Simulation of enhanced CO2 mass transfer of nanofluid with Lattice Boltzmann method coupled cell automation probabilistic model.

Nanofluid is a particle suspension composed of liquid and nanoparticles, and has great potential to enhance mass transfer. Most previous studies have only considered the effect of the Brownian motion of nanoparticles on mass transfer. In this study, the two-dimensional Lattice Boltzmann method (LBM) combined with the cell automation (CA) probabilistic model is proposed to investigate the mass transfer of CO 2 in nanofluids. The model predictions were in good agreement with experimental data, validating the developed mass transfer model. The simulation results indicated that the Brownian motion and grazing effect enhanced the mass transfer in nanofluids, and should be considered simultaneously. Comparing with the pure water, adding 0.1 wt% SiO 2 nanoparticles increased the absorption rate up to 58.3 %, and the effective diffusion coefficients reached 5.41 × 10−9 m2s−1. In addition, changing the physical parameters directly affected the Brownian motion and grazing effect, and changed the effective diffusion coefficient of CO 2 in the nanofluid. The effective diffusion coefficient decreased with an increase in particle size and increased with an increase in fluid temperature. [Display omitted] • The LBM combined with the CA was proposed to investigate the mass transfer of CO 2 in nanofluids. • In our developed model, the nanoparticles can move independently in the solution and absorb CO 2. • The effect of nanoparticles's Brownian motion and grazing effect on mass transfer were both considered. • The effects of different physical parameters on mass transfer in nanofluids were analyzed. [ABSTRACT FROM AUTHOR]