Phase Changing Materials-Based Variable-Stiffness Tensegrity Structures

Zappetti, Davide; Jeong, Seung Hee; Shintake, Jun; Floreano, Dario

doi:10.1089/soro.2019.0091

Cited by 51 publications

(33 citation statements)

References 29 publications

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“…Because of the complex structure of porous materials, the stiffness simulation of porous materials is usually realized by some software like COMSOL [ 82 ] and NASA Tensegrity Robotic Toolkit. [ 93 ] By inputting the structure and properties of material and computing parameters, how loading conditions or structure affect the stiffness can be predicted. Though the effective numerical modeling for the mechanical properties of the core–shell structure is still lacking, for some structurally simple hollow lattices, some works use classic first‐order scaling model to calculate the effective yield strength of lattice material, [ 86 ] expressed as,

\begin{matrix} σ_{eff} = C {\overset{ρ}{true}}^{a} σ_{normals} \end{matrix}

where σ eff and σ s represent the effective yield strength of hollow lattice materials and intrinsic strength of the material, respectively.…”

Section: Structures Of Lmpa‐enabled Stiffness Tunable Materialsmentioning

confidence: 99%

Low Melting Point Alloys Enabled Stiffness Tunable Advanced Materials

Hao

Gao

et al. 2022

Adv Funct Materials

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Stiffness tunable advanced materials have demonstrated their superiority and versatility in diverse areas, while the global pursuit of reversible, intelligent, and fast response for stiffness regulation is growing radically, leaving great challenges for traditional materials. As newly emerging functional metal material, the low melting point alloys (LMPAs) have shown encouraging potential in developing various stiffness regulation strategies owing to their excellent physicochemical and mechanical properties. This article is dedicated to presenting a comprehensive review of the LMPA‐enabled stiffness tunable materials from the aspects of material system, regulation principle and method, capability enabling mechanisms, and application scenarios. First, according to the structural differences, three kinds of LMPA‐enabled stiffness tunable material systems are evaluated. Then, the regulation strategies are elaborated from the fundamental LMPA modifications to dynamical external field controls, and the mainstream stiffness regulation modes are also combed out. Following that, the diversified applications of LMPA enabled stiffness tunable materials are systematically summarized and discussed. Finally, a perspective interpretation of the potentials and challenges of LMPA‐enabled stiffness tunable materials is provided. This article is expected to be important for guiding the future design of smart materials, functional entities, transformable robots, etc.

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\begin{matrix} σ_{eff} = C {\overset{ρ}{true}}^{a} σ_{normals} \end{matrix}

where σ eff and σ s represent the effective yield strength of hollow lattice materials and intrinsic strength of the material, respectively.…”

Section: Structures Of Lmpa‐enabled Stiffness Tunable Materialsmentioning

confidence: 99%

Low Melting Point Alloys Enabled Stiffness Tunable Advanced Materials

Hao

Gao

et al. 2022

Adv Funct Materials

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“…压杆可预先编程为紧凑的形状, 在加热后再恢复笔直, 使张拉整体结构展开, 实现显著的形状变化. Zappetti 等人 [73] 在可拉伸管道中封装低熔点合金作为变刚度拉索, 设超材料是一类具有天然材料所不具备的超常物理性质的人工复合结构或材料 [75] , 其性质往往取决于内部的人工结构, 而非构成材料的本征性质. 超材料的基本组成单位称为胞元, 剪纸结构、折纸结构、张拉整体结构和多稳态结构等都可以作为超材料胞元.…”

Section: 材料物理智能unclassified

“…Lee 等人 [55] 剪纸结构抓手 [67] ; (c) 软体气动双稳态阀, 可组合形成全软气动数字逻辑门(与或非) [70] ; (d) 变刚度张拉整体结构 [73] ; (e) 能够向任意方向行走的张拉整体超材料软体机器人 [55] Origami-inspired self-folding crawling robot [64] ; (b) Kirigami gripper [67] ; (c) Soft pneumatic bistable valve, which can be combined to generate completely soft pneumatic digital logic gates (OR, AND, and NOT) [70] ; (d) Variable-stiffness tensegrity structures [73] ; (e) Soft robot made of tensegrity metamaterials capable of walking in any direction [55] 2.2.3 形态物理智能对于固定形态的机器人而言, 通过纯控制器优化的行为适应只能提供有限的适应性. 自适应形态提供了额外的自由度, 增加了机器人对环境和任务变化的适应性, 无需每次遇到新的环境或任务时都重新设计和制作.…”

Section: 材料物理智能unclassified

“…A c c e p t e d https://engine.scichina.com/doi/10.1360/TB-2021-1217 以实现更集成与一体化的的物理智能. 例如, 将形状记忆聚合物与折纸结构相结合 [64] , 液晶聚合物网络与剪纸结构相结合 [66] , 形状记忆聚合物与双稳态结构相结合 [118] , 形状记忆聚合物 [72] 、低熔点合金 [73] 、液晶弹性体-碳纳米管复合材料 [74] 与张拉整体结构相结合, 软磁复合材料与超材料相结合 [55] 等. 将智能材料、智能结构和智能形态三者有机融合在软体机器人系统中无疑会大幅提升其物理智能的水平.…”

Section: 物理智能系统集成目前越来越多的研究将智能材料与智能结构结合在一起融合力学和材料科学的前沿unclassified

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Bio-inspired physical intelligence for soft robotics

Wang¹,

Xie²,

Yuan³

et al. 2022

Chin. Sci. Bull.

