二硫化钨
纳米发生器
材料科学
压电
接口(物质)
纳米技术
钨
二硫键
二硫化钼
光电子学
冶金
复合材料
毛细管数
生物化学
化学
毛细管作用
作者
Yuxiang Zhou,Yu-Tung Lin,Shih‐Min Huang,Guanting Chen,Shuo‐Wen Chen,Hansong Wu,I‐Chih Ni,Wei‐Pang Pan,Meng‐Lin Tsai,Chih‐I Wu,Po‐Kang Yang
出处
期刊:Nano Energy
[Elsevier]
日期:2022-03-24
卷期号:97: 107172-107172
被引量:24
标识
DOI:10.1016/j.nanoen.2022.107172
摘要
Tungsten disulfide (WS 2 ), which is one of the most common transition metal dichalcogenides (TMDCs), has received great attention in recent years owing to their outstanding carrier mobility, chemical functionality, and optoelectronic properties. However, only few attempts have been reported to access its electromechanical characteristics. Herein, we investigate the intrinsic piezoelectricity of monolayer WS 2 nanosheets (NSs) synthesized by chemical vapor deposition (CVD) and estimate their effective piezoelectric coefficient d 33 by piezo-response force microscopy (PFM). Moreover, the as-grown WS 2 NS was further fabricated into a piezoelectric nanogenerator (W-PENG) to evaluate their energy harvesting capability within nanoscale dimension. More importantly, the W-PENG was applied as self-powered strain sensors with high sensitivity, and integrated into a smart gesture recognition system. These results demonstrate that the W-PENG has great potential for future strain-modulated electronics, ultrathin functional sensors, and human-machine interface design. Intrinsic piezoelectricity of monolayer tungsten disulfide nanosheets (WS 2 NSs) synthesized via the chemical vapor deposition is characterized by piezoresponse force microscopy (PFM). The WS 2 NSs are further fabricated into a piezoelectric nanogenerator (W-PENG) for self-powered strain sensor application. The W-PENGs are also designed into a smart gesture recognition system. • The intrinsic piezoelectricity of monolayer WS 2 nanosheet investigated by piezoresponse force microscopy is reported. • A flexible piezoelectric nanogenerator (W-PENG) based on monolayer WS 2 nanosheet is demonstrated for the first time. • The W-PENG is further applied to self-powered strain sensor and smart human-machine interface applications.
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