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Selected Methods for Field-Controlled Reconfiguration of Soft-Mat.pdf (51.43 MB)

Selected Methods for Field-Controlled Reconfiguration of Soft-Matter Electrical Contacts

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posted on 2017-05-01, 00:00 authored by James P. Wissman

Just as conventional mechatronic systems rely on switches and relays, machines that are soft and elastically deformable will require compliant materials that can support field-controlled reconfiguration. In this dissertation, I present several novel approaches to shape programmability that primarily rely on condensed soft matter and are stimulated by electric or magnetic fields. I begin with electric-field-driven methods for achieving shape programmability of elastomer-based systems. These include dielectric elastomer actuators and electrostatic beams that undergo extreme stretch. Classical theories in elasticity and electrostatics are used to examine the mechanical responses and instabilities of these soft, hyperelastic systems. Such modeling techniques are also used to examine another switching mode based on the snap through behavior of a buckled ferromagnetic beam under magnetic load. I will then discuss a unique approach to shape programmability that is based on electrochemistry and exploits the coalescence and separation of anchored liquid metal drops. In this case, electrical signals under 10V are utilized to manipulate surface energies and transition between bi-stable states. Experiments and Surface Evolver simulations show that oxidation and reduction on opposing poles of the coalesced drops create an interfacial tension gradient that eventually leads to limit-point instability. Theory derived from bipolar electrochemistry and vertical electrical sounding predicts droplet motion and separation based on geometry and bath conductivity, facilitating the optimization of reconfigurable devices using this phenomenon. I conclude with the application of the bi-stable droplets to a simple toggle switch capable of changing circuit conductivity by over three orders of magnitude.

History

Date

2017-05-01

Degree Type

  • Dissertation

Department

  • Mechanical Engineering

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Carmel Majidi

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