Random sequential adsorption of polydisperse mixtures on lattices.

Area of Science:

• Surface Science and Physical Chemistry
• Computational Physics and Materials Science

Background:

• Understanding particle adsorption on surfaces is crucial for applications in materials science, catalysis, and nanotechnology.
• Previous models often simplify particle shapes and size distributions, limiting their predictive power for complex systems.

Purpose of the Study:

• To numerically investigate the random sequential adsorption (RSA) of linear and square particles with excluded volume interactions on planar lattices.
• To analyze the influence of Gaussian size distributions (average size μ and width-to-average ratio w) on adsorption kinetics and particle arrangement.

Main Methods:

• Numerical simulations of RSA on planar lattices.
• Modeling incident particles with Gaussian distributions of lateral sizes.
• Analysis of coverage (θ) as a function of time (t), adsorption time (tM), and particle characteristics (μ, w).

Main Results:

• Adsorption time (tM) scales with monolayer incidence time (τ), with linear particles adsorbing slower (1.5τ < tM < 5τ) than square particles (0.3τ < tM < τ).
• Surface coverage at tM is approximately 0.3 for linear and 0.2 for square particles.
• Particle size distribution of adsorbed particles closely matches incident distributions for small w (≤1/8) but deviates significantly for larger w (≥1/2).

Conclusions:

• The shape of adsorbed particles and the width of their size distribution critically influence adsorption kinetics and final surface coverage.
• The observed differences in adsorbed vs. incident size distributions for larger w can serve as a consistency test for RSA models.
• The pair correlation function reveals distinct structural ordering depending on the width of the incident size distribution.