Research Articles

Wood materials have been used in many products such as furniture, stairs, windows, and doors for centuries. There are differences in methods used to adapt wood to ambient conditions. Impregnation is a widely used method of wood preservation. In terms of efficiency, it is critical to optimize the parameters for impregnation. Data mining techniques reduce most of the cost and operational challenges with accurate prediction in the wood industry. In this study, three data-mining algorithms were applied to predict bending strength in impregnated wood materials (Pinus sylvestris L. and Millettia laurentii). Models were created from real experimental data to examine the relationship between bending strength, diffusion time, vacuum duration, and wood type, based on decision trees (DT), random forest (RF), and Gaussian process (GP) algorithms. The highest bending strength was achieved with wenge (Millettia laurentii) wood in 10 bar vacuum and the diffusion condition during 25 min. The results showed that all algorithms are suitable for predicting bending strength. The goodness of fit for the testing phase was determined as 0.994, 0.986, and 0.989 in the DT, RF, and GP algorithms, respectively. Moreover, the importance of attributes was determined in the algorithms.

The radial variation and the genetic variation of wood properties between the parents and offspring of Populus deltoides were studied in this work. The chemical composition, density, and anatomical characteristics of Populus deltoides cl. ‘Danhong’ and its offspring exhibited the phenomenon of transgressive segregation. The chemical compositions of the parents and offspring were decreased in several attributes (benzene alcohol extract, hemicelluloses, lignin) with the increase of the cambial age. Moreover, the fibre length, fibre width, ratio of fibre length to width, and wall thickness to lumen ratio of parents and offspring were increased with cambial age. In addition, the densities of parents and offspring were increased with the increase of cambial age. There were significant differences in wood properties among Populus deltoides and its hybrids. These results indicated that Populus deltoides cl. ‘Danhong’ could be considered as pulp material and Populus deltoides cl. ‘Nanyang’ as building material. According to the radial variation rule of each material character, the rotation cutting period can be selected as years 7 or 8.

This study evaluated Parkia gigantocarpa wood from the Amazon rainforest for its permeability to air and liquid in the longitudinal direction. The influence of anatomical characteristics on the permeability of wood was characterized. Three trees were collected in the State of Pará, Brazil. Samples were converted into specimens and subjected to permeability tests and anatomical characterization. Permeability was obtained in the laboratory, and the results were compared with the permeability data estimated by a longitudinal flow model for hardwoods. The air permeability of wood was 140.2 x 10-9 m3.[m.(N.m-2).s]-1 liquid permeability was 3.28 x 10-9 m3.[m.(N.m-2).s]-1. The fiber length and thickness of the cell wall had a direct and positive relationship with the permeability, whereas fiber width presented an inverse relationship with permeability. The vessel frequency and diameter did not influence the permeability of wood from the heartwood of P. gigantocarpa that presented high permeability and potential for easy wood drying and treatment.

Binderless poplar powder compacts were prepared using the hot-pressing technology. The effect of the forming process on the mechanical properties and surface color of the poplar powder compacts was studied. The effect of forming temperature on mechanical properties and surface color was more noticeable than the forming pressure and the holding time. With the change of the forming process parameters, the static bending strength of the compacts increased first and then decreased. The overall change trend of the surface hardness increased continuously. The overall color difference (ΔE*) of the compacts increased with the change of forming process parameters and the surface color deepened gradually. The results of Fourier transform infrared (FTIR) spectroscopy showed that hemicellulose, cellulose, and lignin in the compacts were greatly affected by the forming process parameters. The degradation of hemicellulose and cellulose produced many colored substances, and the content of lignin increased. These made the surface color of compacts deepen.

The influence of the process parameters on the mechanical properties of compact wood powder generated via hot-pressing was analyzed through a single-factor experiment. The mechanical properties exhibited a nonlinear trend relative to the process conditions of hot-pressed compact wood powder. The relationship models between the process parameters and the mechanical properties for the compact wood powder were established by applying a multiple regression analysis and neural network methods combined with data from an orthogonal array design. A comparison between experimental and predicted results was made to investigate the accuracy of the established models by applying several data groups among the single-factor experiments. The results showed that the accuracy of the neural network model in terms of predicting the mechanical properties was greater compared with the multiple regression model. This demonstrates that the established neural network model had a better prediction performance, and it can accurately map the relationship between the process conditions and the mechanical properties of the compact wood powder.

