(55h) Programming Soft Materials Assembly Via Inverse-Design

Soft materials are crucial in many different forms of revolutionary technologies for their ability to self-assemble into intricate structures using a finite set of building blocks. Oftentimes, we can alter these building blocks with continuously tunable parameters, providing us with an almost infinite design space for potential materials properties. Because of this giant parameter space, forward approaches to sweep through parameters might not be the most efficient way to discover the building blocks for a specific material structure or property, and many inverse approaches have been developed in the past years. In this talk, I will discuss two different inverse-design strategies for building block selection for targeted assembly properties: digital alchemy, a method based on extended thermodynamics ensembles, and differentiable molecular dynamics utilizing JAX-MD. By utilizing these methods, we can inverse-design optimal particle shape for density-induced solid-solid phase transitions and best patchy particles for bulk and finite self-assembly.