Huang Jincai, Zhang Man, He Haoyun, Li Qingang, Zhao Yixin, Tan Qiulin, Zang Xining
Department of Mechanical Engineering, Tsinghua University, Beijing, 100084 China.
State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084 China.
Microsyst Nanoeng. 2024 Mar 11;10:34. doi: 10.1038/s41378-024-00670-z. eCollection 2024.
The implementation of an intelligent road network system requires many sensors for acquiring data from roads, bridges, and vehicles, thereby enabling comprehensive monitoring and regulation of road networks. Given this large number of required sensors, the sensors must be cost-effective, dependable, and environmentally friendly. Here, we show a laser upgrading strategy for coal tar, a low-value byproduct of coal distillation, to manufacture flexible strain-gauge sensors with maximum gauge factors of 15.20 and 254.17 for tension and compression respectively. Furthermore, we completely designed the supporting processes of sensor placement, data acquisition, processing, wireless communication, and information decoding to demonstrate the application of our sensors in traffic and bridge vibration monitoring. Our novel strategy of using lasers to upgrade coal tar for use as a sensor not only achieves the goal of turning waste into a resource but also provides an approach to satisfy large-scale application requirements for enabling intelligent road networks.
智能道路网络系统的实施需要许多传感器来从道路、桥梁和车辆获取数据，从而实现对道路网络的全面监测和调控。鉴于所需传感器数量众多，这些传感器必须具备成本效益、可靠性和环境友好性。在此，我们展示了一种针对煤焦油（煤炭蒸馏的低价值副产品）的激光升级策略，以制造用于拉伸和压缩的最大应变系数分别为15.20和254.17的柔性应变计传感器。此外，我们还完整设计了传感器放置、数据采集、处理、无线通信和信息解码的配套流程，以展示我们的传感器在交通和桥梁振动监测中的应用。我们利用激光升级煤焦油用作传感器的新颖策略不仅实现了变废为宝的目标，还提供了一种满足大规模应用需求以实现智能道路网络的方法。
