Healable Self-assembled Magneto-elastic Networks with Robust Mechanical Properties
ORAL
Abstract
Magneto-active soft materials show significant potential in the applications of soft robotics, control systems, and waveguides due to their programmable shapes, adaptive stiffness, and tunable strength, arising from magnetic-elastic coupling. Magneto-elastic networks coming from this composite design have been fabricated by 3D printing and laser cutting techniques as a monolithic body. These architected network materials offer great energy dissipation capacity per weight under impact but the damage incurred is permanent. To overcome this, a novel magneto-elastic network that can be self-assembled from elastic elements decorated with permanent magnets under random vibrations is proposed in this work. The magneto-elastic unit configuration is shown to dictate the assembled network topology. The design criteria for those units to form mechanically robust networks are derived based on computer simulations, energetic analyses, and experimental validation. Once subjected to large conformational changes or fracturing into pieces in extreme environments, these magneto-elastic lattices can self-heal to their original functional structure by first resetting to the ground state and then reassembling. The self-assembly and self-healing properties enable them to be fabricated and repaired on-the-fly. This work combines concepts from magnetic handshake materials and thermalized granular systems with elastic network designs to understand the self-assembly, elasticity, and failure mechanisms of elastic bar elements with sticky magnetic ends. The presented work will broaden the engineering applications of magneto-elastic soft materials in the field of fatigue-free reusable protective materials and actuators.
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Publication: 1. Yang, X., and Keten, S. (July 29, 2021). "Multi-Stability Property of Magneto-Kresling Truss Structures." ASME. J. Appl. Mech. September 2021; 88(9): 091009.<br>2. Yang, X., and Keten, S. "Self-assembled Mechanically Robust 2D Networks from Magneto-elastic Bars" (Manuscript in preparation).
Presenters
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Xinyan Yang
Northwestern University
Authors
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Xinyan Yang
Northwestern University
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Sinan Keten
Northwestern University