| Abstract: omplex cellular behaviors such as motion and division are directed by far-from-equilibrium chemical reaction networks that regulate self-assembly, driving a cell to states that, without control by these networks, would be totally inaccessible. Could one design analogous chemical networks to control the dynamic behavior of synthetic materials? To do so, we must understand the dynamics of coupled reaction and assembly processes.
By coupling simple relatively simple chemical reactions to self-assembly processes, one can impose feedback regulation or trap materials in chosen metastable states. More complex networks could switch materials between many different metastable states, and guide the transitions between them. Using an example of shape change in soft hydrogels films, I will discuss how we might construct “programmable” DNA and enzyme networks that can drive such multistate switching. These “genelet” networks, simplified analogs of genetic regulatory networks, are composed of interchangeable parts, such that they can emulate the dynamics of a large class of feedforward and recurrent artificial neural networks. They can also faithfully propagate and amplify information, and handle the load imposed by when they are coupled to an assembly process. Genelet networks could thus allow us to explore a broad range of dynamic material behaviors by design. |