Pressure-drop viscosity measurements for gamma-Al2O nanoparticles in water and PG-water mixtures (nanofluids).

Nanofluids have attracted wide attention because of their promising thermal applications. Compared with the base fluid, numerous experiments have generally indicated increases in effective thermal conductivity and convective heat transfer coefficient for suspensions having only a small amount of nanoparticles. It is also known that with the presence of nanoparticles, the viscosity of a nanofluid is greater than its base fluid and deviates from Einstein's classical prediction. However, only a few groups have reported nanofluid viscosity results to date. Therefore, relative viscosity data for gamma-Al2O3 nanoparticles in DI-water and propylene glycol/H2O mixtures are presented here based on pressure drop measurements of flowing nanofluids. Results indicate that with constant wall heat flux, the relative viscosities of nanofluid decrease with increasing volume flow rate. The results also show, based on Brenner's model, that the nanofluid viscosity can be explained in part by the aspect ratio of the aggregates.

Dynamics of rotating paramagnetic particles simulated by lattice Boltzmann and particle dynamics methods.

Novel biochemical sensors consisting of rotating chains of microscale paramagnetic particles have been proposed that would enable convenient, sensitive analyte detection. Predicting the dynamics of these particles is required to optimise their design. The results of lattice Boltzmann (LB) and particle dynamics (PD) simulations are reported, where the LB approach provides a verified solution of the complete Navier-Stokes equations, including the hydrodynamic interactions among the particles. On the other hand, the simpler PD approach neglects hydrodynamic interactions, and does not compute the fluid motion. It is shown that macroscopic properties, like the number of aggregated particles, depend only on the drag force and not on the total hydrodynamic force, making PD simulations yield reasonably accurate predictions. Relatively good agreement between the LB and PD simulations, and qualitative agreement with experimental data, are found for the number of aggregated particles as a function of the Mason number. The drag force on a rotating cylinder is significantly different from that on particle chains calculated from both simulations, demonstrating the different dynamics between the two cases. For microscopic quantities like the detailed force distributions on each particle, the complete Navier-Stokes solution, here represented by the LB simulation, is required.

Enhanced mass transport in nanofluids.

Thermal conductivity enhancement in nanofluids, which are liquids containing suspended nanoparticles, has been attributed to localized convection arising from the nanoparticles' Brownian motion. Because convection and mass transfer are similar processes, the objective here is to visualize dye diffusion in nanofluids. It is observed that dye diffuses faster in nanofluids compared to that in water, with a peak enhancement at a nanoparticle volume fraction, phi, of 0.5%. A possible change in the slope of thermal conductivity enhancement at that same phi signifies that convection becomes less important at higher phi. The enhanced mass transfer in nanofluids can be utilized to improve diffusion in microfluidic devices.