Volume 18 Issue 4

Castor oil is a widely used biomass energy source. In this paper, the process conditions for the preparation of sebacic acid by cracking castor oil using the microwave method were investigated using environmentally friendly and recyclable liquid paraffin (petrolatum) as a solvent. The optimum conditions for the reaction were determined in the experiments as follows: the mass ratio of solvent: castor oil: sodium hydroxide was 4:1:2.5 and the concentration of sodium hydroxide solution was 50% (w/t). The average microwave power was 210 W, the temperature was about 280 °C, the cracking time was 25 min under nitrogen protection, and the yield of sebacic acid was measured to be 85%. The solvents can be recycled and the recovered solvent can be used again without affecting the yield of sebacic acid. The solvent recovery was more than 92%.

In laboratory practice, several standards for testing the bending stiffness of corrugated board are used. There are often cases of tests where the results depend on the way the sample is placed on the supports. The problem arises when the board is five-ply (with two corrugated layers with different corrugation heights) or when the board has asymmetrically selected papers on the flat layers. This article focuses on the problem related to boundary conditions, with particular attention to the local effects of the support of the sample. Because the cardboard layers, both flat and corrugated, have a small thickness, a slight deformation of the papers can always be observed at the point of contact between the sample and the support, which affects the readings of the measured stiffness. The paper presents theoretical and numerical analyses showing how much the method of supporting the sample affects the measured bending stiffness of various samples. Numerical observations were compared with the results of analyses presented by other scientists as well as with experimental results.

Index levels of the process of pulping wheat straw (WS), industrial hemp stalks (HS), and Miscanthus x giganteus (MS) using the nitric acid-alkali (NA-A) method (HNO₃/KOH and HNO₃/NH₄OH two-stage sequential delignification systems) were determined. The research showed, as a rule, a lower total yield of NA-A pulps than kraft pulps from WS, HS, and MS, and a lower level of the tensile index and tear resistance compared to the properties of soda-AQ and kraft pulps presented in other studies, as well as the author’s own studies. Additionally, the levels of nitrogen (in different forms) and potassium in the combined post-pulping filtrate were determined. Their levels were found to be higher than in the fertilizer solution used to fertilize tomato crops grown on soilless substrates in greenhouses. However, application of filtrates from pulping of nonwoody plant straw using NA-A method requires determining the effectiveness of this type of fertilizer solution, its impact on the horticulture and agriculture plants, and the properties of their output including grains, tubers, and fruits.

Specimens of European beech wood (Fagus sylvatica L.) charred at 250 °C (4 min), 300 °C (2 min), and 350 °C (1 min) in combination with linseed oil coating were studied. The influence of the surface charring process and artificial weathering on surface discoloration, water absorption, and decay resistance were analyzed. Discoloration analysis showed a decrease in all parameters L*, a*, and b* due to the charring process. Coating with linseed oil caused a decrease in the L* parameter. An influence on parameters a* and b* was also demonstrated. As a result of the artificial weathering, the L* parameter increased in almost all groups. The group charred at 350 °C showed a decrease in L*. The parameters a* and b* were also affected. The effect of oil coating on discoloration during artificial weathering was negligible. The average water absorption of uncoated charred specimens decreased more than 50%. Damage due to artificial weathering disrupted the effect of the charring process. The effect of oil coating decreased depending on the length of partial immersion. Surface charring and oil impregnation slightly reduced the loss of beech wood mass caused by T. versicolor and P. placenta but could not fully protect the wood.

Different types of wood defects correspond to different processing methods. Good classification means can transform defective boards into practical boards after appropriate processing. The detection accuracy of the wood surface defects is particularly important for improving the utilization rate and speed of processing the boards. The RegNet stands out in the field of computer vision. It automatically designs the network model based on the design space and applies it to wood defect detection, which can improve the classification accuracy. When the convolutional structure of the RegNet network is applied to industrial detection and classification, the problems of long real-time detection time and large algorithm parameters persist. This study focuses on collecting wood material images of common coniferous and broad-leaved trees in Northeast China with three types of defects: wormholes, slip knots, and dead knots. To improve the allocation of computing resources, based on the RegNet network model, an attention mechanism module was added, and the Ghostconv structure was introduced. The structure quickly and accurately highlighted the types of wood defects, improved the classification accuracy, reduced the parameters of the network, and exhibited generalization ability. To verify the performance of the improved network, MobileNet-v2, EfficientNet, and Vision-Transformer networks were introduced for comparative analysis. The improved RegNet network had smaller weight and higher accuracy, with a classification accuracy of 96.58%.

