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</script>Energy-harvesting devices based on a single energy conversion mechanism generally have a low output and low conversion efficiency. To solve this problem, an energy harvester coupled with a triboelectric mechanism and electrostatic mechanism for biomechanical energy harvesting is presented. The output performances of the device coupled with a triboelectric mechanism and electrostatic mechanism were systematically studied through principle analysis, simulation, and experimental demonstration. Experiments showed that the output performance of the device was greatly improved by coupling the electrostatic induction mechanisms, and a sustainable and enhanced peak power of approximately 289 μW was produced when the external impedance was 100 MΩ, which gave over a 46-fold enhancement to the conventional single triboelectric conversion mechanism. Moreover, it showed higher resolution for motion states compared with the conventional triboelectric nanogenerator, and can precisely and constantly monitor and distinguish various motion states, including stepping, walking, running, and jumping. Furthermore, it can charge a capacitor of 10 μF to 3 V within 2 min and light up 16 LEDs. On this basis, a self-powered access control system, based on gait recognition, was successfully demonstrated. This work proposes a novel and cost-effective method for biomechanical energy harvesting, which provides a more convenient choice for human motion status monitoring and can be widely used in personnel identification systems.
energy harvesting, triboelectric mechanism, Chemistry, energy harvesting; triboelectric mechanism; electrostatic mechanism; human motion status monitoring, electrostatic mechanism, human motion status monitoring, QD1-999, Article
energy harvesting, triboelectric mechanism, Chemistry, energy harvesting; triboelectric mechanism; electrostatic mechanism; human motion status monitoring, electrostatic mechanism, human motion status monitoring, QD1-999, Article
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
