4.8 Article

Graphene-based bimorphs for micron-sized, autonomous origami machines

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1712889115

关键词

origami; graphene; bimorph; self-folding; atomic membranes

资金

  1. Cornell Center for Materials Research Grant [DMR-1719875]
  2. National Science Foundation (NSF) Major Research Instrumentation Award [DMR-1429155]
  3. NSF [DMR-1435829, ECCS-0335765]
  4. Air Force Office of Scientific Research (AFSOR) multidisciplinary research program of the university research initiative [FA2386-13-1-4118]
  5. Kavli Institute at Cornell for Nanoscale Science

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Origami-inspired fabrication presents an attractive platform for miniaturizing machines: thinner layers of folding material lead to smaller devices, provided that key functional aspects, such as conductivity, stiffness, and flexibility, are persevered. Here, we show origami fabrication at its ultimate limit by using 2D atomic membranes as a folding material. As a prototype, we bond graphene sheets to nanometer-thick layers of glass to make ultrathin bimorph actuators that bend to micrometer radii of curvature in response to small strain differentials. These strains are two orders of magnitude lower than the fracture threshold for the device, thus maintaining conductivity across the structure. By patterning 2-mu m-thick rigid panels on top of bimorphs, we localize bending to the unpatterned regions to produce folds. Although the graphene bimorphs are only nanometers thick, they can lift these panels, the weight equivalent of a 500-nm-thick silicon chip. Using panels and bimorphs, we can scale down existing origami patterns to produce a wide range of machines. These machines change shape in fractions of a second when crossing a tunable pH threshold, showing that they sense their environments, respond, and perform useful functions on time and length scales comparable with microscale biological organisms. With the incorporation of electronic, photonic, and chemical payloads, these basic elements will become a powerful platform for robotics at the micrometer scale.

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