Ultralight Iontronic Triboelectric Mechanoreceptor with High Specific Outputs for Epidermal Electronics

The pursuit to mimic skin exteroceptive ability has motivated the endeavors for epidermal artificial mechanoreceptors.Artificial mechanoreceptors are required to be highly sensitive to capture imperceptible skin deformations and preferably to be self-powered,breathable,lightweight and deformable to satisfy the prolonged wearing demands.It is still struggling to achieve these traits in single device,as it remains difficult to minimize device architecture without sacrificing the sensitivity or stability.In this article,we present an all-fiber iontronic triboelectric mechanoreceptor(ITM)to fully tackle these challenges,enabled by the high-output mechano-to-electrical energy conversion.The proposed ITM is ultralight,breathable and stretchable and is quite stable under various mechanical deformations.On the one hand,the ITM can achieve a superior instantaneous power density;on the other hand,the ITM shows excellent sensitivity serving as epidermal sensors.Precise health status monitoring is readily implemented by the ITM calibrating by detecting vital signals and physical activities of human bodies.The ITM can also realize acoustic-to-electrical conversion and distinguish voices from different people,and biometric application as a noise dosimeter is demonstrated.The ITM therefore is believed to open new sights in epidermal electronics and skin prosthesis fields.

A Wearable Multidimensional Motion Sensor for AI-Enhanced VR Sports

Regular exercise paves the way to a healthy life.However,conventional sports events are susceptible to weather conditions.Current motion sensors for home-based sports are mainly limited by operation power consumption,single-direction sensitivity,or inferior data analysis.Herein,by leveraging the 3-dimensional printing technique and triboelectric effect,a wearable self-powered multidimensional motion sensor has been developed to detect both the vertical and planar movement trajectory.By integrating with a belt,this sensor could be used to identify some low degree of freedom motions,e.g.,waist or gait motion,with a high accuracy of 93.8%.Furthermore,when wearing the sensor at the ankle position,signals generated from shank motions that contain more abundant information could also be effectively collected.By means of a deep learning algorithm,the kicking direction and force could be precisely differentiated with an accuracy of 97.5%.Toward practical application,a virtual reality-enabled fitness game and a shooting game were successfully demonstrated.This work is believed to open up new insights for the development of future household sports or rehabilitation.

Graphene-based dual-function acoustic transducers for machine learning-assisted human-robot interfaces

Human–robot interface(HRI)electronics are critical for realizing robotic intelligence.Here,we report graphene-based dual-function acoustic transducers for machine learning-assisted human–robot interfaces(GHRI).The GHRI functions both an artificial ear through the triboelectric acoustic sensing mechanism and an artificial mouth through the thermoacoustic sound emission mechanism.The success of the integrated device is also attributed to the multifunctional laser-induced graphene,as either triboelectric materials,electrodes,or thermoacoustic sources.By systematically optimizing the structure parameters,the GHRI achieves high sensitivity(4500 mV Pa^(–1))and operating durability(1000000 cycles and 60 days),capable of recognizing speech identities,emotions,content,and other information in the human speech.With the assistance of machine learning,30 speech categories are trained by a convolutional neural network,and the accuracy reaches 99.66%and 96.63%in training datasets and test datasets.Furthermore,GHRI is used for artificial intelligence communication based on recognized speech features.Our work shows broad prospects for the development of robotic intelligence.

Triboelectric-optical responsive cholesteric liquid crystals for self-powered smart window,E-paper display and optical switch

Intelligent responsive devices are crucial for a variety of applications ranging from smart electronics to robotics.Electro-responsive cholesteric liquid crystals(CLC)have been widely applied in display panels,smart windows,and so on.In this work,we realize the mechanical stimuli-triggered optical responses of the CLC by integrating it with a triboelectric nanogenerator(TENG),which converts the mechanical motion into alternating current electricity and then tunes the different optical responses of the CLC.When the voltage applied on the CLC is relatively low(15–40 V),the TENG drives the switching between the bistable planar state and focal conic state of the CLC,which shows potential applications in selfpowered smart windows or E-paper displays.When the voltage supplied by the TENG is larger than60 V,a self-powered optical switch is demonstrated by utilizing the transformation between focal conic state and instantons homeotropic state of the CLC.This triboelectric-optical responsive device consumes no extra electric power and suggests a great potential for future smart electronics.