4.8 Article

Triboelectric Nanogenerators Based on Super-Stretchable Conductive Hydrogels with the Assistance of Deep-Learning for Handwriting Recognition

期刊

ACS APPLIED MATERIALS & INTERFACES
卷 15, 期 27, 页码 32993-33002

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsami.3c06597

关键词

flexible; hydrogel; triboelectric nanogenerator(TENG); sensor; identification

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In this paper, a composite hydrogel composed of polyacrylamide, hydroxypropylmethylcellulose, and MXene (Ti3C2Tx) nanosheets was developed, which formed a stable double-chain structure by hydrogen bonding. Based on the excellent properties of the hydrogel, a flexible and multifunctional triboelectric nanogenerator (PHM-TENG) was prepared, which can collect biomechanical energy and convert it to 183 V with a maximum power density of 78.3 mW/m(2). This work holds great potential in providing a green power source for miniature electronics and developing intelligent systems for handwriting recognition.
Nowadays, wearable electronic devices are developingrapidly withthe internet of things and human-computer interactions. However,there are problems such as low power, short power supply time, anddifficulty in charging, leading to a limited range of practical applications.In this paper, a composite hydrogel composed of polyacrylamide, hydroxypropylmethylcellulose, and MXene (Ti3C2T x ) nanosheets was developed, which formed a stabledouble-chain structure by hydrogen bonding. The configuration endowsthe hydrogel with excellent properties, such as high strength, strongstretchability, excellent electrical conductivity, and high strainsensitivity. Based on these characteristics, a flexible multifunctionaltriboelectric nanogenerator (PHM-TENG) was prepared using thehydrogel as a functional electrode. The nanogenerator can collectbiomechanical energy and convert it to 183 V with a maximum powerdensity of 78.3 mW/m(2). It is worth noting that PHM-TENGcan be applied as a green power source for driving miniature electronics.Also, it can be used as an auto-powered strain sensor that distinguishesletters, enabling monitoring under small strain conditions. This workis anticipated to provide an avenue for the development of new intelligentsystems for handwriting recognition.

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