ArticleChemistry of materials : a publication of the American Chemical Society2021
Visualization and Quantification of Geometric Diversity in Metal-Organic Frameworks.
Article in Chemistry of materials : a publication of the American Chemical Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The Application of Metal-Organic Frameworks as Drug Delivery Systems: From the Perspective of Molecular Dynamics Simulations.MedComm · 2026Review
- Surface-Enhanced Raman Spectroscopy for Biomedical Applications: Recent Advances and Future Challenges.ACS applied materials & interfaces · 2025Review
- Unexpected reversal of reactivity in organic functionalities when immobilized together in a metal-organic framework (MOF).Molecular systems design & engineering · 2024Article
- Coarse-grainedChemical communications (Cambridge, England) · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With ever-growing numbers of metal-organic framework (MOF) materials being reported, new computational approaches are required for a quantitative understanding of structure-property correlations in MOFs. Here, we show how structural coarse-graining and embedding ("unsupervised learning") schemes can together give new insights into the geometric diversity of MOF structures. Based on a curated data set of 1262 reported experimental structures, we automatically generate coarse-grained and rescaled representations which we couple to a kernel-based similarity metric and to widely used embedding schemes. This approach allows us to visualize the breadth of geometric diversity within individual topologies and to quantify the distributions of local and global similarities across the structural space of MOFs. The methodology is implemented in an openly available Python package and is expected to be useful in future high-throughput studies.
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Registered trials
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