Moving contact line dynamics for capillary-driven microfluidics in wetting transition regime

Abstract

The dynamics of moving contact lines (MCLs) dominate the behavior of capillary-driven microfluidics, which underlie many applications including microfluidic chips. The capillary displacement dynamics in the quasi-static regime has been extensively studied. However, the behavior of MCLs in the dynamic wetting transition regime remains largely unexplored, and previously established MCL dynamic models may be inadequate. In this study, a novel capillary displacement experiment is introduced, which is achieved by reversely introducing microfluidics with surface tension differences, where the one with low surface tension undergoes the wetting transition. In addition, a generalized Navier boundary condition (GNBC)-based model of capillary displacement dynamics is developed within the framework of diffusive interface theory to investigate the MCL dynamics in the wetting transition regime. The oscillation-relaxation process is experienced for phase interface and microscopic dynamic contact angle θd in the wetting transition regime. Spontaneous filling distance follows dfill*∼t1/2, and reaching quasi-static stage follows dfill*∼t1. The previously neglected mechanism of inertial-viscous competition dominates the early dynamics of such dynamic wetting transition processes. θd∝ucl is observed to be valid solely under conditions where viscosity dominates, but it breaks down in the presence of dominant inertial effects. An escalation in slip substantially diminishes the influence of inertia, with frictional dissipation mediated by slip emerging as the predominant factor in the capillary-driven early dynamics. The origin of uncompensated Young's stress in the GNBC and its correlation with capillary forces is unified, unveiling the underlying physical mechanism governing the dynamics at the MCL. Finally, by decoupling the analysis of viscosity and slip, a new θd-viscous-slip formulation is proposed, in agreement with the model predictions.