Multistable mechanical metamaterials are artificial materials whose microarchitectures offer more than two different stable configurations. Existing multistable mechanical metamaterials mainly rely on origami/kirigami-inspired designs, snap-through instability, and microstructured soft mechanisms, with mostly bistable fundamental unit cells. Scalable, tristable structural elements that can be built up to form mechanical metamaterials with an extremely large number of programmable stable configurations remains illusive. Here, we harness the elastic tensile/compressive asymmetry of kirigami microstructures to design a class of scalable X-shaped tristable structures. Using these structure as building block elements, hierarchical mechanical metamaterials with one-dimensional (1D) cylindrical geometries, 2D square lattices, and 3D cubic/octahedral lattices are designed and demonstrated, with capabilities of torsional multistability or independent controlled multidirectional multistability. The number of stable states increases exponentially with the cell number of mechanical metamaterials. The versatile multistability and structural diversity allow demonstrative applications in mechanical ternary logic operators and amplitude modulators with unusual functionalities.
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http://dx.doi.org/10.1126/sciadv.abf1966 | DOI Listing |
Wearable Technol
December 2024
Robotics Research Centre, School of Mechanical and Aerospace Engineering, NTU, Singapore.
Pathological tremors can often be debilitating to activities of daily living and significantly affect the quality of life. Such tremulous movements are commonly observed in wrist flexion-extension (FE). To suppress this tremor we present a wearable robot (WR) with a customized mechanical metamaterial (MM) as the physical human-robot interface (pHRI).
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January 2025
State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China.
Higher-order DNA nanomaterials have emerged as programmable tools for probing biological processes, constructing metamaterials, and manipulating mechanically active nanodevices with the multifunctionality and high-performance attributes. However, their utility is limited by intricate mixtures formed during hierarchical multistage assembly, as standard techniques like gel electrophoresis lack the resolution and applicability needed for precise characterization and enrichment. Thus, it is urgent to develop a sorter that provides high separation resolution, broad scope, and bioactive functionality.
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January 2025
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China.
This research presents a method based on deep learning for the reverse design of sound-absorbing structures. Traditional methods require time-consuming individual numerical simulations followed by cumbersome calculations, whereas the deep learning design method significantly simplifies the design process, achieving efficient and rapid design objectives. By utilizing deep neural networks, a mapping relationship between structural parameters and the sound absorption coefficient curve is established.
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January 2025
Mechanical Engineering, Stanford University, Stanford, CA, 94305, USA.
Triply periodic minimal surface (TPMS) metamaterials show promise for thermal management systems but are challenging to integrate into existing packaging with strict mechanical requirements. Composite TPMS lattices may offer more control over thermal and mechanical properties through material and geometric tuning. Here, we fabricate copper-plated, 3D-printed triply periodic minimal surface primitive lattices and evaluate their suitability for battery thermal management systems.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Faculty of Mechanical Engineering, Poznan University of Technology, Piotrowo 3 Street, 61-138 Poznan, Poland.
This paper is dedicated to the analysis of a foot prosthesis optimization process, with a particular focus on the application of optimization algorithms and unconventional materials, such as auxetic materials. The study aims to enhance prosthesis performance by minimizing the difference between the ground reaction force generated by the prosthetic foot and that of a natural limb. In the initial part of the study, the basic topics concerning the parameterization of the foot prosthesis geometry and the preparation of a finite element model for human gait are discussed.
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