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To setup a theoretical model for grasping cutting pieces of garment better, which will help to design a special soft gripper and push forward the automated level of garment manufacturing.

This paper first analyzed the mechanics of the grasping process and concluded the main factors that affect the success of grasping. A theoretical model named grasping fabric model (GFM) was constructed to show the mechanical relationship between the soft gripper and the fabric pieces. Subsequently, two fabric samples were selected and tested for their friction properties and critical buckling force, and the test data were substituted into the theoretical model GFM to obtain the grasping parameters required for fabric grasping layer by layer.

It was found that (1) the critical buckling force of the fabric is mainly influenced by the bending stiffness and the deformation length of the fabric during grab. (2) The difference between the friction between the soft gripper and the fabric and the friction between the fabric, that is DF1-2, has an important influence on the accuracy of grasping layer-by-layer.

It showed that the grasping parameters provided by GFM enable the two samples to be more effectively separated layer by layer, which verifies that the GFM model is strong enough for the possible application in garment automated production.

Current multi-source image fusion methods frequently overlook the issue of detailed features when employing deep learning technology, resulting in inadequate target feature information. In real-world mission scenarios, such as military information acquisition or medical image enhancement, the prominence of target feature information is of paramount importance. To address these challenges, this paper introduces a novel infrared-visible light fusion model.

Leveraging the foundational architecture of the traditional DenseFuse model, this paper optimizes the backbone network structure and incorporates a Unique Feature Encoder (UFE) to meticulously extract the distinctive features inherent in the two images. Furthermore, it integrates the Convolutional Block Attention Module (CBAM) and the Squeeze and Excitation Network (SE) to enhance and replace the original spatial and channel attention mechanisms.

Compared to other methods such as IFCNN, NestFuse, DenseFuse, etc., the values of entropy, standard deviation, and mutual information index of the method presented in this paper can reach 6.9985, 82.6652, and 13.6022, respectively, which are significantly improved compared with other methods.

This paper presents a UFEFusion framework that synergizes with the CBAM attention mechanism to markedly augment the extraction of detailed features relative to other methods. Moreover, the framework adeptly extracts and amplifies unique features from disparate images, thereby elevating the overall feature representation capability.

Based on the pursuit of improving the temperature endurance capabilities of conventional superalloys for hot-end components, this paper aims to investigate the failure mechanisms of yttria-stabilized zirconia (YSZ) coatings fabricated by the atmospheric plasma spraying method at 1220 °C and 1260 °C.

Thermal spraying techniques are applied to produce thermal barrier coatings (TBCs) that offer superior thermal insulation, thermal shock resistance and thermal stability. The oxidation kinetics, the propagation patterns of cracks and the phase stability prior to failure of the coating were analyzed in detail.

The failure of coatings during static isothermal oxidation process is caused by slow crack initiation and propagation in the densification stage. External stress induces rapid initiation and propagation of cracks, leading to coating phase transformation. Cracks create pathways for oxygen diffusion and accelerate the growth of oxide layers.

This work aims to provide reliability data on the failure of TBCs, elucidate the high-temperature service characteristics of TBCs and provide theoretical basis for its performance improvement under extreme conditions.

The marine environment presents a great challenge to the anticorrosion properties of organic coatings applied on equipment. Since the compactness of coatings is critical in marine environments, a novel nepheline-epoxy resin (N-EP) composite was introduced into organic coatings to improve the interfacial compatibility between the pigments and the binder. The purpose of this study is to evaluate the effectiveness of the N-EP composite in enhancing the corrosion resistance of the coatings in marine conditions.

These composite particles were prepared via the mechanical ball milling method at thermofield-assisted, leading to chemical bonding between inorganic nepheline and epoxy resin, the agglomeration of particles was avoided by this method. Fourier transform infrared spectroscopy, transmission electron microscope, particle size distribution, sedimentation and thermogravimetric-differential thermal analysis were used to verify the feasibility of thermal field-assisted mechanochemistry for achieving a direct reaction between epoxy resin and nepheline powder, as well as to determine the optimal reaction conditions. Additionally, water absorption tests, Electrochemical impedance spectroscopy and scanning electron microscope were conducted to assess the anticorrosive properties of the modified nepheline coatings.

The results further indicated that N-EP improved the barrier performance and mechanical properties of the coating. For example, after modified, the tensile strength of coating had increased from 41.96 ± 0.05–63.14 ± 0.05 MPa. This can be attributed to the less defective N-EP/binder interface and the uniform dispersion of N-EP in the coating. The optimal preparation conditions (500 r/min of ball grinding speed and 6 h of ball grinding time) for the composites were also studied for a superior corrosion resistance of the coating.

Thermofield-assisted mechanochemistry enables direct reactions between epoxy resin and nepheline powder, enhancing the dispersion stability and interfacial compatibility of N-EP. This modification improves coating compactness, reduces porosity and enhances corrosion resistance by strengthening the labyrinth effect on water diffusion.