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Stefan Reimann-Zitz

Publications and source records attributed to Stefan Reimann-Zitz.

2 recordsLinked to original sources

Mixing of miscible liquids: Dimensionless scaling for intermediate-to-large density differences in a stirred tank

Mixing of miscible liquids is an essential process in multiple industrial settings, usually with the intent to homogenize the product. This seemingly simple process is in fact a complex hydrodynamic problem that has a direct impact on the product quality. In this study, numerical simulations of a stirred tank were performed with a 50/50 ratio of liquids and systematically varied the Reynolds and Richardson numbers. A positive correlation between the mixing time and the Richardson number was observed, as reported in the literature. The influence of the Reynolds number was not as pronounced and clear. Based on the Power, Froude and Richardson numbers, we were able to derive an exponential scaling for the dimensionless mixing time that collapsed all our data onto one master curve.

physics.flu-dyn

Practical Insights to Thin Film Dewetting

Thin liquid films exhibit rich instability and rupture dynamics that critically impact coating performance across many applications. In this work, we use the lattice Boltzmann method (LBM) simulations within a lubrication-theory framework to systematically quantify how film thickness, surface energy, wettability, and intermolecular forces govern dewetting kinetics and long-time morphology. Master-curve scalings are identified for the time to dewet, revealing a strong power-law sensitivity to film thickness and a comparatively weak dependence on moderate variations in the contact angle. Following rupture, the film reaches a physically meaningful coverage plateau, whose magnitude correlates with material parameters and provides a practical window for morphological stabilization prior to coarsening. Long-time evolution obeys classical coarsening scaling laws, with surface energy controlling domain density. These results demonstrate that lubrication-based models can deliver predictive design guidance for evaluating coating robustness and forming materials and surface engineering strategies. Source code is available at https://github.com/Zitzeronion/Swalbe.jl.

cond-mat.mtrl-sci