Controlling morphology in hybrid isotropic/patchy particle assemblies

TL;DR

This study uses Brownian Dynamics simulations to explore how hybrid isotropic and patchy particles self-assemble into different morphologies, revealing a sharp transition between amorphous and crystalline structures based on particle size ratios.

Contribution

It introduces a novel simulation approach combining annealing and symmetry-specific order parameters to control and characterize morphology in hybrid particle assemblies.

Findings

Sharp morphological crossover detected at specific size ratios

High symmetry phases observed for larger size ratios

Coherent clusters identified in amorphous structures using SymBOPs

Abstract

Brownian Dynamics is used to study self-assembly in a hybrid system of istotropic particles (IPs), combined with anisotropic building blocks that represent special "designer particles". Those are modeled as spherical patchy particles (PPs) with binding only allowed between their patches and IPs. In this study, two types of PPs are considered: Octahedral PPs (Oh-PPs) and Square PPs (Sq-PPs), with octahedral and square arrangements of patches, respectively. The self-assembly is additionally facilitated by the simulated annealing procedure. The resultant structures are characterized by a combination of local correlations in cubatic ordering, and a symmetry-specific variation of bond orientation order parameters (SymBOPs). By varying the PP/IP size ratio, we detected a sharp crossover between two distinct morphologies, in both types of systems. High symmetry phases, NaCl crystal for Oh-PP and square lattice for Sq-PP, are observed for larger size ratios. For smaller ones, the dominant morphologies are significantly different, e.g., Oh-PPs form a compact amorphous structure with predominantly Face-to-Face orientation of neighboring PPs. Unusually for a morphology without a long range order, it is still possible to identify well organized coherent clusters of this structure, thanks to the adoption of our SymBOP-based characterization.