Model for Spreading of Liquid Monolayers

TL;DR

This paper uses kinetic Monte Carlo simulations to analyze the spreading dynamics of liquid monolayers on substrates, confirming theoretical predictions and revealing how inter-particle attraction influences spreading and density profiles.

Contribution

The study provides detailed simulation results on monolayer spreading, demonstrating the effects of inter-particle attraction and density, and improves mean-field models to include correlation effects.

Findings

Spreading follows a  ightarrow \u221a t dependence.

Prefactor A depends on attraction strength U_0 and reservoir density C_0.

Including correlations improves density profile predictions.

Abstract

Manipulating fluids at the nanoscale within networks of channels or chemical lanes is a crucial challenge in developing small scale devices to be used in microreactors or chemical sensors. In this context, ultra-thin (i.e., monolayer) films, experimentally observed in spreading of nano-droplets or upon extraction from reservoirs in capillary rise geometries, represent an extreme limit which is of physical and technological relevance since the dynamics is governed solely by capillary forces. In this work we use kinetic Monte Carlo (KMC) simulations to analyze in detail a simple, but realistic model proposed by Burlatsky \textit{et al.} \cite{Burlatsky_prl96,Oshanin_jml} for the two-dimensional spreading on homogeneous substrates of a fluid monolayer which is extracted from a reservoir. Our simulations confirm the previously predicted time-dependence of the spreading, $X(t \to \infty) = A \sqrt t$, with $X(t)$ as the average position of the advancing edge at time $t$, and they reveal a non-trivial dependence of the prefactor $A$ on the strength $U_0$ of inter-particle attraction and on the fluid density $C_0$ at the reservoir as well as an $U_0$-dependent spatial structure of the density profile of the monolayer. The asymptotic density profile at long time and large spatial scale is carefully analyzed within the continuum limit. We show that including the effect of correlations in an effective manner into the standard mean-field description leads to predictions both for the value of the threshold interaction above which phase segregation occurs and for the density profiles in excellent agreement with KMC simulations results.