ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2025
Facilitating Screening of MOFs for Mixed Matrix Membranes Using Machine Learning and the Maxwell Model.
Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Discovering metal-organic framework/polymer mixed-matrix membranes via machine learning for COCommunications materials · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metal organic framework (MOF)-based mixed-matrix membranes (MMMs), which embed MOF particles in polymer matrices, combine the advantages of polymeric and inorganic membranes. Multiple previous studies have used the Maxwell model together with molecular simulations and machine learning (ML) to predict the performance of MOF/polymer MMMs. However, the assumption of rigid MOF frameworks in molecular simulations limited the accuracy of the data used in the predictions, particularly in predicting molecular diffusivities. We developed a novel workflow integrating ML models with consideration of MOF flexibility to predict the permeability and selectivity of 131,722 MMMs for CO
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Registered trials
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