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Abstract Tunable dry adhesion has a range of applications, including transfer printing, climbing robots, and gripping in automated manufacturing processes. Here, a novel concept to achieve dynamically tunable dry adhesion via modulation of the stiffness of subsurface mechanical elements is introduced and demonstrated. A composite post structure, consisting of an elastomer shell and a core with a stiffness that can be tuned via application of electrical voltage, is fabricated. In the nonactivated state, the core is stiff and the effective adhesion strength between the composite post and contact surface is high. Activation of the core via application of electrical voltage reduces the stiffness of the core, resulting in a change in the stress distribution and driving force for delamination at the interface and, thus a reduction in the effective adhesion strength. The adhesion of composite posts with a range of dimensions is characterized and activation of the core is shown to reduce the adhesion by as much as a factor of 6. The experimentally observed reduction in adhesion is primarily due to the change in stiffness of the core. However, the activation of the core also results in heating of the interface and this plays a secondary role in the adhesion change.
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Correlation-function-based microstructure design of alloy-polymer composites for dynamic dry adhesion tuning in soft gripping
Tunable dry adhesion is a crucial mechanism in compliant manipulation. The gripping force can be controlled by reversibly varying the physical properties (e.g., stiffness) of the composite via external stimuli. The maximal gripping force Fmaxand its tunability depend on, among other factors, the stress distribution on the gripping interface and its fracture dynamics (during detaching), which in turn are determined by the composite microstructure. Here, we present a computational framework for the modeling and design of a class of binary smart composites containing a porous low-melting-point alloy (LMPA) phase and a polymer phase, in order to achieve desirable dynamically tunable dry adhesion. We employ spatial correlation functions to quantify, model, and represent the complex bi-continuous microstructure of the composites, from which a wide spectrum of realistic virtual 3D composite microstructures can be generated using stochastic optimization. A recently developed volume-compensated lattice-particle method is then employed to model the dynamic interfacial fracture process, where the gripper is detached from the object, to compute Fmaxfor different composite microstructures. We focus on the interface defect tuning mechanism for dry adhesion tuning enabled by the composite, and find that for an optimal microstructure among the ones studied here, a tenfold dynamic tuning of Fmaxbefore and after the thermal expansion of the LMPA phase can be achieved. Our computational results can provide valuable guidance for experimental fabrication of the LMPA–polymer composites.
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- Award ID(s):
- 2020277
- PAR ID:
- 10363882
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- Journal of Applied Physics
- Volume:
- 131
- Issue:
- 11
- ISSN:
- 0021-8979
- Page Range / eLocation ID:
- Article No. 115104
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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