Estimating Al2O3–CO2 nanofluid viscosity: a molecular dynamics approach

Abstract

High-viscosity CO2 is of interest to the oil and gas industry in enhanced oil recovery and well-fracturing applications. Dispersing nanoparticles in CO2 is one way of achieving increased viscosity. However, parametric studies on viscosity estimation of CO2 nanofluids is not found in the open literature. A comparison of various interatomic potentials for their accuracy in predicting viscosity is also missing. In this work, we studied Al2O3 nanoparticles in CO2 base fluid. We screened the inter-molecular interaction potential models available for CO2–CO2 interactions and found that the TraPPE-flexible model (with MORSE potential) to be most suitable for conditions used in this work. We estimated the CO2–Al2O3 interaction potential using quantum mechanical simulations. Using this combination for CO2–CO2 and CO2–Al2O3 interactions, we explored the effects of temperature and nanoparticle size on viscosity using molecular dynamics simulations (MD). We predicted that the viscosity would increase with increase in temperature and particle size. We also calculated the base fluid self-diffusion coefficient to investigate the effect of Brownian motion and its contribution to changes in viscosity. We found that it decreases with increase in particle size and temperature, thereby indicating that Brownian motion does not contribute to the increased viscosity. Further, the nanolayer formed at the Al2O3–CO2 interface is studied through density distributions around the nanoparticle; the thickness of this nanolayer is found to increase with nanoparticle diameter. Finally, we examined the structures of CO2 fluid in presence of nanoparticles at different thermodynamic states through radial distribution functions. The current work sheds light on the viscosity enhancement by the addition of nanoparticles; it is hoped that such studies will lead to tools that help tailor fluid properties to specific requirements.