Abstract
Chemical waves represent one of the fundamental behaviors that emerge in nonlinear, out-of-equilibrium chemical systems. They also play a central role in regulating behaviors and development of biological organisms. Nevertheless, understanding their properties and achieving their rational synthesis remains challenging. In this work, we obtained traveling chemical waves using synthetic organic molecules. To accomplish this, we ran a thiol-based reaction network in an unstirred flow reactor. Our observations revealed single or multiple waves moving in either the same or opposite directions, a behavior controlled by the geometry of our reactor. A numerical model can fully reproduce this behavior using the proposed reaction network. To better understand the formation of waves, we varied the diffusion coefficient of the fast inhibitor component of the reaction network by attaching polyethylene glycol tails with different lengths to maleimide and studied how these changes affect the properties of the waves and conditions for their sustained production. These studies point towards the importance of the molecular titration network motif in controlling the production of chemical waves in this system. Furthermore, we used machine learning (ML) tools to identify phase boundaries for classes of dynamic behaviors of this system, thus demonstrating the applicability of ML tools for the study of experimental nonlinear reaction-diffusion systems.