Viscosity and aggregation structure of nanocolloidal dispersions

Abstract

In this work, the effects of nanoparticle size, particle volume fraction and pH on the viscosity of silicon dioxide nanocolloidal dispersions are investigated. Both size and pH are found to significantly affect nanocolloid viscosity. Two models are used to study the effect of aggregate structure on the viscosity of the nanocolloidal dispersion. The fractal concept is introduced to describe the irregular and dynamic aggregate structure. The structure of aggregates, which is considered to play an important role in viscosity, is affected by both intermolecular and electrostatic forces. The particle interaction is primarily affected by particle distance and becomes stronger with decreasing particle size and increasing volume fraction. The aggregate structure is also affected by the pH of the solution. Studying the relationship between pH and zeta-potential shows that with the neutralization of charges on the particle surface and decreasing electrical repulsion force, the particle interaction becomes dominated by attractive forces and the aggregates form a more compact structure. In recent years, nanocolloidal dispersions, which are heterogeneous mixtures consisting of very small particles with sizes typically in the order of 1-1000 nm, have attracted much attention for applications related to cooling [1], nanolubricants [2], drug delivery and diagnosis [3]. In the application of nanocolloidal dispersions, the viscosity, which is related to the required pumping power and diffusion properties, plays an important role in delivery systems. The rheological behavior of nanoparticle-fluid mixtures have been investigated experimentally [4][5][6][7]. Newtonian behavior has been observed for very dilute suspensions [4,7] and a considerable amount of effort has been devoted to determining the relationship between the viscosity and volume fraction of suspensions. Yu et al.[8] observed shear-thinning behavior when the volume concentration was higher than 0.03. An interesting phenomenon is that most of the viscosities are under-predicted by the traditional Einstein viscosity model [9,10]. This discrepancy could be caused by aggregation of the nanoparticles and an underestimated effective volume fraction of clusters [10,11]. Rubio-Hernandez et al.[6] also noted that the intrinsic viscosity will be affected by the shape of aggregates, which could be changed by the pH and shear rate of a colloidal system. The formation of aggregates can greatly change the transfer of heat and stress in a system because of their porous structure and large effective volume fraction. Particularly for nanocolloidal dispersions, the distance between aggregates can be in the order of several nanometers. The aggregation of nanoparticles can simply be characterized as ellipsoidal with a certain effective size and axial ratio. The size and shape of aggregates can be determined from dynamic scattering light measurements and intrinsic viscosity data, respectively [6]. Aggregation is a dynamic process and the structure changes continuously because of Brownian m...

Experimental investigation on synthesis, characterization, stability, thermo-physical properties and rheological behavior of MWCNTs-kapok seed oil based nanofluid

“…The viscosity of nanofluid decreases non-linearly with the rise in temperature in all sonication time ranges as the rising in temperature diminish the intermolecular forces between the nanoparticles and base fluid [58]. This temperature-viscosity behavior shows high agreement with most of the previous work [74][75][76]. It should be noted that there are many models available for the prediction of effective viscosity as a function of volume concentration without any temperature dependence consideration [77][78][79][80].…”

Influence of bound water layer on the viscosity of oxide nanopowder suspensions

“…More extensive comparisons in literature were reported the similar conclusions. 5,[23][24][25][26][32][33][34][35] Besides, none of the models explain the difference between oxide systems. Here, we propose to incorporate the bound water concept to model the suspension viscosities of different oxide systems.…”

“…The current models underestimate the viscosity of nanopowder suspensions and it is a topic of current debate. 5,[23][24][25][26][32][33][34][35] We suggested the "bound water" mechanism to explain the relatively higher viscosities of nanopowder suspensions. [36][37][38] Since the bound water, which exists around the nanoparticles, does not serve as a solvent in the system, but behaves as a part of the powder, the effective solids content increases and is partially responsible for the high viscosities of alumina nanopowder suspensions.…”

Experimental investigation of turbulent flow convection heat transfer of MgO/water nanofluid at low concentrations – Prediction of aggregation effect of nanoparticles

“…In determining the viscosity by considering the aggregate effect of particles, the model used by many researchers has been the fractal model [23][24][25][26][27][28][29], while in this research, the fractal model was compared with conventional models without considering the aggregate effect.…”