Acta Energiae Solaris Sinica•2026•DOI: 10.19912/j.0254-0096.tynxb.202608_9731
Fault diagnosis of wind turbine planetary gearboxes is severely constrained by the scarcity of high-quality fault data, as gearboxes operate predominantly in healthy states and automatic shutdowns prevent fault progression. This paper proposes a data-model jointly driven diagnosis method to address low diagnostic accuracy under limited fault samples. A high-fidelity lumped-parameter dynamic model of the planetary gearbox is constructed to generate pseudo-fault data, supplementing the training set. A domain-shared residual network feature extractor incorporating convolutional block attention modules extracts key physical features from both pseudo and measured data. Local maximum mean discrepancy aligns feature distributions at the fault-category level between pseudo and real fault data. A Kolmogorov-Arnold network module enhances the model's capacity to learn complex data relationships, enabling classification and identification of different fault types. Validation on a wind turbine planetary gearbox fault diagnosis test rig demonstrates that the proposed method achieves superior diagnostic performance under fault sample scarcity compared to classical methods. The framework offers an effective solution for known fault types, though identification of unknown and atypical faults remains a challenge for future work via open-set domain generalization.
The Chinese Journal of Process Engineering•2026•DOI: 10.12034/j.issn.1009-606X.225225
The non-Newtonian rheological properties of plastic melts are critical for regulating plastic processing, molding, and recycling processes, ensuring processing stability and product performance. However, rheological data for commonly used plastics and their blends remain incomplete. This study combined experimental testing and theoretical modeling to investigate the rheological behaviors of four pure plastics—polypropylene (PP), polyethylene (PE), polystyrene (PS), and acrylonitrile-butadiene-styrene copolymer (ABS)—and three binary blend systems: PE/ABS, PP/ABS, and PS/ABS. Rheological tests were conducted using a rheometer over a shear rate range of 0.1–100 s⁻¹ and temperatures from 180°C to 250°C. Results showed that the flow behavior index n was less than 1 for all samples, and apparent viscosity decreased significantly with increasing shear rate, indicating clear shear-thinning behavior. The consistency coefficient K followed the Arrhenius relationship with temperature, and melt viscosity decreased as temperature increased. The study quantitatively characterized the relationship between the mass fraction m (0.5 < m ≤ 1) of the main component in binary blends and melt viscosity. Based on experimental data, a component correction term was introduced into the traditional power-law model to construct a constitutive equation that simultaneously describes the effects of shear rate, temperature, and component fraction on melt viscosity. The average relative error between model predictions and experimental values was only 5.90%. These rheological data and the modified constitutive equation provide important theoretical support and data reference for optimizing process parameters in waste plastic recycling and injection molding.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4100-9
Shape memory droplet manipulation platforms have attracted significant attention due to their programmable droplet control capabilities. Current research primarily focuses on superhydrophobic surfaces and slippery lubricant-infused porous surfaces (SLIPS); however, these approaches suffer from vulnerable surface micro/nanostructures and loss of lubricant oils. Here, we report a shape memory quasi-liquid polydimethylsiloxane (PDMS) brush surface that overcomes these limitations. The surface is fabricated by introducing a SiO2 layer as a 'bridge' on a shape memory epoxy substrate, providing abundant functional groups for grafting PDMS brushes. By precisely controlling the SiO2 layer thickness and grafting conditions, the surface exhibits good shape memory properties and low adhesion to diverse liquids with varying surface tensions. Reversible anisotropic/isotropic droplet sliding control for both water and organic droplets is demonstrated through dynamic introduction/removal of groove structures, proving excellent droplet manipulation based on the combination of shape memory and low adhesion of PDMS brushes. Furthermore, the material can be applied as a functional coating on diverse substrates to impart anti-fouling and self-cleaning properties. This work introduces a nanoscale SiO2 layer as a 'bridge', offering a strategy to graft PDMS brushes onto polymer surfaces. Given the advantages of quasi-liquid PDMS brushes and programmable controllability of shape memory polymers, this work provides fresh ideas for developing droplet manipulation platforms.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4048-x
Selective oxidation of aromatic alkanes is a key reaction to produce high-value chemicals in the chemical industry. However, the strong C–H bonds and inert chemical properties of aromatic alkanes render the oxidation process difficult, thereby making the development of promising and sustainable catalysts highly desirable. Herein, a resin-assisted coordination co-assembly strategy is developed to synthesize heterometal-doped mesoporous Co3O4 with abundant oxygen vacancies, enabling precise control over both composition and pore structure. The site-specific Mn doping at octahedral sites of mesoporous Co3O4 promotes the formation of oxygen vacancy with enhanced activity. Density functional theory calculations further demonstrate that Mn doping in mesoporous Co3O4 reduces the oxygen vacancy formation energy, induces the electronic structure modifications and introduces the defect energy levels, finally promoting the efficient catalytic oxidation of a series of aromatic alkanes. Representatively, Mn-doped mesoporous Co3O4 exhibits remarkably outstanding catalytic activity, achieving 37% conversion of ethylbenzene and 97% selectivity for acetophenone under solvent-free conditions.