Key points are not available for this paper at this time.
Natural skin receptors use ions as signal carriers, while most of the developed artificial tactile sensors utilize electrons as information carriers. To imitate the biological ionic sensing behavior, here, we present a kind of biomimetic, ionic, and fully passive mechanotransduction mechanism leveraging mechanical modulation of interfacial ionic p-n junction (IPNJ) through microchannels. Sensors based on this mechanism do not rely on an external power supply and can encode external tactile stimuli into highly analogous signal outputs to those of natural skin receptors, in terms of both signal type (i.e., ionic potential difference) and signal intensity (≈120 mV). More importantly, the instant interfacial IPNJ regulation characteristic endows the sensors with superior performance when compared to the state-of-the-art piezoionic sensors, including a low detection limit of 0.01 N, fast response/recovery speeds (16 ms/16 ms), ultralow power consumption (pW level), excellent reproducibility (over 100,000 cycles), and good capabilities to resolve both static and dynamic mechanical stimulations. As demonstrations, machine-learning-assisted high accuracy (over 99%) surface texture recognition and object classification are successfully demonstrated with the sensors integrated on robotic hands. This work enriches the family of mechanical sensing mechanisms and provides a path to mimicking natural tactile sensory systems for smart skins, artificial prostheses, and intelligent robots.
Zhang et al. (Tue,) studied this question.