Prediction of nanoparticle self-assembly structures based on kinetic Monte Carlo algorithm and dynamic nanoparticle diffusion rates

The self-assembly patterns formed during the drying of nanofluid films and droplets are closely associated with the diffusion dynamics of nanoparticles driven by evaporation. This study employs a quasi-three-dimensional kinetic Monte Carlo model to simulate the effects of variations in nanoparticle diffusion rates on the development of distinct deposition patterns in nanofluid films. By incorporating nanoparticle diffusion, this approach provides deeper insights into the evaporation characteristics of nanofluids, advancing the understanding of their underlying mechanisms. Simulation results indicate that, compared to a constant nanoparticle diffusion rate, variations in dynamic nanoparticle diffusion rates significantly influence the morphological evolution of depositions during nanofluid evaporation, resulting in the formation of mesh-like or dendritic particle deposition patterns. In evaporation simulations conducted at varying nanoparticle concentrations, an increase in nanoparticle concentration stabilizes the evaporation dynamics of nanofluid films.