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A triboelectric nanogenerator (TENG) is an efficient technology that can harvest various forms of mechanical energy and convert it into electrical energy. However, high output efficiency and durability are necessary for the mass application of TENGs, and these characteristics strongly depend on the frictional properties of triboelectric materials, especially for sliding TENGs. Diamond-like carbon (DLC) films, which are effective triboelectric materials, have better durability and tribological properties than those of other conventional dielectric materials. In this study, molecular self-assembly technology was applied to functionalize the surface of DLC films as an ultrathin lubricating layer to increase the output of TENGs and simultaneously improve durability. Three self-assembled monolayers (SAMs) with different functional groups, perfluorodecyltrichlorosilane (FDTS), octadecyltrichlorosilane (OTS), and 3-aminopropyltriethoxysilane (APTES), were successfully formed on the DLC film surfaces. The performance of the sliding TENGs with SAM-modified DLC films as triboelectric pairs revealed interesting findings. The TENGs with hydrogenated DLC (H-DLC) modified with the OTS SAM and fluorinated DLC (F-DLC) modified with the FDTS SAM produced the highest outputs, with a peak short-circuit current of 15.1 μA at a power density of up to 69.5 mW/m 2 , which is four times that of the bare DLC film pair. Furthermore, the DLC films modified with SAMs exhibited outstanding stability and durability in humidity and during prolonged evaluation studies. This research is expected to advance a methodology for designing highly durable and efficient thin-film TENGs owing to the thin film characteristics of DLC films and SAMs.

With the rapid development of the Internet of Things and artificial intelligence (AI), the requirement for sensing technologies for smart bearings has increased dramatically. The general bearing sensors can only recognize the basic information from temperature or vibration, far from satisfying the self‐diagnosis and self‐maintenance. Recently, self‐powered sensing technologies based on triboelectric nanogenerators have paved a new route for fabricating smart bearings. In this study, the triboelectric principle is applied to a commercial metal‐polymer plain bearing (MPPB) bearing, which can achieve self‐sensing, self‐diagnosis, and self‐maintenance. The geometrical structure of the triboelectric MPPB (T‐MPPB) is designed to balance the output efficiency and external load, and the super durability and load capability are verified. Besides, the mechanism behind the output change trend under boundary and hydrostatic fluid lubrication is revealed for the first time. Furthermore, the deep learning algorithm can classify the lubrication states with highly accurate performance. The proposed T‐MPPB has the potential to achieve self‐maintenance with the lubricating pump according to the lubrication condition classified by the AI. This research not only establishes the feasibility of designing self‐powered smart MPPB but also demonstrates a way for identifying lubrication states, thus achieving self‐diagnosis and self‐maintenance ability by self‐powered sensors.

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