Two terminal devices that exhibit resistance switching in response to an external voltage are interesting for neuromorphic computing applications. Owing to its simple device structure, a crossbar array of two‐terminal resistance switching devices is highly desired for application as artificial neural network weights. Here, ferroelectric diodes that show resistance switching in their forward bias are presented. The resistance can be set to a high‐ and a low‐resistance state or any state between these limits. It is demonstrated that the ferroelectric diodes can function as an artificial synapse. An array of the ferroelectric diodes with two bit and two row lines (2 × 2) is demonstrated. The resistance of every bit is independently tuned, and spike‐time‐dependent plasticity is shown for the array.
Soft vibrotactile devices have the potential to expand the functionality of emerging electronic skin technologies. However, those devices often lack the necessary overall performance, sensing-actuation feedback and control, and mechanical compliance for seamless integration on the skin. Here, we present soft haptic electromagnetic actuators that consist of intrinsically stretchable conductors, pressure-sensitive conductive foams, and soft magnetic composites. To minimize joule heating, high-performance stretchable composite conductors are developed based on in situ-grown silver nanoparticles formed within the silver flake framework. The conductors are laser-patterned to form soft and densely packed coils to further minimize heating. Soft pressure-sensitive conducting polymer-cellulose foams are developed and integrated to tune the resonance frequency and to provide internal resonator amplitude sensing in the resonators. The above components together with a soft magnet are assembled into soft vibrotactile devices providing high-performance actuation combined with amplitude sensing. We believe that soft haptic devices will be an essential component in future developments of multifunctional electronic skin for future human−computer and human−robotic interfaces.
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