Suppr超能文献

大孔硅基吸附剂萃取色层法分离硝酸溶液中的钇和锶及其吸附行为。

Adsorption and separation behavior of yttrium and strontium in nitric acid solution by extraction chromatography using a macroporous silica-based adsorbent.

机构信息

Cyclotron and Radioisotope Center, Tohoku University, Aoba 6-3, Aramaki, Sendai, 980-8578, Japan.

出版信息

J Chromatogr A. 2012 Nov 9;1263:28-33. doi: 10.1016/j.chroma.2012.09.036. Epub 2012 Sep 16.

Abstract

To separate (90)Y from the fission product (90)Sr-(90)Y group, a silica-based TODGA/SiO(2)-P adsorbent was prepared by impregnating N,N,N',N'-tetraoctyl-3-oxapentane-1,5-diamide (TODGA) extractant into the macroporous SiO(2)-P support with a mean diameter of 60 μm. The adsorption behavior of Sr(II) and Y(III) onto TODGA/SiO(2)-P adsorbent from HNO(3) solution and their mutual separation were investigated. Under the experimental conditions, this adsorbent showed high adsorption affinity to Y(III) and weak adsorption to Sr(II). It was found that the adsorption process of Y(III) could be expressed by both of Langmuir monomolecular layer adsorption mode and the pseudo-second order model. From the results of stability experiments, it became clear that TODGA/SiO(2)-P adsorbent is stable in 3M HNO(3) solution for 1 month contact time at 298 K. Using a column packed with TODGA/SiO(2)-P adsorbent, Sr(II) and Y(III) were eluted by distilled water and diethylenetriamine pentaacetic acid (DTPA) solution, respectively. The separation of Y(III) from Sr(II)-Y(III) group was achieved successfully.

摘要

为了将 (90)Y 与裂变产物 (90)Sr-(90)Y 组分离,通过将 N,N,N',N'-四辛基-3-氧杂戊烷-1,5-二酰胺(TODGA)萃取剂浸渍到大孔 SiO(2)-P 载体(平均直径为 60μm)中,制备了一种基于二氧化硅的 TODGA/SiO(2)-P 吸附剂。研究了 Sr(II)和 Y(III)从 HNO(3)溶液中通过 TODGA/SiO(2)-P 吸附剂的吸附行为及其相互分离。在实验条件下,该吸附剂对 Y(III)表现出高吸附亲和力,对 Sr(II)的吸附较弱。结果表明,Y(III)的吸附过程可以用 Langmuir 单分子层吸附模型和拟二级模型来表示。从稳定性实验的结果可以清楚地看出,TODGA/SiO(2)-P 吸附剂在 298K 下于 3M HNO(3)溶液中接触 1 个月是稳定的。使用填充有 TODGA/SiO(2)-P 吸附剂的柱子,分别用水和二乙三胺五乙酸(DTPA)溶液洗脱 Sr(II)和 Y(III)。成功地实现了 Y(III)从 Sr(II)-Y(III)组的分离。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验