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A reprogrammable mechanical metamaterial with stable memory

Author

Listed:
  • Tian Chen

    (École Polytechnique Fédérale de Lausanne
    École Polytechnique Fédérale de Lausanne)

  • Mark Pauly

    (École Polytechnique Fédérale de Lausanne)

  • Pedro M. Reis

    (École Polytechnique Fédérale de Lausanne)

Abstract

Metamaterials are designed to realize exotic physical properties through the geometric arrangement of their underlying structural layout1,2. Traditional mechanical metamaterials achieve functionalities such as a target Poisson’s ratio3 or shape transformation4–6 through unit-cell optimization7–9, often with spatial heterogeneity10–12. These functionalities are programmed into the layout of the metamaterial in a way that cannot be altered. Although recent efforts have produced means of tuning such properties post-fabrication13–19, they have not demonstrated mechanical reprogrammability analogous to that of digital devices, such as hard disk drives, in which each unit can be written to or read from in real time as required. Here we overcome this challenge by using a design framework for a tileable mechanical metamaterial with stable memory at the unit-cell level. Our design comprises an array of physical binary elements (m-bits), analogous to digital bits, with clearly delineated writing and reading phases. Each m-bit can be independently and reversibly switched between two stable states (acting as memory) using magnetic actuation to move between the equilibria of a bistable shell20–25. Under deformation, each state is associated with a distinctly different mechanical response that is fully elastic and can be reversibly cycled until the system is reprogrammed. Encoding a set of binary instructions onto the tiled array yields markedly different mechanical properties; specifically, the stiffness and strength can be made to range over an order of magnitude. We expect that the stable memory and on-demand reprogrammability of mechanical properties in this design paradigm will facilitate the development of advanced forms of mechanical metamaterials.

Suggested Citation

  • Tian Chen & Mark Pauly & Pedro M. Reis, 2021. "A reprogrammable mechanical metamaterial with stable memory," Nature, Nature, vol. 589(7842), pages 386-390, January.
  • Handle: RePEc:nat:nature:v:589:y:2021:i:7842:d:10.1038_s41586-020-03123-5
    DOI: 10.1038/s41586-020-03123-5
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    Citations

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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. Junghwan Byun & Aniket Pal & Jongkuk Ko & Metin Sitti, 2024. "Integrated mechanical computing for autonomous soft machines," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Lei Wu & Damiano Pasini, 2024. "Zero modes activation to reconcile floppiness, rigidity, and multistability into an all-in-one class of reprogrammable metamaterials," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    4. Zemin Liu & Meng Li & Xiaoguang Dong & Ziyu Ren & Wenqi Hu & Metin Sitti, 2022. "Creating three-dimensional magnetic functional microdevices via molding-integrated direct laser writing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    5. Zhou Hu & Zhibo Wei & Kun Wang & Yan Chen & Rui Zhu & Guoliang Huang & Gengkai Hu, 2023. "Engineering zero modes in transformable mechanical metamaterials," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    6. Xin Yang & Zhihe Zhang & Mengwei Xu & Shuxun Li & Yuanhong Zhang & Xue-Feng Zhu & Xiaoping Ouyang & Andrea Alù, 2024. "Digital non-Foster-inspired electronics for broadband impedance matching," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    7. Xinchen Ni & Haiwen Luan & Jin-Tae Kim & Sam I. Rogge & Yun Bai & Jean Won Kwak & Shangliangzi Liu & Da Som Yang & Shuo Li & Shupeng Li & Zhengwei Li & Yamin Zhang & Changsheng Wu & Xiaoyue Ni & Yongg, 2022. "Soft shape-programmable surfaces by fast electromagnetic actuation of liquid metal networks," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    8. 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.
    9. Tie Mei & Chang Qing Chen, 2023. "In-memory mechanical computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    10. Yaohui Wang & Haitao Ye & Jian He & Qi Ge & Yi Xiong, 2024. "Electrothermally controlled origami fabricated by 4D printing of continuous fiber-reinforced composites," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    11. Neng Xia & Dongdong Jin & Chengfeng Pan & Jiachen Zhang & Zhengxin Yang & Lin Su & Jinsheng Zhao & Liu Wang & Li Zhang, 2022. "Dynamic morphological transformations in soft architected materials via buckling instability encoded heterogeneous magnetization," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    12. 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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