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This study introduces a novel sharp-interface model for dynamic wetting, incorporating mass diffusion at the contact line. The model effectively resolves contact line singularities without empirical fitting, offering an efficient alternative for fluid dynamics simulations.

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Area of Science:

  • Fluid Dynamics and Interface Science
  • Computational Physics

Background:

  • Classical sharp-interface models face contact line singularities due to the no-slip condition, often requiring empirical Navier boundary conditions.
  • Phase-field models naturally handle contact line dynamics via mass diffusion, but can be computationally intensive.
  • A need exists for efficient sharp-interface methods that capture diffusive mass transport at the contact line.

Purpose of the Study:

  • To develop a computationally efficient sharp-interface toy model that incorporates mass diffusion at the contact line.
  • To regularize contact line singularities without empirical parameter fitting.
  • To provide a practical alternative for simulating dynamic wetting phenomena.

Main Methods:

  • Developed a theoretical relation from Cahn-Hilliard equations linking diffusive mass transport to wall curvature.
  • Estimated chemical potential on a curved interface to derive the highly curved region width (δ) and apparent contact angle.
  • Introduced a fictitious boundary within the sharp-interface framework with a dynamic apparent contact angle condition.

Main Results:

  • The toy model successfully accounts for mass diffusion at the contact line within a sharp-interface framework.
  • Model validation against phase-field simulations showed good agreement for liquid bridge steady states and drop spreading transients.
  • The model provides an efficient and practical method for solving contact line problems.

Conclusions:

  • The proposed sharp-interface toy model effectively resolves contact line singularities by incorporating mass diffusion.
  • This approach offers a computationally less expensive alternative to phase-field methods for dynamic wetting simulations.
  • The model's parameters can be informed by phase-field simulations, bridging the gap between methods.