Synthesis and Characterization of a New Polymer-Based Supramolecular Recognition Material and its Adsorption for Cesium

Synthesis and Characterization of a New Polymer-Based Supramolecular Recognition Material and its Adsorption for Cesium
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DOI:
10.1080/07366299.2011.581076
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发表时间:
2012-01
影响因子:
2
通讯作者:
Chengliang Xiao;A. Zhang;Z. Chai
Chengliang Xiao;A. Zhang;Z. Chai
中科院分区:
化学3区
文献类型:
--
作者:
Chengliang Xiao;A. Zhang;Z. Chai

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合成了一种新型大孔聚合物基25,27-双(异丙氧基)calix[4]arene-26,28-crown-6 (BiPCalix[4]C6)超分子识别材料BiPCalix[4]C6/XAD-7。它是通过真空浸渍并将 BiPCalix[4]C6 固定到大孔 XAD-7 颗粒的孔中来进行的。分别使用 SEM、BET、TG-DSC、FT-IR 和 XRD 对其组成和结构进行表征。研究了 BiPCalix[4]C6/XAD-7 材料对高活性液体废物 (HLW) 中的一些典型金属(如 Ru(III)、Mo(VI)、K(I)、Rb(I)、Cs(I)、Sr(II)、Ba(II)、La(III) 和 Y(III) 的吸附。评估了 HNO3 浓度和接触时间对测试金属吸附的影响。结果发现,在最佳浓度 4.0 M HNO3 下,BiPCalix[4]C6/XAD-7 对 Cs(I) 表现出优异的吸附能力和高选择性,而除 Rb(I) 外,其他测试金属表现出较弱或几乎没有吸附。这表明基于聚合物的超分子识别材料 BiPCalix[4]C6/XAD-7 在从 HLW 中分离 Cs(I) 方面的应用前景广阔。
A novel macroporous polymer-based 25,27-bis(iso-propyloxy)calix[4]arene-26,28-crown-6 (BiPCalix[4]C6) supramolecular recognition material, BiPCalix[4]C6/XAD-7, was synthesized. It was performed by vacuum impregnation and immobilization of BiPCalix[4]C6 into the pores of the macroporous XAD-7 particles. The composition and structure were characterized using SEM, BET, TG-DSC, FT-IR, and XRD, respectively. The adsorption of some typical metals contained in highly active liquid waste (HLW) such as Ru(III), Mo(VI), K(I), Rb(I), Cs(I), Sr(II), Ba(II), La(III), and Y(III) onto the BiPCalix[4]C6/XAD-7 materials was investigated. The effects of the HNO3 concentration and contact time on the adsorption of the tested metals were evaluated. It was found that at the optimum concentration of 4.0 M HNO3, BiPCalix[4]C6/XAD-7 exhibited excellent adsorption ability and high selectivity for Cs(I) over all the other tested metals, which showed weak or almost no adsorption except Rb(I). It demonstrated that application of the polymer-based supramolecular recognition material, BiPCalix[4]C6/XAD-7, in partitioning of Cs(I) from HLW is promising.