Shuai Mo , Zurui Huang , Yiheng Liu , Haruo Houjoh , Wei Zhang
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引用次数: 0
Abstract
The use of intelligent materials is anticipated in various fields such as medicine, science, and the military. In this context, the development of programmable metamaterials with in-situ continuously adjustable mechanical properties holds significant importance for the advancement of smart materials. Here we propose a novel approach to constructing mechanical metamaterials using gears as the fundamental building blocks. The gear-based metamaterials we introduce is a multi-stable structure that allows for seamless transitions between stable states by engaging the gear teeth. This unique feature enables the metamaterials to possess in situ continuously adjustable mechanical properties, including a wide range of compressive Young's modulus, variable generalized shear stiffness, and tunable dynamic characteristics of the system, and both simulations and experiments are used to validate the metamaterial designs. These unique properties of gear-based metamaterials offer a novel path to creating programmable metamaterials with in situ continuously tunable mechanical properties.
期刊介绍:
The International Journal of Non-Linear Mechanics provides a specific medium for dissemination of high-quality research results in the various areas of theoretical, applied, and experimental mechanics of solids, fluids, structures, and systems where the phenomena are inherently non-linear.
The journal brings together original results in non-linear problems in elasticity, plasticity, dynamics, vibrations, wave-propagation, rheology, fluid-structure interaction systems, stability, biomechanics, micro- and nano-structures, materials, metamaterials, and in other diverse areas.
Papers may be analytical, computational or experimental in nature. Treatments of non-linear differential equations wherein solutions and properties of solutions are emphasized but physical aspects are not adequately relevant, will not be considered for possible publication. Both deterministic and stochastic approaches are fostered. Contributions pertaining to both established and emerging fields are encouraged.