2026 · Journal of Chemical Information and Modeling
52. Hunting Structural Demons in Digital Reticular Chemistry: Lessons From Metal‐Organic Frameworks
    Yongchul G. Chung, Myoung Soo Lah · 2026 · Israel Journal of Chemistry
53. Leveraging general molecular fragments to expand the design space of metal–organic polyhedra
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54. Machine learning-accelerated discovery of metal–organic frameworks for storage and delivery of anticancer drug molecules
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55. From Graphs to Reactions: Decoding the Oxidizing Strength of KMnO_4 and K_2Cr_2O_7
    Shilpa Patil, Prashanth B., Sushma T C · 2026 · Boletim da Sociedade Paranaense de Matemática
56. Materials screening and design for carbon capture technologies
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