Computational Steering of Cluster Formation in Brownian Suspensions

TL;DR

This paper introduces a computational steering method for simulating cluster formation in colloidal suspensions, enabling real-time control and exploration of phase transitions under varying experimental conditions.

Contribution

It presents a novel steering approach that allows dynamic control of simulations to efficiently explore phase behavior in colloidal systems.

Findings

The steering method effectively detects structural transitions.

Simulations reveal different phases like clusters, glasses, and liquids.

Physical constraints limit the steering applicability.

Abstract

We simulate cluster formation of model colloidal particles interacting via DLVO (Derjaguin, Landau, Vervey, Overbeek) potentials. The interaction potentials can be related to experimental conditions, defined by the pH-value, the salt concentration and the volume fraction of solid particles suspended in water. The system shows different structural properties for different conditions, including cluster formation, a glass-like repulsive structure, or a liquid suspension. Since many simulations are needed to explore the whole parameter space, when investigating the properties of the suspension depending on the experimental conditions, we have developed a steering approach to control a running simulation and to detect interesting transitions from one region in the configuration space to another. The advantages of the steering approach and the restrictions of its applicability due to physical constraints are illustrated by several example cases.