Optimizing electrostatic cleaning for dust removal on gecko-inspired adhesives

Abstract Gecko-inspired adhesives are one of the most promising forms of controllable adhesives for a wide range of applications, especially robotic gripping, perching, and climbing. One impediment to the technology's success is the negative effect of dust and other contaminants, which can significantly decrease adhesion in real-world environments. Previous work has shown that electrostatic forces were capable of removing adhered dust on the surface of gecko-inspired adhesives and that a two-phase square wave input to the electrostatic element with the lowest possible frequency produced the highest cleaning efficiency. In this work, dust particle size, electrode geometry (electrode width and gap), duty cycle of the exciting wave, peak-peak voltage of the electrodes, and the thickness of dielectric layer (the gecko-inspired microstructures) are evaluated experimentally and in simulation. Moreover, three possible electrostatic particle removal mechanisms were modeled to explain their relative importance: repulsion, sliding, and rolling. Results indicate that the highest cleaning efficiency for all particle sizes occurs with the highest possible peak-peak voltage when the electrode width and gap are 400 μm and 300 μm, respectively. The results also show the highest cleaning efficiencies are produced using a duty cycle of 50 % on the thinnest samples of the gecko-inspired microstructures, where electrodes are closer to particles. Finally, particle sliding and particle rolling are the dominant factors in electrostatic cleaning of gecko-inspired adhesives, while particle repulsion plays a limited role.