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Published on: September 9, 2022
Colloidal particle adsorption at liquid interfaces: capillary driven dynamics and thermally activated kinetics
Amir M Rahmani1, Anna Wang, Vinothan N Manoharan
1Department of Mechanical Engineering, Stony Brook University, Stony Brook, New York 11794, USA. carlos.colosqui@stonybrook.edu.
This study introduces a Langevin model to explain colloidal particle adsorption at liquid interfaces. The model captures both fast capillary-driven and slow thermally activated kinetics, including dynamics before the equilibrium crossover.
Area of Science:
- Colloid and interface science
- Soft matter physics
- Statistical mechanics
Background:
- Colloidal microparticle adsorption at water-oil interfaces exhibits slow relaxation to equilibrium.
- This slow kinetics is attributed to nanoscale surface defects creating metastable contact line configurations.
- Previous models focused on relaxation kinetics, leaving initial adsorption dynamics unstudied.
Purpose of the Study:
- To develop a comprehensive model describing the entire adsorption process of single colloidal particles at liquid interfaces.
- To account for metastable states induced by surface defects and thermal fluctuations.
- To accurately predict the crossover from fast capillary-driven to slow thermally activated kinetics.
Main Methods:
- Development of a Langevin model incorporating metastable states and thermal motion.
- Inclusion of a drag term based on the fluctuation-dissipation theorem to account for interface fluctuations.
- Langevin dynamics simulations to model the adsorption process.
Main Results:
- The proposed Langevin model successfully describes the complete adsorption dynamics.
- The model captures the crossover from fast initial adsorption to slow logarithmic relaxation.
- Simulations show close agreement with experimental observations for various microparticles.
Conclusions:
- The Langevin model provides a unified framework for understanding colloidal particle adsorption kinetics.
- Surface defects and thermal fluctuations are crucial for explaining the observed adsorption dynamics.
- The model accurately predicts the transition to slow, thermally activated kinetics.
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