Wenbo Ding's group at Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, have made important achievements in the research of vibration sensing. This study developed a highly sensitive self-powered vibration sensor based on the triboelectric nanogenerator (TENG), which is successfully used to monitor the operating conditions of mechanical gear systems, reaching a recognition accuracy of 99.78%. The research article entitled "A Highly Sensitive Triboelectric Vibration Sensor for Machinery Condition Monitoring" was published in the journal Advanced Energy Materials and selected as the front cover paper of the current issue (https://doi.org/10.1002/aenm.202201132).

Vibration sensors are involved extensively in a variety of applications. Especially in the era of the Internet of things, developing self-powered vibration sensors has become a very meaningful yet challenging problem. In this paper, a highly sensitive self-powered vibration sensor based on the TENG for machinery condition monitoring is investigated. The triboelectric layers constructed by the flexible dielectric film and porous metal material effectively improve the sensitivity of the TENG sensor. The TENG sensor can detect vibration of 1-2000 Hz, and the output signal of the TENG sensor has no distortion in waveforms even in high-temperature and high-humidity environments. Combined with machine learning algorithms, the TENG system has been successfully used to monitor the operating conditions of mechanical gear systems with high accuracy. The results can be displayed on both the computer screen and other mobile devices in real-time. Furthermore, it can be used for vibration detection in other areas such as the air compressor, heat gun, hollow tile recognition, etc. The detected data is further processed by an embedded system and displayed on the local screen. This work presents solid progress toward the practical applications of TENG in vibration detection and has great potential for the development of self-powered vibration sensing.