Nonequilibrium associative retrieval of multiple stored self-assembly targets.

摘要: Many biological systems rely on the ability to self-assemble different target structures using same set of components. Equilibrium self-assembly suffers from a limited capacity in such cases, due an increasing number decoy states that grows rapidly with targets encoded. Moreover, improving kinetic stability at equilibrium carries price introducing traps, leading slower assembly. Using toy physical model interacting particles, we demonstrate local driving can improve both assembly time and multitarget self-assembly, as well reduce fluctuations around configuration. We further show drive result steady-state probability distribution over deviates Boltzmann way depends types interactions stabilize targets. Our results illustrate role nonequilibrium plays overcoming tradeoffs are inherent assemblies.