Fluidization and mixing of nanoparticle agglomerates assisted via magnetic impaction View Full Text


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Article Info

DATE

2013-02

AUTHORS

James V. Scicolone, Daniel Lepek, Lin Louie, Rajesh N. Davé

ABSTRACT

Mixing of nanopowders in an environmentally benign magnetically assisted fluidized bed (MAFB) system was studied. Examination of fluidization behavior of agglomerate particulate fluidization (APF; silica R974 or R972) and agglomerate bubbling fluidization (ABF; alumina or titania) nano-powders in un-assisted and MAFB systems confirmed previous results on decreased minimum fluidization velocity and increased bed expansion of APF and ABF powders due to magnetic assistance. APF and ABF powder mixtures behaved like APF powders with the bed expansions in between those of individual constituents. Unlike previous MAFB studies, fluidization as a function of time was studied to examine its influence on nano-mixing. With time, the bed expansion reduced, and reduction was faster as magnet-to-powder ratio increased from 0:1 to 5:1, although fluidization was sustained, confirmed via the pressure drop measurements. Reduction in bed expansion was attributed to change in the nature of nanoagglomerates, which showed increased density as a function of processing time, ruling out electrostatics or elutriation as major factors. Mixtures of silica (APF) and alumina (ABF), processed at various magnet-to-powder ratios, were characterized via statistical analysis from energy dispersive x-ray spectroscopy using field emission scanning electron microscope to compute homogeneity of mixing (HoM). Magnetic assistance improved the HoM as a function of time, and was strongly related to the product of number of magnets and time, similar to previous results in magnetically assisted impaction mixing (MAIM). The best achievable HoM was significantly better than unassisted fluidization and comparable to previous results for rapid expansion of high-pressure suspensions and MAIM. More... »

PAGES

1434

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11051-013-1434-7

DOI

http://dx.doi.org/10.1007/s11051-013-1434-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042292704


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