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Tactile sensing plays a vital role in human somatosensory perception as it provides essential touch information necessary for interacting with the environment and accomplishing daily tasks. The progress in textile electronics has opened up opportunities for developing intelligent wearable devices that enable somatosensory perception and interaction. Herein, a skin‐inspired all‐textile pressure sensor (ATP) is presented that emulates the sensing and interaction functions of human skin, offering wearability, comfort, and breathability. The ATP demonstrates impressive features, including ultrahigh sensitivity (1.46 × 106 kPa−1), fast response time (1 ms), excellent stability and durability (over 2000 compression‐release cycles), a low detection limit of 10 Pa, and remarkable breathability (93.2%). The multipixel array of ATPs has been proven to facilitate static and dynamic mapping of spatial pressure, as well as pressure trajectory monitoring functions. Moreover, by integrating ATP with oscillation circuits, external force stimuli can be directly encoded into digital frequency pulses that resemble human physiological signals. The frequency of output pulses increases with the applied pressure. Consequently, an ATP‐based artificial sensory system is constructed for intelligent tactile perception. This work provides a simple and versatile strategy for practical applications of wearable electronics in the fields of robotics, sports science, and human–machine interfaces technologies. [ABSTRACT FROM AUTHOR]

The emulation of human multisensory functions to construct artificial perception systems is an intriguing challenge for developing humanoid robotics and cross‐modal human–machine interfaces. Inspired by human multisensory signal generation and neuroplasticity‐based signal processing, here, an artificial perceptual neuro array with visual‐tactile sensing, processing, learning, and memory is demonstrated. The neuromorphic bimodal perception array compactly combines an artificial photoelectric synapse network and an integrated mechanoluminescent layer, endowing individual and synergistic plastic modulation of optical and mechanical information, including short‐term memory, long‐term memory, paired pulse facilitation, and "learning‐experience" behavior. Sequential or superimposed visual and tactile stimuli inputs can efficiently simulate the associative learning process of "Pavlov's dog". The fusion of visual and tactile modulation enables enhanced memory of the stimulation image during the learning process. A machine‐learning algorithm is coupled with an artificial neural network for pattern recognition, achieving a recognition accuracy of 70% for bimodal training, which is higher than that obtained by unimodal training. In addition, the artificial perceptual neuron has a low energy consumption of ∼20 pJ. With its mechanical compliance and simple architecture, the neuromorphic bimodal perception array has promising applications in large‐scale cross‐modal interactions and high‐throughput intelligent perceptions. [ABSTRACT FROM AUTHOR]

User‐interactive interfaces, converting tactile stimuli into readable signals to users and devices simultaneously, improve the communication and interaction between human and machines and therefore greatly contribute to the safety and dexterity during the interactions. However, the concomitant challenges of current user‐interactive interfaces such as complex architecture, massive electrodes and fussy cable connections, bulky and unhandy power supply, and deficiency in multistimuli responses have yet to be solved. Herein, an all‐optical tactile sensing platform consisting of heterogeneous mechanoluminescent materials and polymer matrix is proposed for the conversion of multiple tactile stimuli into heterochromatic lights in an untethered and self‐powered manner. The all‐optical tactile sensing platform can respond to tiny shear force such as fingertip slipping with a low limit of 2 N and wide range of strains ranging from 30% to 70% with appropriate discrimination. Most importantly, the visualization of tactile stimuli with human‐ and machine‐readability and vividness permit remote and wireless user‐interactive applications such as videogames and RC car control, assisted with the developed method of active optical signal recognition. This work presents a paradigm shift to user‐interactive interfaces, boosting their implementation in multitudinous areas such as artificial intelligences and the Internet of Things. [ABSTRACT FROM AUTHOR]

Halide perovskites featuring remarkable optoelectronic properties hold great potential for threshold switching devices (TSDs) that are of primary importance to next-generation memristors and neuromorphic computers. However, such devices are still in their infancy due to the unsolved challenges of high threshold voltage, poor stability, and lead-containing features. Herein, a unipolar TSD based on an all-inorganic halide perovskite of CsCu 2 I 3 is demonstrated, exhibiting the fascinating attributes of a low threshold voltage of 0.54 V, a high ON/OFF ratio of 10 4 , robust air stability over 70 days, a steep switching slope of 6.2 mV·decade -1 , and lead-free composition. Moreover, the threshold voltage can be further reduced to 0.23 V using UV illumination to reduce the barrier of iodide ion migration. The multilevel threshold switching behavior can be realized through the modulation of either the compliance current or the scan rate. The TSD with mechanical compliance and transparency is also demonstrated. This work enriches TSDs with expanded perovskite materials, boosting the related applications of this emerging class of device families.