Reentrant Network Formation in Patchy Colloidal Mixtures under Gravity

TL;DR

This study investigates how gravity influences the layering and network formation in a binary mixture of patchy colloids, revealing complex stacking sequences and reentrant percolation behavior through simulations and theoretical modeling.

Contribution

It introduces a theoretical framework that predicts gravity-induced stacking and reentrant network formation in patchy colloidal mixtures, validated by Monte Carlo simulations.

Findings

Complex stacking sequences with up to four layers observed.

Reentrant network formation occurs under certain buoyant mass conditions.

Theoretical predictions align with simulation results.

Abstract

We study a two-dimensional binary mixture of patchy colloids in sedimentation-diffusion-equilibrium using Monte Carlo simulation and Wertheim's theory. By tuning the buoyant masses of the colloids we can control the gravity-induced sequence of fluid stacks of differing density and percolation properties. We find complex stacking sequences with up to four layers and reentrant network formation, consistently in simulations and theoretically using only the bulk phase diagram as input. Our theory applies to general patchy colloidal mixtures and is relevant to understanding experiments under gravity.