Enhancing Membrane Materials for Efficient Li Recycling and Recovery
Abstract: Rapid uptake of lithium‐centric technology, e.g., electric vehicles and large‐scale energy storage, is increasing the demand for efficient technologies for lithium extraction from aqueous sources. Among various lithium‐extraction technologies, membrane processes hold great promise due to energy efficiency and flexible operation in a continuous process with potential commercial viability. However, membrane separators face challenges such as the extraction efficiency due to the limited selectivity toward lithium relative to other species. Low selectivity can be ascribed to the uncontrollable selective channels and inefficient exclusion functions. However, recent selectivity enhancements for other membrane applications, such as in gas separation and energy storage, suggest that this may also be possible for lithium extraction. This review article focuses on the innovations in the membrane chemistries based on rational design following separation principles and unveiling the theories behind enhanced selectivity. Furthermore, recent progress in membrane‐based lithium extraction technologies is summarized with the emphasis on inorganic, organic, and composite materials. The challenges and opportunities for developing the next generation of selective membranes for lithium recovery are also pointed out.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Enhancing Membrane Materials for Efficient Li Recycling and Recovery ; day:15 ; month:12 ; year:2024 ; extent:26
Advanced materials ; (15.12.2024) (gesamt 26)
- Creator
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Tian, Xingpeng
Ye, Chunchun
Zhang, Liyuan
Sugumar, Manoj K.
Zhao, Yan
McKeown, Neil B.
Margadonna, Serena
Tan, Rui
- DOI
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10.1002/adma.202402335
- URN
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urn:nbn:de:101:1-2412161311312.757219976448
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:25 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Tian, Xingpeng
- Ye, Chunchun
- Zhang, Liyuan
- Sugumar, Manoj K.
- Zhao, Yan
- McKeown, Neil B.
- Margadonna, Serena
- Tan, Rui