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High-throughput microrheology and simple viscosity modeling can be used to continuously monitor the kinetic evolution of polymer molecular weight during controlled polymerizations. 

The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically. 

The fully automated fabrication of robots has long been a holy grail with the potential to revolutionize various industries, including manufacturing, construction, disaster relief, and space exploration. 3D printing offers a promising approach to automation, but the ability to print entire, complex robots with multiple materials remains limited. Previous approaches have simplified robot manufacturing by using fluidic control circuits, but these rely on labor‐intensive methods like silicone molding and manual assembly, limiting accessibility and replicability. Recent work, including this work, has demonstrated 3D‐printed robotic grippers and crawlers with embedded control circuits, but generating cyclic control outputs for legged locomotion in rough terrain remains challenging. This study addresses the challenge with a monolithic 3D‐printable four‐phase bistable oscillating valve, capable of generating coordinated motion of multiple limbs from a steady source of pressurized air. The ability of the oscillator to control an electronics‐free autonomous legged robot capable of walking on rough terrain, which can be fully fabricated on a desktop 3D printer without postassembly is demonstrated. The robot is operational immediately upon connection to an air supply. This development marks a significant step toward accessible, customizable, and biodegradable autonomous soft robots that can be produced using desktop 3D printers with no human intervention.