低粘度溶剂相更好配方的最小预测模型

IF 0.9 Q3 NUCLEAR SCIENCE & TECHNOLOGY
Maximilian Pleines, M. Hahn, J. Duhamet, T. Zemb
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引用次数: 5

摘要

随着液液萃取过程的加剧,有机相的粘度增加,给工业规模的湿法冶金工艺带来了困难。本文以硝酸铀酰存在下的N,N-二基酰胺为例,对这一问题进行了实验分析。此外,我们提出了一个纳米尺度的最小模型,通过连接分子、介观和宏观尺度,使实验现象合理化,并允许预测粘度的定性趋势。该模型为优化约束开辟了广阔的可能性,并且是朝着基于知识的配方提取由低连通性微结构形成的微乳液的进一步一步,即使在重金属高负荷下也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A minimal predictive model for better formulations of solvent phases with low viscosity
The viscosity increase of the organic phase when liquid–liquid extraction processes are intensified causes difficulties for hydrometallurgical processes on industrial scale. In this work, we have analyzed this problem for the example of N,N-dialkylamides in the presence of uranyl nitrate experimentally. Furthermore, we present a minimal model at nanoscale that allows rationalizing the experimental phenomena by connecting the molecular, mesoscopic and macroscopic scale and that allows predicting qualitative trends in viscosity. This model opens broad possibilities in optimizing constraints and is a further step towards knowledge-based formulation of extracting microemulsions formed by microstructures with low connectivity, even at high load with heavy metals.
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来源期刊
EPJ Nuclear Sciences & Technologies
EPJ Nuclear Sciences & Technologies NUCLEAR SCIENCE & TECHNOLOGY-
CiteScore
1.00
自引率
20.00%
发文量
18
审稿时长
10 weeks
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