RESUMEN
Nowadays, with the rapid development of e-commerce, the transportation of products has become more and more frequent. However, how to monitor the situation of products effectively and conveniently during road transportation is a long-standing problem. In order to meet this problem in practical applications, we fabricated a triboelectric nanogenerator sensor with a "square box" structure (S-TENG) for detecting the vibration suffered by vehicles. Specifically, with the spring installed in the S-TENG as a trigger, the two friction layers can contact and then separate to generate the real-time electrical signals when the S-TENG receives external excitation. The output voltage signals of the S-TENG under different vibration states were tested and the results demonstrated that the peak and zero positions of the open-circuit voltage-output curve are related to amplitude and frequency, respectively. In addition, the subsequent simulation results, obtained by ANSYS and COMSOL software, were highly consistent with the experimental results. Furthermore, we built a platform to simulate the scene of the car passing through speed bumps, and the difference in height and the number of speed bumps were significantly distinguished according to the output voltage signals. Therefore, the S-TENG has broad application prospects in road transportation.
RESUMEN
Reciprocating motion is a widely existing form of mechanical motion in the natural environment. Triboelectric nanogenerators (TENGs) that work in sliding mode are ideal for harnessing large-distance reciprocating motion, and their energy conversion efficiency could be greatly enhanced by adding springs to them. Herein, we focused on investigating the design and optimization principles of sliding mode TENGs by analyzing the effects of spring parameters and vibration frequency on the triboelectric output performance of typical cylindrical sliding TENGs (CS-TENGs). Experimental study and finite elemental analysis were carried out based on a CS-TENG model assembled using a polytetrafluoroethylene (PTFE) film as the negative layer and an aluminum film as the positive layer. The energy output was found to be mainly affected by the change of relative displacement between the two friction layers, rather than the reactive force applied by the springs or the velocity of the sliding motion. However, the frequency of the output signals could be improved when the stiffness coefficient of the springs and the CS-TENG vibration frequency were increased. This study provides valuable directions for the design and optimization of sliding mode TENGs containing springs, and will motivate in-depth research on the fundamental principles of TENG operation.
RESUMEN
Fabric-based triboelectric nanogenerators (TENGs) are promising candidates as wearable energy-harvesting devices and self-powered sensors. Booting the power generation performance is an eternal pursuit for TENGs. Herein, an efficient approach was proposed to enhance the triboelectric performance of commercial velvet fabric by enriching the fiber surface with hierarchical structures and amide bonds through chemical grafting of carbon nanotube (CNT) and poly(ethylenimine) (PEI) via a polyamidation reaction. With an optimized modifier concentration, the fabric-based TENG easily achieved over 10 times improvement in output voltage and current at a low modifier content of less than 1 wt %. The modified-fabric-based TENG was fully washable and exhibited excellent robustness and long-term stability. With a maximum power density of 3.2 W/m2 achieved on a 5 × 106 Ω external resistor, the TENG was able to serve as a power source for various small electronics such as pedometer, digital watch, calculator, and digital timer. In addition, the TENG demonstrated capability in self-powered tactile and pressure sensing and promising potential in human-computer interface applications. The approach proposed provides a feasible path for boosting the triboelectric performance of fabric-based TENGs and gives insights into the design of fabric-based nanogenerators and smart textiles.