Implications of the effective one-component analysis of pair correlations in colloidal fluids with polydispersity
Mark J. Pond, Jeffrey R. Errington, Thomas M. Truskett

TL;DR
This study investigates how simplifying polydisperse colloidal fluids to an effective one-component model affects the understanding of their structure and dynamics, revealing significant differences from multicomponent descriptions especially at higher concentrations.
Contribution
It introduces a Monte Carlo sampling method for analyzing partial pair-correlation functions in highly polydisperse systems and compares effective one-component and multicomponent descriptions.
Findings
Effective one-component models can overlook important structural details.
Multicomponent analysis reveals different trends in structural order and attractions.
Differences impact the interpretation of shear viscosity and dynamic scaling behaviors.
Abstract
Partial pair-correlation functions of colloidal suspensions with continuous polydispersity can be challenging to characterize from optical microscopy or computer simulation data due to inadequate sampling. As a result, it is common to adopt an effective one-component description of the structure that ignores the differences between particle types. Unfortunately, whether this kind of simplified description preserves or averages out information important for understanding the behavior of the fluid depends on the degree of polydispersity and can be difficult to assess, especially when the corresponding multicomponent description of the pair correlations is unavailable for comparison. Here, we present a computer simulation study that examines the implications of adopting an effective one-component structural description of a polydisperse fluid. The square-well model that we investigate…
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