Manipulation of gas in an aqueous environment is fundamental to both academic research and industrial applications. In particular, the gas film on a superhydrophobic surface, referred to as a plastron, has fascinated scientists due to its potential applications, including drag reduction, antifouling, gas-involving reactions, and gas transport. However, most gas manipulation strategies focus on the transportation of bubbles. An effective method for the facile manipulation of plastrons has yet to be explored. In this work, we propose a high-performance manipulation strategy for plastrons that uses the capillary pressure difference generated by connected sparse and dense superhydrophobic mesh surfaces (S-D-SHM). Plastrons can be transported directionally, spontaneously, repeatedly, and counterbuoyantly (up to a 30° tilt angle) between asymmetric SHMs. This method, which requires no external energy input or human intervention, can provide on-demand plastron replenishment for SHMs (8 times), significantly enhancing plastron stability. Furthermore, the S-D-SHM achieves a 142% improvement in water impact resistance due to the automatic adjustment of the plastron pressure. Owing to the long-term isolation effect of the plastron, the S-D-SHM shows an excellent drag reduction effect (23.7% drag reduction rate (D_r)) and antiscaling performance (93.3% antiscaling rate). This facile and effective strategy simplifies plastron manipulation and can advance the development of stable superhydrophobicity under complex wetting conditions.

Owing to their excellent mechanical properties, two-dimensional (2D) materials show substantial promise for application in tribology. This has prompted a proliferation of novel 2D structures in numerous studies. However, ‌there is a lack of understanding regarding‌ the intrinsic relationship between their structure and lubrication performance, ‌which presents‌ a challenge to the systematic design of high-performance 2D ‌lubricating‌ materials. Therefore, this paper first classifies 2D lubricating materials into four categories based on their structural characteristics: inorganic, organic, carbon-based, and hybrid structures. Subsequently, it systematically reviews key research advances for each structural type within the field of tribology. This review encompasses fundamental studies on intrinsic lubrication ability—primarily investigated through microscopic experiments and theoretical simulations—as well as applied research exploring their use as lubricant additives (both oil- and water-based), lubricant coatings, and reinforcing phases in composite materials. Furthermore, the lubrication mechanisms of diverse 2D structures across various lubrication regimes have been systematically summarized, and strategies for enhancing performance via structural modification are also discussed. Finally, the current challenges and future research directions for 2D lubricating materials are critically analyzed.

Electron energy dissipation is an important energy dissipation pathway that cannot be ignored in friction process. Two-dimensional zeolite imidazole frameworks (2D ZIFs) and fluorine doping strategies give 2D Zn-ZIF and 2D Co-ZIF unique electrical properties, making them ideal materials for studying electron energy dissipation mechanism. In this paper, based on the superlubricity modulation of 2D fluoridated ZIFs, the optimal tribological properties are obtained on the 2D F-Co-ZIF surface, with the friction coefficient as low as 0.0010. Electrical experiments, density functional theory (DFT) simulation, and fluorescence detection are used to explain the mechanism of fluorine doping regulation of tribological properties from the two stages, namely energy transfer and energy release. Specifically, the energy will transfer into the friction system through the generation of electron–hole pairs under an external excitation, and release by radiation and non-radiation energy dissipation channels. Fluorination reduces energy transfer by altering the electronic properties and band structures of ZIFs, and slows down the charge transfer by enhancing the shielding efficiency, thus slowing the non-radiative energy dissipation rate during the energy release stage. Our insights not only help us better understand the role of fluorine doping in improving tribological properties, but also provide a new way to further explore the electron energy dissipation pathway during friction.

Layered double hydroxides (LDHs) have the potential to be superlubricated materials due to their strong adsorption effect and weak internal interaction. However, obtaining stable superlubricity during the ultrafast time (< 10 s) is still a challenge. Here, we demonstrated macroscale superlubricity based on LDHs of multiple metal ions at high surface roughness, achieving superlow friction coefficients (0.006) and ultrafast wearing-in time (< 7 s), which mainly originated from tribochemical reactions and the formation of nanostructured adsorption layers. Through cross-sectional analysis and density functional theory, we revealed the properties of the protective tribofilm to achieve ultrafast superlubricity. LDHs strongly adsorbed on the surface of the bearing steel, and the sliding interface transformed into a heterogeneous interface between the polytetrafluoroethylene and LDH, leading to macroscale superlubricity. These findings demonstrate that tribochemical treatment of surfaces produces tribofilm that effectively reduces wearing-in time and promotes ultralow friction.

