Low-dissipation self-assembly protocols of active sticky particles

TL;DR

This paper employs neuroevolution to discover low-dissipation self-assembly protocols for active particles, revealing that attraction suffices for long times, while self-propulsion is essential for rapid assembly, with entropy scaling depending on the mechanism used.

Contribution

It introduces a neuroevolutionary approach to optimize self-assembly protocols, highlighting the roles of attraction and self-propulsion in entropy production.

Findings

Attractive interactions suffice for low-dissipation assembly with ample time.

Self-propulsion becomes necessary for rapid assembly, increasing entropy.

Entropy scales with particle number and swim length depending on the protocol.

Abstract

We use neuroevolutionary learning to identify time-dependent protocols for low-dissipation self-assembly in a model of generic active particles with interactions. When the time allotted for assembly is sufficiently long, low-dissipation protocols use only interparticle attractions, producing an amount of entropy that scales as the number of particles. When time is too short to allow assembly to proceed via diffusive motion, low-dissipation assembly protocols instead require particle self-propulsion, producing an amount of entropy that scales with the number of particles and the swim length required to cause assembly. Self-propulsion therefore provides an expensive but necessary mechanism for inducing assembly when time is of the essence.