A minimal predictive model for better formulations of solvent phases with low viscosity - CEA - Commissariat à l’énergie atomique et aux énergies alternatives
Article Dans Une Revue EPJ N - Nuclear Sciences & Technologies Année : 2020

A minimal predictive model for better formulations of solvent phases with low viscosity

Résumé

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.

Domaines

Chimie
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Dates et versions

cea-02458352 , version 1 (28-01-2020)

Identifiants

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Maximilian Pleines, Maximilian Hahn, Jean Duhamet, Thomas Zemb. A minimal predictive model for better formulations of solvent phases with low viscosity. EPJ N - Nuclear Sciences & Technologies, 2020, 6, pp.3. ⟨10.1051/epjn/2019055⟩. ⟨cea-02458352⟩
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