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Digital logic gates in soft, conductive mechanical metamaterials

Author

Listed:
  • Charles El Helou

    (The Pennsylvania State University)

  • Philip R. Buskohl

    (Materials and Manufacturing Directorate, Air Force Research Laboratory)

  • Christopher E. Tabor

    (Materials and Manufacturing Directorate, Air Force Research Laboratory)

  • Ryan L. Harne

    (The Pennsylvania State University)

Abstract

Integrated circuits utilize networked logic gates to compute Boolean logic operations that are the foundation of modern computation and electronics. With the emergence of flexible electronic materials and devices, an opportunity exists to formulate digital logic from compliant, conductive materials. Here, we introduce a general method of leveraging cellular, mechanical metamaterials composed of conductive polymers to realize all digital logic gates and gate assemblies. We establish a method for applying conductive polymer networks to metamaterial constituents and correlate mechanical buckling modes with network connectivity. With this foundation, each of the conventional logic gates is realized in an equivalent mechanical metamaterial, leading to soft, conductive matter that thinks about applied mechanical stress. These findings may advance the growing fields of soft robotics and smart mechanical matter, and may be leveraged across length scales and physics.

Suggested Citation

  • Charles El Helou & Philip R. Buskohl & Christopher E. Tabor & Ryan L. Harne, 2021. "Digital logic gates in soft, conductive mechanical metamaterials," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21920-y
    DOI: 10.1038/s41467-021-21920-y
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    Cited by:

    1. Tie Mei & Zhiqiang Meng & Kejie Zhao & Chang Qing Chen, 2021. "A mechanical metamaterial with reprogrammable logical functions," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    2. Wenzhong Yan & Shuguang Li & Mauricio Deguchi & Zhaoliang Zheng & Daniela Rus & Ankur Mehta, 2023. "Origami-based integration of robots that sense, decide, and respond," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Tie Mei & Chang Qing Chen, 2023. "In-memory mechanical computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Xinyu Hu & Ting Tan & Benlong Wang & Zhimiao Yan, 2023. "A reprogrammable mechanical metamaterial with origami functional-group transformation and ring reconfiguration," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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