To improve the friction performance and service life of protective coatings in humidity-fluctuating environments, porous hard titanium nitride (TiN)–molybdenum disulfide (MoS2) composite coatings were prepared by using direct current magnetron sputtering (DCMS) with the mode of oblique angle deposition (OAD) and chemical vapor deposition (CVD) technologies. The structure and chemical component were characterized by field emission scanning electron microscopy (FESEM), energy dispersive spectrometer (EDS), grazing incidence X-ray diffraction (GIXRD), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. The tribological properties of these TiN–MoS2composite coatings were investigated. The results indicate that the porous TiN–MoS2composite coating exhibited outstanding friction performance and long service life under humidity-fluctuating environments. At the initial 20% relative humidity (RH) stage, the MoS2on the porous TiN–MoS2composite coating surface worked as an effective lubricant; thus, the coating demonstrated excellent lubrication performance, and the friction coefficient (COF) was about 0.05. As the humidity was alternated to 70% RH, the lubrication effect diminished due to the production of molybdenum oxide (MoO3), and the COF was about 0.2, which was attributed to the degradation of MoS2on the wear track and the release of fresh MoS2from the porous TiN matrix. After the environmental conditions shifted from 70% to 20% RH, the MoO3was removed, and the lubrication effect was restored. In summary, TiN–MoS2porous composite coating offers a promising approach for lubrication in humidity-fluctuating environments.
In this study, we systematically investigate the triboelectric performance degradation of polytetrafluoroethylene (PTFE)-based triboelectric nanogenerators (TENGs) under high–low temperature cycling and humidity variations, a critical yet underexplored challenge in extreme environmental applications. Under accelerated aging conditions spanning 0–300 thermal cycles and 0–90% RH, PTFE films demonstrated progressively worsening electrical output, their short-circuit current declining steadily from 7.2 to 4.6 μA, alongside an open-circuit voltage drop from 400 to 240 V. Surface characterization via scanning electron microscopy, atomic force microscopy, and X-ray photoelectron spectroscopy reveals that thermal cycling induces microstructural defects and chemical oxidation, where oxygen content replaced C–F bonds with weaker electron-accepting groups (C–O, C═O). This oxidative degradation reduced PTFE’s electron affinity and directly impaired charge transfer efficiency in TENGs. To address performance unpredictability, an improved extreme learning machine algorithm is developed, achieving 100% accuracy in real-time classification of PTFE aging states by analyzing triboelectric signals. Furthermore, paired with pristine PTFE, aged PTFE modified surface states enable a 21.8-fold power output enhancement and outperform conventional configurations. These findings establish a mechanistic framework linking thermal-humidity aging to triboelectric decay while proposing machine-learning-driven predictive maintenance strategies for TENGs in aerospace, energy systems, and autonomous devices operating in harsh environments.
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