A mean field thermodynamic framework for time dependent self-assembly and pattern formation

TL;DR

This paper introduces a mean-field thermodynamic framework to predict and control the self-assembly of spatial patterns in materials driven by time-dependent external forces, linking entropy production to pattern reliability.

Contribution

It presents a novel thermodynamic model for time-dependent self-assembly, providing guidelines for controlling pattern formation under dynamic conditions.

Findings

Predicts conditions for reliable pattern self-assembly

Links entropy production to pattern encoding accuracy

Applicable to complex self-assembly scenarios

Abstract

In this work, we use a minimal model to introduce a framework for controlling self-assembly under the influence of time-dependent driving forces. We develop a mean-field thermodynamic framework that predicts the conditions required to reliably self-assemble a desired spatial pattern under time-varying external fields. We also calculate the entropy production associated with the time-dependent self-assembly process and examine how it can be used to predict conditions under which the external time-varying signal is reliably encoded as a spatial pattern in the self-assembling material. While the results in this work are developed in the context of a minimal one-dimensional model, we anticipate that the framework can be used to establish guidelines for controlling self-assembly in more complex scenarios.