five

The behaviour of tributyl phosphate in an organic diluent

收藏
DataCite Commons2020-09-04 更新2024-07-25 收录
下载链接:
https://tandf.figshare.com/articles/dataset/The_behaviour_of_tributyl_phosphate_in_an_organic_diluent/1040393/3
下载链接
链接失效反馈
官方服务:
资源简介:
Tributyl phosphate (TBP) is used as a complexing agent in the Plutonium Uranium Extraction (PUREX) liquid–liquid phase extraction process for recovering uranium and plutonium from spent nuclear reactor fuel. Here, we address the molecular and microstructure of the organic phases involved in the extraction process, using molecular dynamics to show that when TBP is mixed with a paraffinic diluent, the TBP self-assembles into a bi-continuous phase. The underlying self-association of TBP is driven by intermolecular interaction between its polar groups, resulting in butyl moieties radiating out into the organic solvent. Simulation predicts a TBP diffusion constant that is anomalously low compared to what might normally be expected for its size; experimental nuclear magnetic resonance (NMR) studies also indicate an extremely low diffusion constant, consistent with a molecular aggregation model. Simulation of TBP at an oil/water interface shows the formation of a bilayer system at low TBP concentrations. At higher concentrations, a bulk bi-continuous structure is observed linking to this surface bilayer. We suggest that this structure may be intimately connected with the surprisingly rapid kinetics of the interfacial mass transport of uranium and plutonium from the aqueous to the organic phase in the PUREX process.

磷酸三丁酯(Tributyl phosphate, TBP)常作为络合剂,应用于钚铀萃取法(Plutonium Uranium Extraction, PUREX)液液萃取工艺中,该工艺用于从乏核燃料中回收铀与钚。本研究针对该萃取过程中有机相的分子与微观结构展开探究,借助分子动力学模拟发现:当TBP与烷烃稀释剂混合时,TBP会自组装形成双连续相。TBP的内在自缔合作用由其极性基团间的分子间相互作用驱动,使得丁基基团向外辐射分布于有机溶剂中。模拟结果显示,TBP的扩散系数相较于其分子量对应的理论值反常偏低;实验核磁共振(Nuclear Magnetic Resonance, NMR)研究也测得极低的扩散系数,这与分子聚集模型的结论相符。在油/水界面处的TBP模拟表明,低TBP浓度下会形成双层膜结构;当浓度升高时,会形成与该表面双层结构相连的本体双连续相。我们认为,该结构与PUREX工艺中铀、钚从水相向有机相界面传质的异常快速动力学过程密切相关。
提供机构:
Taylor & Francis
创建时间:
2016-01-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作