IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-28696-9.html
   My bibliography  Save this article

Sequential metamaterials with alternating Poisson’s ratios

Author

Listed:
  • Amin Farzaneh

    (University of California, Los Angeles)

  • Nikhil Pawar

    (University of California, Los Angeles)

  • Carlos M. Portela

    (Massachusetts Institute of Technology)

  • Jonathan B. Hopkins

    (University of California, Los Angeles)

Abstract

Mechanical metamaterials have been designed to achieve custom Poisson’s ratios via the deformation of their microarchitecture. These designs, however, have yet to achieve the capability of exhibiting Poisson’s ratios that alternate by design both temporally and spatially according to deformation. This capability would enable dynamic shape-morphing applications including smart materials that process mechanical information according to multiple time-ordered output signals without requiring active control or power. Herein, both periodic and graded metamaterials are introduced that leverage principles of differential stiffness and self-contact to passively achieve sequential deformations, which manifest as user-specified alternating Poisson’s ratios. An analytical approach is provided with a complementary software tool that enables the design of such materials in two- and three-dimensions. This advance in design capability is due to the fact that the tool computes sequential deformations more than an order of magnitude faster than contemporary finite-element packages. Experiments on macro- and micro-scale designs validate their predicted alternating Poisson’s ratios.

Suggested Citation

  • Amin Farzaneh & Nikhil Pawar & Carlos M. Portela & Jonathan B. Hopkins, 2022. "Sequential metamaterials with alternating Poisson’s ratios," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28696-9
    DOI: 10.1038/s41467-022-28696-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-28696-9
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-28696-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yingpeng Wu & Ningbo Yi & Lu Huang & Tengfei Zhang & Shaoli Fang & Huicong Chang & Na Li & Jiyoung Oh & Jae Ah Lee & Mikhail Kozlov & Alin C. Chipara & Humberto Terrones & Peishuang Xiao & Guankui Lon, 2015. "Three-dimensionally bonded spongy graphene material with super compressive elasticity and near-zero Poisson’s ratio," Nature Communications, Nature, vol. 6(1), pages 1-9, May.
    2. Larry L. Howell, 2018. "Complex mechanical motion guided without external control," Nature, Nature, vol. 561(7724), pages 470-471, September.
    3. Yuanping Song & Robert M. Panas & Samira Chizari & Lucas A. Shaw & Julie A. Jackson & Jonathan B. Hopkins & Andrew J. Pascall, 2019. "Additively manufacturable micro-mechanical logic gates," Nature Communications, Nature, vol. 10(1), pages 1-6, December.
    4. Corentin Coulais & Alberico Sabbadini & Fré Vink & Martin Hecke, 2018. "Multi-step self-guided pathways for shape-changing metamaterials," Nature, Nature, vol. 561(7724), pages 512-515, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jinhao Zhang & Mi Xiao & Liang Gao & Andrea Alù & Fengwen Wang, 2023. "Self-bridging metamaterials surpassing the theoretical limit of Poisson’s ratios," Nature Communications, Nature, vol. 14(1), pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Meng Li & Nifang Zhao & Anran Mao & Mengning Wang & Ziyu Shao & Weiwei Gao & Hao Bai, 2023. "Preferential ice growth on grooved surface for crisscross-aligned graphene aerogel with large negative Poisson’s ratio," Nature Communications, Nature, vol. 14(1), pages 1-9, 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. 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.
    5. Peng, Zhen & Adam, Zachary R., 2024. "Two mechanisms for the spontaneous emergence, execution, and reprogramming of chemical logic circuits," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    6. 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.
    7. Jinhao Zhang & Mi Xiao & Liang Gao & Andrea Alù & Fengwen Wang, 2023. "Self-bridging metamaterials surpassing the theoretical limit of Poisson’s ratios," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    8. Tie Mei & Chang Qing Chen, 2023. "In-memory mechanical computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    9. 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.
    10. Lei Zhuang & De Lu & Jijun Zhang & Pengfei Guo & Lei Su & Yuanbin Qin & Peng Zhang & Liang Xu & Min Niu & Kang Peng & Hongjie Wang, 2023. "Highly cross-linked carbon tube aerogels with enhanced elasticity and fatigue resistance," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    11. Jiefeng Sun & Elisha Lerner & Brandon Tighe & Clint Middlemist & Jianguo Zhao, 2023. "Embedded shape morphing for morphologically adaptive robots," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    12. Lorenzo Castelli & Qing Zhu & Trevor J. Shimokusu & Geoff Wehmeyer, 2023. "A three-terminal magnetic thermal transistor," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28696-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.