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Predicting the flowability of powder mixtures from their single components properties through the multi-component population-dependent granular bond number; extension to ground powder mixtures

Abstract : The granular Bond number, defined as the ratio between interparticle attractive forces and particle's weight, can be computed to predict the flow behavior of powders. Previous studies used this dimensionless number to predict the flowability of various pharmaceutical or ceramic powders, exhibiting polydispersed particle size distributions. In this paper, we employ a multi-component population-dependent granular Bond number in order to apply this model to powder mixtures. Some binary and ternary mixtures are prepared using two different techniques: a Turbula® mixer and a ball mill. The flowability predictions appear to be in very good agreement with the empirical measurements, carried out with a powder shear tester. However, the model parameters seem to be slightly different between milled and raw powders. The model discussed in this paper allows a prediction of the flowability of powder mixtures according to their composition and serve as a guide for product formulation and equipment design.
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https://hal-mines-albi.archives-ouvertes.fr/hal-02975123
Contributor : Imt Mines Albi Ecole Nationale Supérieure Des Mines d'Albi-Carmaux <>
Submitted on : Thursday, October 22, 2020 - 1:55:52 PM
Last modification on : Saturday, October 24, 2020 - 3:06:19 AM

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Martin Giraud, Stéphane Vaudez, Cendrine Gatumel, Jeremy Nos, Thierry Gervais, et al.. Predicting the flowability of powder mixtures from their single components properties through the multi-component population-dependent granular bond number; extension to ground powder mixtures. Powder Technology, Elsevier, In press, ⟨10.1016/j.powtec.2020.10.046⟩. ⟨hal-02975123⟩

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