Optimization and sensitivity analysis of rheological properties of high concentration γ‐alumina/water suspension

In this study, a high concentration γ‐alumina/water suspension containing 75% (wt) γ‐alumina nanoparticle was prepared by using a 3D‐mixer. TEM imaging, Dynamic Light Scattering (DLS), and X‐Ray Diffraction (XRD) analyses were used to investigate the stability of nanoparticles in the base fluid, purity, and crystallinity as well as chemical structure of nanoparticles, respectively. Then, the variation of dynamic viscosity and rheological behavior of the suspension and their dependency on pH, sonication durations, dispersing agent concentrations, and ratios of ceramic balls to nanoparticles weight was studied. The results showed that the rheological behavior of the suspension was similar to non‐Newtonian fluids, and a power‐law model with yield stress was able to justify this behavior. Moreover a correlation, including pH, sonication time, dispersing agent concentration, and the ratio of ceramic balls to nanoparticles weight as independent parameters, was developed to predict the power of the power‐law model. The model showed a low deviation, about 5%, from the experimental values and revealed the significant effect of pH, sonication time, and the ratio of mixing ceramic balls to nanoparticles on the rheological behavior of the suspension. More importantly, by implementing the method used in this work, a very low dynamic viscosity of 11.4 mPa.s was achieved. While using a 3D‐mixer, there are parameters influencing the rheological behavior and stability of nano alumina suspensions such as mixing time, size of ceramic balls, the weight ratio of nano‐particles to ceramic balls (N/B ratio), suspension pH, amount of dispersing agent, and sonication time can be noted. TEM imaging, dynamic light scattering (DLS), and X‐ray diffraction (XRD) analyses can be employed to evaluate the stability of nanoparticles in the base fluid, and purity and crystallinity of nanoparticles, respectively. An empirical correlation can be developed to correlate the rheological behavior of the high concentration nanofluid by considering pH, sonication time, dispersing agent concentration, and N/B ratio as independent variables.