纳滤
冠醚
膜
化学
乙醚
牙冠(牙科)
色谱法
分析化学(期刊)
材料科学
有机化学
离子
生物化学
复合材料
作者
Qingji Wang,Yilin Wang,Dan Wang,Xueying Yang,Ying Tang,Mingna Feng,Mingxia Wang,Xuemin Li,Feng Yan
出处
期刊:Langmuir
[American Chemical Society]
日期:2025-08-25
卷期号:41 (35): 23772-23787
标识
DOI:10.1021/acs.langmuir.5c03056
摘要
Nanofiltration (NF) stands as a pivotal method for lithium resource recovery. Nonetheless, traditional NF membranes predominantly rely on size exclusion and the Donnan effect, necessitating elevated operating pressures and encountering substantial hurdles in terms of ion selectivity for lithium ions. Inspired by the host-guest recognition of crown ethers toward alkali metal ions, we prepared a crown ether-functionalized loose NF membrane (CE-LNF) via interfacial polymerization of diamino-dibenzo-14-crown-4 (DAB14C4) and trimesoyl chloride on a chloromethylated polysulfone substrate. The preparation conditions of the CE-LNF membranes were systematically optimized. Results revealed that the polyamide (PA) layer structure could be precisely tuned by changing the solvent and concentration of DAB14C4. The diffusion dialysis process with low energy consumption was applied in the Mg2+/Li+ separation experiment. Interestingly, the CE-LNF membrane achieved a unique "Li+ repulsion-Mg2+ permeation" result owing to the efficient host-guest recognition of Li+ by DAB14C4 on the PA layer. During the diffusion process, the transmembrane flux of Mg2+ (0.5 mol·m-2·h-1) surpassed that of Li+ (0.01 mol·m-2·h-1) by 50-fold, leading to a significant reduction in the Mg2+/Li+ ratio in the feed (from 19.5:1 to 5.2:1) and generating a Mg2+-enriched permeate. This work proposes a novel strategy for Mg2+/Li+ separation, where CE-LNF-based continuous diffusion dialysis serves as an energy-efficient, nonpressure-driven pretreatment for high Mg2+/Li+ ratio brines. The process not only produces high-purity Mg2+ solutions but also facilitates subsequent Li+ recovery via secondary CE-LNF diffusion or conventional extraction methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI