Quantifying surface wettability in textured surfaces using two-dimensional pseudo-potential multiphase lattice Boltzmann model

Surface wettability plays a critical role in microfluidic applications, enabling enhanced fluid flow control, minimizing sample waste, and improving efficiency across various fields, including drying technology, food processing, chemical manufacturing, and ­environmental engineering. This study presents a numerical investigation of surface wettability on textured surfaces utilizing a two-dimensional (2D) pseudo-potential multiphase lattice Boltzmann method (LBM) with a D2Q9 model. The analysis is conducted for a range of solid-fluid interaction parameters (Gads), varying between −2.50 and −1.40. Initially, the equilibrium state of a water droplet on a flat surface is simulated for different interaction parameters to validate the accuracy of the numerical model. Subsequently, micropillars are introduced on the bottom wall of the surface with varying heights and spacings to create hydrophobic and superhydrophobic textures, resulting in enhanced contact angles. The wettability of these surfaces is analyzed by placing a water droplet with a radius of 30 lattice units at the center of a computational domain sized 200 × 200 lattice units. The findings reveal that increasing the interaction parameter on textured surfaces significantly reduces the contact area between the droplet and the solid surface due to the momentum redirection effect, thereby increasing surface surface wettability. Similarly, greater spacing between micropillars enhances surface surface wettability. The simulated contact angles for various interaction strengths have been qualitatively validated with previously reported results, confirming the robustness of the present numerical model.