Random Sequential Adsorption on mobile patches

TL;DR

This paper extends the RSA model to include mobile patches that diffuse and adsorb particles, revealing that the jammed-state coverage depends only on the ratio of flux to diffusion coefficient, with different regimes based on patch density.

Contribution

It introduces a novel RSA extension with mobile patches, analyzing how flux and diffusion influence coverage and morphology through simulations and mean-field theory.

Findings

Jammed-state coverage depends solely on F/D ratio.

Two regimes of coverage based on patch density.

Coverage time dependence varies with F and D.

Abstract

An extension of the Random Sequential Adsorption (RSA) model has been proposed recently, motivated by the coverage of oil droplets by DNA-functionalized colloidal particles. Particles arrive to a flat substrate with a uniform flux F but they can only adsorb on patches. Patches diffuse on the substrate with a diffusion coefficient D if they are free and they remain immobile when attached to an adsorbed particle. The adsorption is considered irreversible and particles cannot adsorb on top of each other. Thus, the system reaches a jammed state, consisting of a monolayer where no more particles can adsorb. We performed Monte Carlo simulations to study the adsorption kinetics and jammed-state morphology on a one-dimensional lattice. We show that, while the time-dependence of the coverage depends on F and D, the jammed-state coverage depends solely on the ratio F/D. This result is grasped by a simple mean-field calculation. We also report two different regimes for the functional dependence of the jammed-state coverage on the size of the particles, for low and high density of patches.