Dynamic Water-Driven Competitive Strategy Enables Selective and Easily Regenerable C2H2/C2H4 Separation on Gallate-Based Metal–Organic Framework Nanostructures
Source abstract
Abstract
Efficient separation of C 2 hydrocarbons remains a significant challenge in the petrochemical industry. Metal–organic framework nanostructures, with their tunable pore environments and exposed nanoscale metal sites, have shown great promise in enhancing π-electron gas separation. However, balancing molecular adsorption strength with desorption energy consumption continues to be a major challenge. In our previous work, we discovered that the gallate-based metal–organic framework nanostructure compounds exhibit selective adsorption of C 2 H 4 through π-electron-induced local reconstruction. Building on this, we have proposed a ″dynamic water molecule-driven competition″ strategy in this study, in which the introduction of water molecules enables dynamic regulation of gas binding at the active metal sites. By leveraging the differential responses of M-gallate (Co, Ni, Mg) to various gas molecules, we achieved high-efficiency C 2 separation and low-energy regeneration under dynamic adsorption–desorption competition modulated by water molecules. Experimental results, supported by DFT simulations, reveal that water molecules act as molecular modulators, reversibly competing with π-electron gases for binding near metal centers. This nanostructure-level competition mechanism significantly enhances gas separation performance and material recyclability. The ″dynamic water molecule-driven competition″ strategy proposed in this study not only opens up directions for the design of π-bonded gas separation materials but also provides an important technical reference for greening and decarbonizing industrial adsorption processes.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Metal-Organic Frameworks: Synthesis and Applications · Nanomaterials for catalytic reactions · Covalent Organic Framework Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Chemical Engineering and Technology
Tianjin University
Department of Chemistry, School of Science
Funding
Tianjin University · Grant YLU-DNL Fund
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