(571c) Polymer-Induced Aggregation of Hematite Under Shear By CFD-DEM Simulations | AIChE

(571c) Polymer-Induced Aggregation of Hematite Under Shear By CFD-DEM Simulations

Authors 

Zeng, L. - Presenter, The University of Melbourne
Franks, G., The University of Melbourne
Goudeli, E., University of Melbourne
Effective particle recovery by froth flotation predominantly occurs within particle size ranges of 50-150 microns [1]. As such, aggregation of fine valuable particles smaller than 20 microns plays an important role for their recovery during mineral processing. Mineral microparticles can spontaneously undergo weak aggregation under shear due to attractive interparticle (DLVO) interactions [2]. However, aggregates smaller than 50 microns are not sufficiently large to be effectively separated via froth flotation. Addition of polymers to the suspension is commonly used to produce large and strong mineral aggregates [3], that are suitable for collection via froth flotation. The mechanism of polymer-induced aggregation, as well as the detailed relationship between particle interactions and polymer dosage, and the dynamics of aggregate growth remain poorly understood. Particle-based simulations offer a promising approach for investigating strong aggregation induced by polymers, enabling the quantification and observation associated with the aggregation process.

Here, coupled Computational Fluid Dynamics – Discrete Element Method (CFD-DEM) is employed to explore the impact of polymer dosage on size and structure of hematite particle under shear, taking into account both particle-particle and particle-fluid interactions. The Yukawa force model [4, 5], is introduced to describe polymer-induced bridging flocculation for strong particle aggregation. The temporal evolution of aggregate size, size distribution, number concentration, and structural characteristics during aggregate growth are quantified shedding light into the detailed mechanism of polymer-induced aggregation.

References

1. Ralston, J., Fornasiero, D., Grano, S., Duan, J., and Akroyd, T., Reducing uncertainty in mineral flotation—flotation rate constant prediction for particles in an operating plant ore. International Journal of Mineral Processing, 2007. 84(1): p. 89-98. https://doi.org/10.1016/j.minpro.2006.08.010.

2. Zeng, L., Franks, G.V., and Goudeli, E., Aggregation and breakage dynamics of alumina particles under shear by coupled Computational Fluid Dynamics – Discrete Element Method. Journal of Colloid and Interface Science, 2024. 661: p. 750-760. https://doi.org/10.1016/j.jcis.2024.01.210.

3. Zhou, Y., Gan, Y., Wanless, E.J., Jameson, G.J., and Franks, G.V., Interaction Forces between Silica Surfaces in Aqueous Solutions of Cationic Polymeric Flocculants: Effect of Polymer Charge. Langmuir, 2008. 24(19): p. 10920–10928. https://doi.org/10.1021/la801109n.

4. Elghazrani, K., Azougarh, A., Oberdisse, J., and Filali, M., Interactions between microemulsion droplets decorated with hydrophobically modified polymers: A small-angle neutron scattering study. The European Physical Journal E, 2014. 37(12): p. 128. https://doi.org/10.1140/epje/i2014-14128-8.

5. Yukawa, H., On the Interaction of Elementary Particles. I. Proceedings of the Physico-Mathematical Society of Japan. 3rd Series, 1935. 17: p. 48-57. https://doi.org/10.11429/ppmsj1919.17.0_48.