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Ferroelectric Polarization-Enhanced Performance of Flexible CuInP2S6 Piezoelectric Nanogenerator for Biomechanical Energy Harvesting and Voice Recognition Applications
Authors:Yunchen Zhang  Junqi Mao  Ren-Kui Zheng  Jiawei Zhang  Yonghui Wu  Xiaobing Wang  Kexin Miao  Hongbo Yao  Liya Yang  Haiwu Zheng
Affiliation:1. Henan Province Engineering Research Center of Smart Micro-nano Sensing Technology and Application, School of Physics and Electronics, Henan University, Kaifeng, 475004 P. R. China;2. School of Physics and Materials Science, Guangzhou University, Guangzhou, 510006 P. R. China
Abstract:2D piezoelectric materials have strong intrinsic piezoelectricity and superior flexibility, which are endowed with huge potential to develop piezoelectric nanogenerators (PENGs). However, there are few attempts to investigate the energy harvesting of 2D ferroelectric materials. Herein, an enhanced output performance is reported by ferroelectric polarization in a PENG with exfoliated 2D ferroelectric CuInP2S6 (CIPS). Specifically, the polarized CIPS-based PENG produces a short-circuit current of 760 pA at 0.85% tensile strain, which is 3.8 times higher than that of unpolarized CIPS-based PENG. Systematical PFM and Raman analysis reveal that the ferroelectric polarization remarkably reinforces the effective piezoelectric constant of CIPS nanoflakes and boosts the in-plane migration and out-of-plane hopping of copper ions, which is the main reason for the enhancement of output performance. Furthermore, the CIPS-based PENG can not only be utilized to harvest biomechanical energy such as wrist joints movement, but also exhibits a potential for a voice recognition system integrated with deep learning technology. The classification accuracy of a series of letter sounds is as high as 96%. This study commendably broadens the application scope of 2D materials in micro-nano energy and intelligent sensors, which will have profound implications for exploring wearable nanoelectronic devices.
Keywords:2D materials  biomechanical energy harvesting  deep residual networks  piezoelectric nanogenerators  voice recognition
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