This study examines the effects of different addition levels of tungsten (W) content on the microstructure, corrosion resistance, wear resistance, microhardness, and phase composition of coatings made from FeCoCrNiAl high-entropy alloy (HEA) using the laser cladding technique. Using a preset powder method, FeCoCrNiAlW_x (where x represents the molar fraction of W, x = 0.0, 0.2, 0.4, 0.6, 0.8) HEA coatings were cladded onto the surface of 45 steel. The different cladding materials were tested for dry friction by using a reciprocating friction and wear testing machine. Subsequently, the detailed analysis of the microstructure, phase composition, corrosion resistance, wear traces, and hardness characteristics were carried out using a scanning electron microscope (SEM), X-ray diffractometer (XRD), electrochemical workstation, and microhardness tester. The results reveal that as the W content increases, the macro-morphology of the FeCoCrNiAlW_x HEA cladding coating deteriorates; the microstructure of the FeCoCrNiAlW_x HEA cladding coating, composed of μ phase and face-centered cubic solid solution, undergoes an evolution process from dendritic crystals to cellular crystals. Notably, with the increase in W content, the average microhardness of the cladding coating shows a significant upward trend, with FeCoCrNiAlW_0.8 reaching an average hardness of 756.83 HV_0.2, which is 2.97 times higher than the 45 steel substrate. At the same time, the friction coefficient of the cladding coating gradually decreases, indicating enhanced wear resistance. Specifically, the friction coefficients of FeCoCrNiAlW_0.6 and FeCoCrNiAlW_0.8 are similar, approximately 0.527. The friction and wear mechanisms are mainly adhesive and abrasive wear. In a 3.5 wt.% NaCl solution, the increase in W content results in a positive shift in the corrosion potential of the cladding coating. The FeCoCrNiAlW_0.8 exhibits a corrosion potential approximately 403 mV higher than that of FeCoCrNiAl. The corrosion current density significantly decreases from 5.43 × 10⁻⁶ A/cm² to 5.26 × 10⁻⁹ A/cm², which suggests a significant enhancement in the corrosion resistance of the cladding coating.

In this study, laser cladding of CoCrFeNiMnTi_x (x is the proportion of the mass of a material, x = 0.0, 0.2, 0.4, 0.6, 0.8) high-entropy alloy (HEA) composite powder coating on 45 steel substrate was studied by using the method of preplaced powder. The phase composition, morphology, microhardness, corrosion resistance and wear properties of CoCrFeNiMnTi_x high entropy alloy were analyzed by XRD, SEM, microhardness tester, electrochemical workstation and reciprocating friction wear tester, respectively. The influences of Ti concentration on structure and properties of CoCrFeNiMn HEA laser cladding coating were discussed. The macromorphology of CoCrFeNiMnTi_x HEA coating layer becomes worse with the increase in Ti quantity. The coating layer is a face-centered cubic solid solution phase. The microstructure of the coating layer is dominated by dendrites and equiaxed crystals. The average microhardness of the coating layer grows with the increases in Ti content, and CoCrFeNiMnTi_0.8 can reach 823 HV. The friction coefficient of the cladding coating gradually reduces and the wear resistance adds as Ti content rises; the friction coefficients of CoCrFeNiMnTi_0.6 and CoCrFeNiMnTi_0.8 cladding coating are similar, at 0.835 and 0.828, respectively. Adhesive and abrasive wear are the two basic types of cladding coating wear. In 3.5 wt.% NaCl solution, the corrosion potential of cladding coating increases with increases in Ti content, the corrosion potential of CoCrFeNiMnTi_0.8 is about 244 mV higher than that of CoCrFeNiMnTi₀, and the density of corrosion current drops to 3.41 × 10⁻⁶ A/cm² from 7.17 × 10⁻⁵ A/cm².

Milk jujube has become an increasingly popular tropical fruit. The sugar content, which is commonly represented by the soluble solid content (SSC), is a key indicator of the flavor, internal quality, and market value of milk jujubes. Traditional methods for assessing SSC are time-consuming, labor-intensive, and destructive. These methods fail to meet the practical demands of the fruit market. A rapid, stable, and effective non-destructive detection method based on visible/near-infrared (Vis/NIR) spectroscopy is proposed here. A Vis/NIR reflectance spectroscopy system covering 340–1031 nm was constructed to detect SSC in milk jujubes. A structured spectral modeling framework was adopted, consisting of outlier elimination, dataset partitioning, spectral preprocessing, feature selection, and model construction. Comparative experiments were conducted at each step of the framework. Special emphasis was placed on the impact of outlier detection and dataset partitioning strategies on modeling accuracy. A data-augmentation-based unsupervised anomaly sample elimination (DAUASE) strategy was proposed to enhance the data validity. Multiple data partitioning strategies were evaluated, including random selection (RS), Kennard–Stone (KS), and SPXY methods. The KS method achieved the best preservation of the original data distribution, improving the model generalization. Several spectral preprocessing and feature selection methods were used to enhance the modeling performance. Regression models, including support vector regression (SVR), partial least squares regression (PLSR), multiple linear regression (MLR), and backpropagation neural network (BP), were compared. Based on a comprehensive analysis of the above results, the DAUASE + KS + SG + SNV + CARS + SVR model exhibited the highest prediction performance. Specifically, it achieved an average precision (AP_p) of 99.042% on the prediction set, a high coefficient of determination (R_P²) of 0.976, and a low root-mean-square error of prediction (RMSEP) of 0.153. These results indicate that Vis/NIR spectroscopy is highly effective and reliable for the rapid and non-destructive detection of SSC in milk jujubes, and it may also provide a theoretical basis for the practical application of rapid and non-destructive detection in milk jujubes and other jujube varieties.