Polyalkylene glycol (PAG) aqueous solutions have recently been demonstrated to exhibit an ultralow friction coefficient (COF, μ < 0.01). However, the prolonged running-in period and low bearing capacity have limited its widespread application. In this study, we determined that the running-in period can be decreased by more than 75% when the pH value of the lubricant is controlled at 3 by introducing various acid solutions. Additionally, less time was required to realize stable superlubricity with inorganic acid at lower pH values. This was mainly attributed to the acceleration effect of hydrogen ions around the contact region. In case of PAG aqueous solution with organic acid, the wear loss between sliding solid surfaces was reduced, and thus the bearing pressure during the superlubricity period was significantly improved from approximately 30 to 160 MPa. Furthermore, the organic acid molecules were considered to form strong hydrogen bonds with PAG macromolecules and solid surfaces. This in turn strengthened the structure of the adsorption layers. The unique effect of different acids in aqueous polymer lubrication can potentially significantly aid in advancing the study of polymer tribology and broadening industrial applications.

Controlling friction by the electric field is a promising way to improve the tribological performance of a variety of movable mechanical systems. In this work, the assembly structure and microscale superlubricity of a host–guest assembly are effectively controlled by the electric field. With the help of the scanning tunneling microscopy (STM) technique, the host–guest assembly structures constructed by the co-assembly of fullerene derivative (Fluorene-C₆₀) with macrocycles (4B2A and 3B2A) are explicitly characterized. Combined with density functional theory (DFT), the distinct different assembly behaviors of fullerene derivatives are revealed at different probe biases, which is attributed to the molecular polarity of the fullerene derivative. Through the control on the adsorption behavior, the friction coefficient of host–guest assembly is demonstrated to be controllable in the electric field by using atomic force microscopy (AFM). At positive probe bias, the friction coefficient of the host–guest assembly is significantly reduced and achieves superlubricity (μ_min = 0.0049). The efforts not only help us gain insight into the host–guest assembly mechanism controlled by the electric field, but also promote the further application of fullerene in micro-electro-mechanical systems (MEMS).

Solid evidence is needed to demonstrate the effect of molecular orientation and structure on the frictional property of boundary lubricants. In this work, the frictional properties of phthalocyanine self-assembled monolayers (SAMs) with face-on (aromatic cores parallel to the substrate) and edge-on (aromatic cores stand on the substrate) orientations have been compared and the in situ structural variation of edge-on SAMs under frictional shear has been revealed by atomic force microscope (AFM). Face-on oriented SAMs show lower adhesion, lower friction, and stronger wear resistance, compared with edge-on oriented SAMs. Hierarchical structures of edge-on oriented SAMs have been revealed by frictional topography, which are consisted of nanoscale columns, micron-scale stripes, and centimeter-scale monolayer. The column structure deforms under increasing load force, leading to a stepwise friction force curve and a transition among three friction states (ordered friction, collapsed friction, and worn friction). The structural deformation depends on both the order degree and anisotropic stiffness of columns. Columns in phthalocyanine SAMs show a larger stiffness when shearing against molecular plane than shearing along the molecular plane. The presented study on the interfacial structure and frictional mechanism promisingly supports the designing of novel boundary lubricants and their application in engineering.

Finding the correct category of wear particles is important to understand the tribological behavior. However, manual identification is tedious and time-consuming. We here propose an automatic morphological residual convolutional neural network (M-RCNN), exploiting the residual knowledge and morphological priors between various particle types. We also employ data augmentation to prevent performance deterioration caused by the extremely imbalanced problem of class distribution. Experimental results indicate that our morphological priors are distinguishable and beneficial to largely boosting overall performance. M-RCNN demonstrates a much higher accuracy (0.940) than the deep residual network (0.845) and support vector machine (0.821). This work provides an effective solution for automatically identifying wear particles and can be a powerful tool to further analyze the failure mechanisms of artificial joints.