4.8 Article

Surface modified hybrid ZnSnO3 nanocubes for enhanced piezoelectric power generation and wireless sensory application

期刊

NANO ENERGY
卷 92, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.nanoen.2021.106653

关键词

Piezoelectric nanogenerator; Renewable energy; Sensors; Smart helmet

资金

  1. Welch Foundation [BX 0048]
  2. U.S. Department of Defense Manufacturing Engineering Education Program [N00014-19-1-2728]

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The study presents an aluminum-doped zinc stannate piezoelectric nanogenerator with high electrical output, achieved through a low-temperature solution method; 2 wt% aluminum-doped ZnSnO3 showed the highest electrical output in terms of open circuit voltages and short circuit current; The device can function as an energy harvester and wireless human motion sensor.
Piezoelectric Nanogenerators (PENGs), which can convert ambient mechanical stimuli into electrical energy, are held in high regard due to their cost-effectiveness, energy harvesting applications, and potential as self-powered sensors. We report an aluminum-doped zinc stannate (ZnSnO3) PENG that can achieve high electrical outputs with respect to the external force. In order to enrich the piezoelectric mechanics, a low-temperature solution method was adopted in our work to synthesize ZnSnO3 nanocubes with an average side length of only 30 - 55 nm. Furthermore, ZnSnO3 was doped with 1-5 wt% of aluminum nanoparticles. We report that 2 wt% of aluminum doped ZnSnO3 showed the highest electrical output in terms of open circuit voltages and short circuit current. The nanogenerator device achieved an average open-circuit voltage of 80-175 V with a frequency range of 60 BPM (Beats Per Minute) to 240 BPM, an unprecedented electrical output in comparison to current ZnSnO3-based PENGs. With the presented high output-to-size ratio taken into consideration, the device was mounted in a helmet and tested as an energy harvester and wireless human motion sensor, which can generate electric charge as well as detect human movements and transmit the corresponding signals wirelessly. Our work is indicative of a promising smart helmet using organic-inorganic hybrid materials.

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