Steering Colloids using Chemical Gradients

Dynamically programmable colloidal materials (DPCMs) are an emerging class of materials that change their structure based on external stimuli. With the correct programming, DPCMs could be influenced to self-assemble into arbitrary structures currently unattainable, with applications in photonics, tissue engineering, and nanorobotics. However, realizing such applications requires spatiotemporal control of colloids to a combined precision and scale that is currently unattainable. Inspired by the complex systems of feedback control and non-equilibrium chemical signals in biological systems, it has been suggested that colloidal particles can be controlled using internal chemical feedback loops. By combining this idea of chemical feedback with previous microfluidics research that steers colloidal particles with an electric field, we have devised a new method of steering colloidal particles using externally applied chemical gradients. This is intended as a stepping-off point for future systems that assemble using internal feedback. Our simulations use model predictive control to steer colloidal particles on various trajectories using a chemical solute gradient. We have also derived design rules that illustrate the constraints on controlling colloidal particles using chemical gradients.