journal article·2023-11-14

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

Yafeng Pang, Xingyi Zhu, Shuainian Liu, Chengkuo Lee

ACS Nano· Volume 17· Issue 21
Publisher page

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.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Polydiacetylene-based materials and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 200092, P. R. China

Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore

Center for Intelligent Sensors and MEMS, National University of Singapore, Block E6 #05-11, 5 Engineering Drive 1, Singapore 117608, Singapore

Funding

Shanghai Municipal Education Commission · Fundamental Research Funds for the Central Universities · China Scholarship Council · Science and Technology Commission of Shanghai Municipality · National Natural Science Foundation of China · Shanghai Education Development Foundation

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