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Braille recognition is of great significance for the visually impaired and blind people to achieve convenient communication and learning. A self-powered Braille recognition sensing system with long-term survivability and phonic...

Accurate plantar pressure mapping systems with low dependence on the external power supply are highly desired for preventative healthcare and medical diagnosis. Herein, we propose a self-powered smart insole system that can perform both static and dynamic plantar pressure mapping with high accuracy. The smart insole system integrates an insole-shaped sensing unit, a multi-channel data acquisition board, and a data storage module. The smart insole consists of a 44-pixel sensor array based on triboelectric nanogenerators (TENGs) to transduce pressure to the electrical signal. By optimizing the sensor architecture and the system's robustness, the smart insole achieves high sensitivity, good error-tolerance capability, excellent durability, and short response-recovery time. Various gait and mobility patterns, such as standing, introversion/extraversion, throwing, and surpassing obstacles, can be distinguished by analyzing the acquired electrical signals. This work paves the way for self-powered wearable devices for gait monitoring, which might enable a new modality of medical diagnosis.

Flexible sensing technologies that play a pivotal role in endowing robots with detection capabilities and monitoring their motions are impulsively desired for intelligent robotics systems. However, integrating and constructing reliable and sustainable flexible sensors with multifunctionality for robots remains an everlasting challenge. Herein, an entirely intrinsic self‐healing, stretchable, and attachable multimodal sensor is developed that can be conformally integrated with soft robots to identify diverse signals. The dynamic bonds cross‐linked networks including the insulating polymer and conductive hydrogel with good comprehensive performances are designed to fabricate the sensor with prolonged lifespan and improved reliability. Benefiting from the self‐adhesiveness of the hydrogel, strong interfacial bonding can be formed on various surfaces, which promotes the conformable integration of the sensor with robots. Due to the ionic transportation mechanism, the sensor can detect strain and temperature based on piezoresistive and thermoresistive effect, respectively. Moreover, the sensor can work in triboelectric mode to achieve self‐powered sensing. Various information can be identified from the electrical signals generated by the sensor, including hand gestures, soft robot crawling motions, a message of code, the temperature of objects, and the type of materials, holding great promise in the fields of environmental detection, wearable devices, human‐machine interfacing, and robotics.

Surface defects cause non‐radiative charge recombination and reduce the photovoltaic performance of perovskite solar cells (PSCs), thus effective passivation of defects has become a crucial method for achieving efficient and stable devices. Organic ammonium halides have been widely used for perovskite surface passivation, due to their simple preparation, lattice matching with perovskite, and high defects passivation ability. Herein, a surface passivator 2,4,6‐trimethylbenzenaminium iodide (TMBAI) is employed as the interfacial layer between the spiro‐OMeTAD and perovskite layer to modify the surface defect states. It is found that TMBAI treatment suppresses the nonradiative charge carrier recombination, resulting in a 60 mV increase of the open‐circuit voltage (Voc) (from 1.11 to 1.17 V) and raises the fill factor from 76.3% to 80.3%. As a result, the TMBAI‐based PSCs device demonstrates a power conversion efficiency (PCE) of 23.7%. Remarkably, PSCs with an aperture area of 1 square centimeter produce a PCE of 21.7% under standard AM1.5 G sunlight. The unencapsulated TMBAI‐modified device retains 92.6% and 90.1% of the initial values after 1000 and 550 h under ambient conditions (humidity 55%–65%) and one‐sun continuous illumination, respectively.