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and structure, self-learning, self-healing, and self-decision-making into physical bodies of the biological or robotic agents. Physical intelligence can also be generated during the interaction between the agent's body and the environment over time. The previous focus of intelligent robots is primarily focused on the computational intelligence. As a new paradigm, physical intelligence is expected to boost intelligent robots in real-world applications.Soft robots commonly use soft stimuli-responsive materials and intelligent structures and maintain high stretchability and considerable deformation, therefore, have intrinsic environmental conformable physical property. Thus, soft robots are essential platforms for testing hypothesis of physical intelligence in nature. This review mainly focused on three key physical intelligence elements encoded in the natural organisms' bodies: material, structure, and morphology. Through bio-inspired design, smart soft materials, smart soft structures, and adaptable morphologies can be integrated into the robot's body, thus introducing bio-inspired physical intelligence into the robots. By integrating bio-inspired physical intelligence, soft robots could reduce the cost of control, improve the response speed of the systems, enhance the robustness of robots in extreme environments, and embed intelligence into the micro-and small-scale robots. The research on bio-inspired physical intelligence A c c e p t e d https://engine.scichina.com/doi/10.1360/TB-2021-1217 may also promote the multi-disciplinary collaboration of biology, robotics, materials science, chemistry, computer science, etc.In this review, we first describe the characteristics and principles of physical intelligence in natural organisms' material, structure, and morphology. Then we introduce the purposes and related key technologies and methods of realizing bio-inspired physical intelligence of soft robots. Furthermore, we enumerate the typical applications of bio-inspired physical intelligence of soft robots. Finally, we highlight the trends and challenges of bio-inspired physical intelligence of soft robots in the future.The research on bio-inspired physical intelligence for soft robots is still in the primary stage. There are several critical questions and challenges to be addressed. First, researchers should investigate the basic principles of physical intelligence in biomechanics and then apply the basic principles to guide the development of soft robots. Second, intelligent materials need to meet the challenges of fully integrating sensing, actuation, memory, computation, and communication in soft robots. To this end, an interesting approach is to use stimulus-responsive materials as the basic building blocks to rationally design and integrate different functions into a single composite material. Third, smart structures, like mechanical metamaterials can be a promising research direction in the field of intelligent structures for soft robots. Aided by artificial intelligence and 3D printing, mechanical metamateria...

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“…Liquid metal, gallium-based alloy, is an attractive conductor, because it is inherently stretchable while maintaining metallic conductivity. [2] Liquid metal spontaneously forms native oxide layer on surfaces, [3,4] thus it can be patterned into elastomeric substrates in various ways, such as injection, [5] vacuum filling into capillaries, [6] 3D printing, [7,8] and molding, [9] which processes enable the creation of stretchable antennae, [10] shape memory materials, [11][12][13][14][15] and tough composites. [16][17][18] In general, thermochromic materials are appealing, because they can be used as temperature indicators for building, chemical reactors, and anti-reflective mirrors.…”

Section: Introductionmentioning

confidence: 99%

Ultrastretchable Thermo‐ and Mechanochromic Fiber with Healable Metallic Conductivity

Sin

Singh

Bhuyan

et al. 2021

Adv Elect Materials

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This work demonstrates a facile way to fabricate ultrastretchable thermo‐ and mechanochromic fiber with healable metallic conductivity. Thermochromic hollow elastic fiber is prepared by using silicone composite with thermochromic pigment. Once the fiber forms, gallium‐based liquid metal is injected into the fiber. The composite fiber with liquid metal core shows uniform color change along the fiber by applying Joule heating through the liquid metal wire. The fiber with multiple thermochromic pigment locally distributed along the fiber shows serial color change by increased current. The healable conductivity of the metal core is demonstrated by restoring electrical conductivity near room temperature. When it is in a solid state, the wire can fracture during deformation, thus the wire loses conductivity. However, upon body heating, the wire can rewire, because of the low melting point of the metal (gallium, 29.8 °C). This healing ability of the metal core can allow the fiber to have healable thermochromic behavior. Stretching a liquid metal wire can change the geometry of the wires, resulting in a color change because of increased resistance while Joule heating is applied. This thermo‐ and mechanochromic fiber with liquid metal core would find use in wearable and conformal electronics, electronic textiles, and soft robotics.

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Phase Changing Materials-Based Variable-Stiffness Tensegrity Structures

Cited by 51 publications

References 29 publications

Low Melting Point Alloys Enabled Stiffness Tunable Advanced Materials

Low Melting Point Alloys Enabled Stiffness Tunable Advanced Materials

Bio-inspired physical intelligence for soft robotics

Ultrastretchable Thermo‐ and Mechanochromic Fiber with Healable Metallic Conductivity

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