Thermodynamic speed limits as a design principle for dissipative materials

Whether living or synthetic, systems that can function dynamically must also pay the price of energy dissipation and entropy production. For example, chemically active hydrogels have the potential to power motion and create fibrous structures in a fixed amount of time. However, chemical reaction networks at the molecular scale control the transient and dissipative assembly of fibers at the mesoscale. Because of this strong connection across scales, it is challenging to predict the efficiency of the material function and its timed execution. In this talk, I will discuss thermodynamic speed limits on dissipation as a possible design principle that balances the tradeoff between efficiency and speed across length and timescales. These bounds have theoretical connections to regression analysis and, therefore, existing machine learning techniques, making them a possible theoretical device to optimize energy efficiency and timed structure formation in dissipative materials.