Vibration wave transfer management strategy inside triboelectric nanogenerator device for enhancing recognition accuracy

Abstract

Present triboelectric nanogenerator (TENG) devices can be used for monitoring vibration frequency, intensity and working environment. Nevertheless, vibration wave recognition cannot be achieved, owing to developed device structure and working mechanism limitation. To prevent such issues, dielectric materials (metallized cotton encapsulated by polydimethylsiloxane of gradient elastic modulus) with vibration wave transfer management strategy are applied to enhance the recognition accuracy and output performance. The TENG device with this structure can balance the vibrational energy transfer within the negative triboelectric material and the polydimethylsiloxane layer/metallized cotton interfacial strain. Additionally, the deformation/stress fields inside the device and corresponding the device working mechanisms under vibration are revealed systematically by characterizing the triboelectric signals. An increase in the maximum voltage of 50% and the number of transferred charges of 40% under vibration are achieved. A vibration perception system integrated with a TENG-based sensor, data processing and display modules is also developed, which can fully and quickly recognize the real-time triboelectric signals with approximately 61% recognition accuracy. The operating status of the equipment can be monitored from the perspective of vibration, which has laid a solid foundation for the AIoT era.