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  1. We propose a design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape describing the collective interactions of the machine components. This design paradigm is attractive since, near bifurcations, small variations in a few control parameters can result in large changes to the system’s state providing an emergent lever mechanism. Further, the topological configuration of transitions between states near such bifurcations ensures robust operation, making the machine less sensitive to fabrication errors and noise. To design such machines, we develop and implement a new efficient algorithm that searches for interactions between the machine components that give rise to energy landscapes with these bifurcation structures. We demonstrate a proof of concept for this approach by designing magnetoelastic machines whose motions are primarily guided by their magnetic energy landscapes and show that by operating near bifurcations we can achieve multiple transition pathways between states. This proof of concept demonstration illustrates the power of this approach, which could be especially useful for soft robotics and at the microscale where typical macroscale designs are difficult to implement.

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    Free, publicly-accessible full text available August 22, 2024
  2. Microscopic robots controlled by onboard integrated circuits that walk when powered by light are realized. 
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  3. null (Ed.)
  4. Shape-memory actuators allow machines ranging from robots to medical implants to hold their form without continuous power, a feature especially advantageous for situations where these devices are untethered and power is limited. Although previous work has demonstrated shape-memory actuators using polymers, alloys, and ceramics, the need for micrometer-scale electro–shape-memory actuators remains largely unmet, especially ones that can be driven by standard electronics (~1 volt). Here, we report on a new class of fast, high-curvature, low-voltage, reconfigurable, micrometer-scale shape-memory actuators. They function by the electrochemical oxidation/reduction of a platinum surface, creating a strain in the oxidized layer that causes bending. They bend to the smallest radius of curvature of any electrically controlled microactuator (~500 nanometers), are fast (<100-millisecond operation), and operate inside the electrochemical window of water, avoiding bubble generation associated with oxygen evolution. We demonstrate that these shape-memory actuators can be used to create basic electrically reconfigurable microscale robot elements including actuating surfaces, origami-based three-dimensional shapes, morphing metamaterials, and mechanical memory elements. Our shape-memory actuators have the potential to enable the realization of adaptive microscale structures, bio-implantable devices, and microscopic robots.

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