ArticleScientific reports2025
Molecular dynamics simulations reveal efficient heavy metal ion removal by two-dimensional Cu-THQ metal-organic framework membrane.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Computational Study of Graphene Quantum Dots (GQDs) Functionalized with Thiol and Amino Groups for the Selective Detection of Heavy Metals in Wastewater.Molecules (Basel, Switzerland) · 2025Article
- Structural and functional insights into metal coordination and substrate recognition of Akkermansia muciniphila sialidase Amuc_1547.Molecular biomedicine · 2025Article
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6 authors.
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Abstract
Two-dimensional (2D) metal-organic frameworks (MOFs) have been extensively utilized across various research areas. However, the application of 2D MOF-based membranes for the removal of heavy metal ions remains largely unexplored, despite their potential as suitable candidates due to their inherent porosity. In this study, we employed molecular dynamics (MD) simulations to investigate the capacity of a typical 2D MOF, Cu-THQ, for the separation of heavy metal ions, including Cd²⁺, Cu²⁺, Hg²⁺, and Pb²⁺. Our MD results demonstrate that single-layered Cu-THQ MOF membranes exhibit excellent performance in heavy metal ion removal, with nearly 100% ion rejection while also allowing high water permeability. Free energy calculations confirm that water transport through the Cu-THQ membrane is energetically more favorable compared to the transport of heavy metal ions. Further simulations of multilayered Cu-THQ membranes indicate that increasing the number of Cu-THQ MOF layers hinders water molecule transport, resulting in a reduction in water permeability due to a more widespread adsorption, that is primarily driven by electrostatic interactions within the membrane pores. Therefore, our simulations not only identify a promising MOF membrane candidate for efficient heavy metal ion removal but also suggest an optimal MOF construction scheme, which provide beneficial information for future applications in the sieving field.
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