Design Strategies for Self-Assembly of Discrete Targets
Jim Madge, Mark A. Miller

TL;DR
This paper introduces a model for self-assembly of cubic particles with patterned faces, comparing different strategies like hierarchical and addressable schemes through simulations to evaluate their efficiency and robustness.
Contribution
It presents an idealized model and simulation framework to compare self-assembly strategies, highlighting conditions where complex schemes outperform simple ones.
Findings
One-component assembly is most efficient overall.
Hierarchical and addressable schemes can outperform simple schemes in certain conditions.
Simulations capture thermodynamic, dynamic, and steric challenges of self-assembly.
Abstract
Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks, to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture…
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