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Tunable dry adhesion is a crucial mechanism in compliant manipulation. Thegripping force, mainly originated from the van der Waals force between theadhesive composite and the object to be gripped, can be controlled byreversibly varying the physical properties (e.g., stiffness) of the compositevia external stimuli. The maximal gripping force Fmax and its tunability dependon, among other factors, the stress distribution on the gripping interface andits fracture dynamics (during detaching), which in turn are determined by thecomposite microstructure. Here, we present a computational framework for themodeling and design of a class of binary smart composites containing a porouslow-melting-point alloy (LMPA) phase and a polymer phase, in order to achievedesirable dynamically tunable dry adhesion. In particular, we employ spatialcorrelation functions to quantify, model and represent the complexbi-continuous microstructure of the composites, from which a wide spectrum ofrealistic virtual 3D composite microstructures can be generated usingstochastic optimization. A recently developed volume-compensatedlattice-particle (VCLP) method is then employed to model the dynamicinterfacial fracture process to compute Fmax for different compositemicrostructures. We focus on the interface defect tuning (IDT) mechanism fordry adhesion tuning enabled by the composite, in which the thermal expansion ofthe LMPA phase due to Joule heating initializes small cracks on the adhesioninterface, subsequently causing the detachment of the gripper from the objectdue to interfacial fracture. We find that for an optimal microstructure amongthe ones studied here, a 10-fold dynamic tuning of Fmax before and after thethermal expansion of the LMPA phase can be achieved. Our computational resultscan provide valuable guidance for experimental fabrication of the LMPA-polymercomposites.

Microstructure Design of Low-Melting-Point Alloy (LMPA)/ Polymer Composites for Dynamic Dry Adhesion Tuning in Soft Gripping