Robo-Matter towards reconfigurable multifunctional smart materials
Maximizing materials utilization efficiency via enhancing their reconfigurability and multifunctionality offers a promising avenue in addressing the global challenges in sustainability. To this end, significant efforts have been made in developing reconfigurable multifunctional smart materials, which can exhibit remarkable behaviors such as morphing and self-healing. However, the difficulty in efficiently manipulating and controlling matter at the building block level with manageable cost and complexity, which is crucial to achieving superior responsiveness to environmental clues and stimuli, has significantly hindered the further development of such smart materials. Here we introduce a concept of Robo-Matter, which can be activated and controlled through external information exchange at the building block level, to enable a high-level of controllability, mutability and versatility for reconfigurable multifunctional smart materials. Using specially designed micro-robot building blocks with symmetry-breaking active motion modes, tunable anisotropic interactions, and interactive coupling with a programmable spatial-temporal dynamic light field, we demonstrate an emergent Robot-Matter duality, which enables a spectrum of desirable behaviors spanning from matter-like properties such as ultra-fast self-assembly and adaptivity, to robot-like properties including active force output, smart healing, smart morphing and infiltration. Our work demonstrates a promising direction for designing next-generation smart materials and large-scale robotic swarms.
Authors
- Baohua Ji (ORCID: https://orcid.org/0000-0002-0092-6562)
- Fangfu Ye (ORCID: https://orcid.org/0000-0003-1279-105X)
- Xingyu Ma (ORCID: https://orcid.org/0000-0001-5268-5169)
- Yang Jiao (ORCID: https://orcid.org/0000-0001-6501-8787)
- Jianwei Shuai (ORCID: https://orcid.org/0000-0002-8712-0544)
- Mingcheng Yang (ORCID: https://orcid.org/0000-0002-8742-9277)
- Huaicheng Chen (ORCID: https://orcid.org/0000-0001-7308-9833)
- Jin Wang (ORCID: https://orcid.org/0000-0002-2841-4913)
- Jing Wang (ORCID: https://orcid.org/0009-0007-9352-2850)
- Wang Gao (ORCID: https://orcid.org/0000-0003-0331-2299)
- Peilong Wang (ORCID: https://orcid.org/0000-0003-1585-2727)
- Yanping Liu (ORCID: https://orcid.org/0000-0002-0768-1190)
- Xiangyu Xu (ORCID: https://orcid.org/0000-0002-9305-5830)
- Liyu Liu (ORCID: https://orcid.org/0000-0001-9784-8240)
- Daming Yuan (ORCID: https://orcid.org/0000-0002-9763-5306)
- Zhengdong Cheng
Institutions
- Chongqing University (CN)
- Chinese Academy of Sciences (CN)
- Institute of Physics (CN)
- University of Chinese Academy of Sciences (CN)
- Chongqing University of Technology (CN)
- Arizona State University (US)
- Stony Brook University (US)
- Zhejiang University (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1038/s41467-024-53123-6
- Citations
- 26
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 5.53
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- China Postdoctoral Science Foundation
- University of Chinese Academy of Sciences
- Wenzhou Institute of Biomaterials and Engineering