Liquid Crystal Elastomer Lattices with Thermally Programmable Deformation via Multi-Material 3D Printing.

An integrated design, modeling, and multi-material 3D printing platform for fabricating liquid crystal elastomer (LCE) lattices in both homogeneous and heterogeneous layouts with spatially programmable nematic director order and local composition is reported. Depending on their compositional topology, these lattices exhibit different reversible shape-morphing transformations upon cycling above and below their respective nematic-to-isotropic transition temperatures. Further, it is shown that there is good agreement between their experimentally observed deformation response and model predictions for all LCE lattice designs evaluated. Lastly, an inverse design model is established and the ability to print LCE lattices with the predicted deformation behavior is demonstrated. This work opens new avenues for creating architected LCE lattices that may find potential application in energy-dissipating structures, microfluidic pumping, mechanical logic, and soft robotics.

Efficient automatic design of robots.

Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior. Despite this, almost every detail of every robot built to date has been manually determined by a human designer after several months or years of iterative ideation, prototyping, and testing. Inspired by evolutionary design in nature, the automated design of robots using evolutionary algorithms has been attempted for two decades, but it too remains inefficient: days of supercomputing are required to design robots in simulation that, when manufactured, exhibit desired behavior. Here we show de novo optimization of a robot's structure to exhibit a desired behavior, within seconds on a single consumer-grade computer, and the manufactured robot's retention of that behavior. Unlike other gradient-based robot design methods, this algorithm does not presuppose any particular anatomical form; starting instead from a randomly-generated apodous body plan, it consistently discovers legged locomotion, the most efficient known form of terrestrial movement. If combined with automated fabrication and scaled up to more challenging tasks, this advance promises near-instantaneous design, manufacture, and deployment of unique and useful machines for medical, environmental, vehicular, and space-based tasks.