A Natural Gradient Biological-Enabled Multimodal Triboelectric Nanogenerator for Driving Safety Monitoring

Abstract

A key element to ensuring driving safety is to provide a sufficient braking distance. Inspired by the nature triply periodic minimal surface (TPMS), a gradient and multimodal triboelectric nanogenerator (GM-TENG) is proposed with high sensitivity and excellent multimodal monitoring. The gradient TPMS structure exhibits the multi-stage stress-strain properties of typical porous metamaterials. Significantly, the multimodal monitoring capability depends on the implicit function of the defined level constant c, which directly contributes to the multimodal driving safety monitoring. The mechanical and electrical responsive behavior of the GM-TENG is analyzed to identify the applied speed, load, and working mode. In addition, optimized peak open-circuit voltage (V oc) is demonstrated for self-awareness of the braking condition. The braking distance factor (L) is conceived to construct the self-aware equation of the friction coefficient based on the integration of V oc with respect to time. Importantly, R-squared up to 94.29 % can be obtained, which improves self-aware accuracy and real-time capabilities. This natural structure and self-aware device provide an effective strategy to improve driving safety, which contributes to the improvement of road safety and presents self-powered sensing with potential applications in an intelligent transportation system.

Advancements in Bio-inspired Self-Powered Wireless Sensors: Materials, Mechanisms, and Biomedical Applications

“…Copyright 2020 Springer Nature; (E) Natural triply periodic minimal surface-enabled multimodal and gradient triboelectric sensor for real-time detection of long-distance braking, middle braking, and emergency braking. Reproduced with permission from ref . Copyright 2023 American Chemical Society.…”

“…The self-powered sensors that help monitor braking performance play an important role in improving driving safety. Pang and co-workers also designed a natural triply periodic minimal surface-enabled multimodal and gradient triboelectric sensor based on PTFE film-covered Al foil for real-time awareness of danger in the braking process. They optimized the triply periodic minimal surface inspired by butterfly wings to detect long-distance braking, middle braking, and emergency braking (Figure E).…”

Advances in Machine‐Learning Enhanced Nanosensors: From Cloud Artificial Intelligence Toward Future Edge Computing at Chip Level

“…[ 133–136 ] By analyzing large datasets of simulated or experimental data, machine‐learning models can identify optimal waveguide geometries, materials, or fabrication parameters to reduce losses and enhance the sensitivity of the sensor. [ 137–139 ] Nanoantennas typically exhibit resonant behavior, leading to narrowband sensing responses. [ 19,140 ] Extending the sensing capability to a broader range of wavelengths or enabling multimodal sensing (e.g., polarization or phase) is a challenge.…”

Perspectives of Material Optimization Strategies for High‐Performance Triboelectric Nanogenerators

“…The rapid development of the Internet of Things (IoT) has led to a sharp increase in the number of distributed electronic devices. [ 1–4 ] The traditional batteries with limited capacity require periodic replacement or charging, which greatly increases the maintenance costs of the IoT. [ 5 ] How to develop a power supply that can stably power electronic devices for a long time is an urgent problem to be solved.…”