Colloidal Cluster Self-Assembly Through Connectivity Landscape Analysis

Prefabricated micron-scale colloidal clusters offer a practical way for introducing anisotropic interactions and enabling the formation of interesting crystalline superstructures that are otherwise inaccessible with spherically symmetric interactions. However, it is apparent that the high-dimensional parameter space that defines the geometric and interaction properties of such systems poses an obstacle to assembly design and optimization.

Here, we introduce an analytical framework, connectivity landscape analysis (CLA), for analyzing the geometrical parameter space of superstructures that may be grown with colloidal clusters. CLA segments the overall parameter space into distinct regions in which specific contacts are made between different pairs of particle types. Combined with a small number of targeted molecular dynamics simulations of superstructure growth, we show that it is possible to quickly determine feasibility regions in which the superstructure can be grown. In this context, CLA corresponds to a type of dimensionality reduction, allowing the resulting simplified space to be efficiently scanned either computationally or experimentally.