An Efficient Algorithm for Topological Characterisation of Worm-Like and Branched Micelle Structures from Simulations

TL;DR

This paper introduces a novel topological algorithm for accurately characterizing worm-like and branched micelle structures in particle simulations, addressing limitations of previous methods and enabling detailed analysis of surfactant micelles.

Contribution

The authors develop a new mathematical algorithm for topological analysis of micelle structures in simulations, improving upon existing techniques especially for complex shapes.

Findings

Algorithm successfully characterizes SDS micelles in simulations.

Addresses mathematical challenges with curved and fluctuating micelle structures.

Enables comprehensive topological analysis of micelle formation.

Abstract

Many surfactant-based formulations are utilised in industry as they produce desirable visco-elastic properties at low-concentrations. These properties are due to the presence of worm-like micelles (WLM) and, as a result, understanding the processes that lead to WLM formation is of significant interest. Various experimental techniques have been applied with some success to this problem but can encounter issues probing key microscopic characteristics or the specific regimes of interest. The complementary use of computer simulations could provide an alternate route to accessing their structural and dynamic behaviour. However, few computational methods exist for measuring key characteristics of WLMs formed in particle simulations. Further, their mathematical formulation are challenged by WLMs with sharp curvature profiles or density fluctuations along the backbone. Here we present a new topological algorithm for identifying and characterising WLMs micelles in particle simulations which has desirable mathematical properties that address short-comings in previous techniques. We apply the algorithm to the case of Sodium dodecyl sulfate (SDS) micelles to demonstrate how it can be used to construct a comprehensive topological characterisation of the observed structures.