Investigation and estimation on deagglomeration of nanoparticle clusters in teethed in-line high shear mixers

Abstract

Experimental measurements and numerical studies with CFD method were performed to investigate the deagglomeration performance including the deagglomeration mechanism and the smallest attainable size of nano-clusters in in-line HSM under different operating conditions and structural parameters. The results indicate that the deagglomeration is dominated by rupture mechanism under lower energy input while controlled by erosion mechanism at higher energy input. Besides, the smallest size of nano-clusters is 131 nm, regardless of operating conditions and structural parameters of rotor–stator head. The deagglomeration performance can be effectively improved through increasing rotor speed, employing self-cycle mode and appropriately reducing residence time. In addition, the deagglomeration performance is also significantly impacted by the structural parameters involving rotor tooth number, shear gap and rotor teeth inclination. An ANN model is established to correlate the Sauter mean diameter d32 with the investigated parameters, and the comparison between estimated data and experimental data suggests that this method achieved an accurate prediction of d32 for the whole dispersion.