Flame retardancy was induced in maple (Acer velutinum) and ash (Fraxinus excelsior) wood and bark by means of mixtures consisting of bio-based materials such as starch (S) and glue (G) and water-based paint, MINWAX (M) in two different combined formulations with perlite (P) as the main fire retardant. The selected wood species as solid wood with two different treatable surfaces (with and without bark) were examined. The lowest and the highest mass loss occurred in the untreated-ash and untreated-maple wood samples with bark, while the lowest weight percent gain was related to PSGM-treated ash wood samples with bark, and the highest weight percent gain was related to PSGM-treated maple wood samples without bark. The lowest time to ignition and glowing point time were measured in the untreated-maple wood samples without bark, and the highest of them were measured in the PSGM-treated ash wood samples without bark. The effect of bark in the treated- and untreated-maple samples on the time to ignition and glowing point time was greater than the bark of treated- and untreated-ash samples, respectively. There was not any significant relationship between actual retention, weight percent gain, and mass loss for all treatments. However, there was significant difference between the individual and interaction agents on fire retardancy of treated and untreated samples.

Cellulose nanocrystals (CNCs) with a high content of polar groups were prepared via the oxidation process by controlling the amount of mixed acid, incorporating additional additive of citric acid and vitamin C as active agents, and applying ultrasonic crosslinking. Subsequently, cellulose nanocrystal–silver (CNC–Ag) nanohybrid materials were synthesized via an oxidation hydrolysis reaction, which displayed good dispersibility and high interaction, leading to the hydrogen bonding between polar groups (-OH and -COOH) on the surface of CAC–Ag nanohybrids. The positive effects of hydrogen bonding on the surface of CAC–Ag nanohybrids were confirmed by the high carboxyl group content (2.69 mmol/g) and low contact angle (53.7°) tested. In addition, CAC–Ag nanohybrids showed significant antibacterial activity against both Gram-negative E. coli and Gram-positive S. aureus. These results showed that the high-performance CNC–Ag nanohybrids prepared in this study may be highly suitable as nano-fillers for polyester materials used in antibacterial food packaging.

The available surface defect detection methods for disposable wooden spoons still involve screening with the naked eye. This detection method is not only inefficient but also accompanied by problems such as false detection and missed detection. Therefore, this paper proposes a detection method based on an improved YOLOv5 network model (YOLOv5-TSPP). This method uses the K-Means ++ algorithm to cluster the target samples in the data set to obtain anchor frames that are more in line with different target scales. The Coordinate Attention module is added to the backbone network of the YOLOv5 network model to improve the feature extraction ability of the model. A new SPP module is added to the backbone network to increase the important features in the receptive field extraction network to improve the detection accuracy of small targets. The experimental results show: The YOLOv5-TSPP algorithm has better detection performance and the mAP of defect detection reaches 80.3%, which is 9.2% higher than that of the YOLOv5 algorithm. Among them, the detection accuracy of black knot defect reached 98.6%, the detection accuracy of back crack defect reached 92.1%, and the detection accuracy of mineral line defect reached 92.3%.

Elastic materials for seat foundations come in a variety of materials, shapes, and dimensions. However, it is difficult to measure the stress-strain relationships of many elastic material combinations by conventional uniaxial compression tests. This study investigated the stress-strain relations of elastic material combinations for foam foundations using finite element analysis (FEA). First, the stress-strain relations of single-layer polymer foams and a combination of double-layer polymer foams with covering were quantified by uniaxial compression tests, and axial tensile tests quantified the properties of the covering material of the fabric. Then, based on the Ogden foam and Ogden constitutive equation of Ansys Workbench 19.2, the test data of single-layer polymer foams and covering were fitted by a non-linear least square method, and a combination of double-layer polymer foams with the covering is predicted by FEA. When the strain was 10% to 65%, the stress error between FEA and test results dropped from 95.68% to -5.08%.

This study investigated the mechanical behaviour of Dou-Gong brackets with different structural forms, including Jixinzao and Touxinzao. Scaled Dou-Gong models were designed and fabricated at a 1:3.4 geometrical ratio. Vertical load tests were conducted to determine the failure modes, load-displacement response, stiffness degradation, and deformation capacity of the Dou-Gong models. Under vertical load, the primary failure modes of the Dou-Gong models were observed at the Lu-Dou, Nidao-Gong, and Hua-Gong component. The specimens demonstrated excellent load-bearing capacity and high deformation resistance. The Jixinzao Dou-Gong model exhibited a 15.0% higher ultimate load-carrying capacity than the Touxinzao Dou-Gong due to the presence of transverse arches. The number of transverse arches in the Dou-Gong models positively correlated with the compression stiffness, while their presence had a negligible effect on stiffness degradation rates. The Touxinzao Dou-Gong model exhibited superior ductility, characterized by a ductility coefficient 8.57% higher than that of the Jixinzao Dou-Gong model. Although the regular layering of the Dou-Gong models was disrupted by Ang component, the models remained stable in both the vertical and horizontal directions. The bi-linear model can effectively simulate the deformation behaviour of the Dou-Gong model under vertical load.