Novel Multi Agent Models for Chemical Self-assembly

TL;DR

This paper introduces a novel multi-agent model for chemical self-assembly using Lennard-Jones potential, proposing an optimal control scheme to enhance assembly quality and analyzing convergence to stability.

Contribution

It presents a new multi-agent framework for chemical self-assembly with an optimal control approach and theoretical convergence analysis.

Findings

Control scheme improves self-assembly product quality

Model converges to stable configurations without noise

Numerical solutions demonstrate effectiveness of the approach

Abstract

The chemical self-assembly has been considered as one of most important scientific problems in the 21th Century; however, since the process of self-assembly is very complex, there is few mathematic theory for it currently. This paper provides a novel multi-agent model for chemical self-assembly, where the interaction between agents adopts the classic Lennard-Jones potential. Under this model, we propose an optimal problem by taking the temperature as the control input, and choosing the internal energy as the optimal object. A numerical solution for our optimal problem is also developed. Simulations show that our control scheme can improve the product of self-assembly. Further more, we give a strict analysis for the self-assembly model without noise, which corresponds to an attraction-repulsion multi-agent system, and prove it converges to a stable configuration eventually.