Wearable Perovskite‐Based Shadow Recognition Sensor for Ambient and Nonobtrusive Human–Computer Interaction

Autor: Tingqing Wu, Zengqi Huang, Lin Li, Wei Sun, Tangyue Xue, Qi Pan, Hongfei Xie, Sisi Chen, Lutong Guo, Jimei Chi, Huadong Wang, Zeying Zhang, Teng Han, Meng Su, Yanlin Song
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Advanced Intelligent Systems, Vol 5, Iss 1, Pp n/a-n/a (2023)
Druh dokumentu: article
ISSN: 2640-4567
20220030
DOI: 10.1002/aisy.202200307
Popis: Driven by the Internet of Everything, one of the main goals in human–computer interaction is to achieve intuitive, effortless, and easy‐to‐learn communication. Thus, senseless optoelectronic devices with high response performance under ambient environment have an extensive application space in improving the interfacing between users and computers. Herein, a concept of wearable perovskite‐based shadow recognition sensor is demonstrated for ambient and nonobtrusive human–computer interaction. The multidimensional ordered nucleation and growth of perovskite crystals are promoted by introducing the self‐driving effect of liquid crystal (LC) oligomers. The resulted LC‐doped perovskite film (LC‐PVK) with micrometer‐sized grains can output relatively high photocurrent under indoor ambient light (≈500 lux). The LC‐based device exhibits over a hundred times of on–off ratio and fast response of millisecond level even after storage for more than 1200 h. The device also shows an ultratrace Pb2+ leakage of 1.02 μg L−1 in water, and still retains more than 90% of the photocurrent intensity after thousands of bending strains. Accordingly, a novel human–computer interaction is achieved by identifying external action commands with the recognition of shadows, which can provide a “haptic” perception for robots.
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