Crack growth that takes place in natural fibre polymer composite formations is dependent on several factors, whereby primary crack size is a key aspect that influences uncertainty of the crack growth. The nucleation stage is strongly affected by the fracture collapse of structures, unavoidably affecting the accuracy of the estimation of total fatigue life. In this research, fatigue crack was examined using rice husk/polypropylene composite specimens across stress loads ranging from 80 to 90% for ultimate tensile strength at the stress ratios R=0.1, 0.3, and 0.5. Consequently, the propagation rate of the crack was dependent on the stress ratio. Crack resistance showed a drop in the propagation rate of the crack rate with an increase in the R value. This effect produced more fibres/matrix fracture at high stress ratio, in comparison to the low stress ratio, which was verified further through scanning electron microscopy. Moreover, the S-N curve method was proposed, as it facilitates the deterministic total fatigue life discovery in a highly favorable manner via equivalent crack size approach. A strong consensus was observed between the model of prediction and the outcomes of the experiment.

To prevent the illegal trade of precious wood in circulation, a wood species identification method based on convolutional neural network (CNN), namely PWoodIDNet (Precise Wood Specifications Identification) model, is proposed. In this paper, the PWoodIDNet model for the identification of rare tree species is constructed to reduce network parameters by decomposing convolutional kernel, prevent overfitting, enrich the diversity of features, and improve the performance of the model. The results showed that the PWoodIDNet model can effectively improve the generalization ability, the characterization ability of detail features, and the recognition accuracy, and effectively improve the classification of wood identification. PWoodIDNet was used to analyze the identification accuracy of microscopic images of 16 kinds of wood, and the identification accuracy reached 99%, which was higher than the identification accuracy of several existing classical convolutional neural network models. In addition, the PWoodIDNet model was analyzed to verify the feasibility and effectiveness of the PWoodIDNet model as a wood identification method, which can provide a new direction and technical solution for the field of wood identification.

Matched sets of clear specimens of poplar and pine wood were treated with 3, 5, and 8% (v/v) aqueous solutions of slow pyrolysis acid (PA) derived from date palm waste, to evaluate the effectiveness of PA in controlling mold growth on species of wood. Chemical compounds available in PA were identified by gas chromatography-mass spectrometry analysis. Treated and control specimens were contaminated with Aspergillus sp., then incubated in accordance to AWPA E24 (2017). Percentages of occupied surface by mold on each of control and treated specimen with respect to its total surface were evaluated by Image-J software. Comparisons of mean values of these determined ratios and physical examinations showed that, depending on species, the 5 and 8% water solutions of PA prohibited Aspergillus growth on tested woods. Experiments were also conducted on a matched set of small clear specimens of beech wood, impregnated by 3, 5, and 8% water solutions (v/v) of PA, using full-cell process and contaminated with decay fungus (Trametes versicolor), then incubated. Specifications of the EN 113 (1996) standard were followed. Weight loss was applied for comparing control and treated specimens. Average values of weight losses indicated that the 5% solution was effective, but 8% solution presented a better result.

Hybrid calcium carbonate (HCC) is prepared by pre-flocculating calcium oxide and ground calcium carbonate (GCC) with ionic polymers, and by injecting carbon dioxide to the pre-flocculated flocs until termination of the reaction at neutral pH. When used in papermaking, HCC gave higher bulk, higher stiffness, and higher tensile strength than GCC did. Furthermore, when higher wet pressing pressure was applied to the paper containing HCC, higher solid content was achieved with still better stiffness, smoothness, and tensile strength in comparison with the paper containing GCC. Actually, very high bulk of the HCC containing paper was compromisingly reduced to obtain high solid content by applying higher wet pressing pressure. Higher solid content achieved by combination of HCC technology and higher wet pressing pressure resulted in paper drying energy savings of more than 10%, while a high quality of all the essential printing paper properties was maintained. Drying energy savings may contribute to greenhouse gas (GHG) reduction and lowering of the paper production cost.

Bamboo material has excellent properties and is suitable for making bamboo furniture. Bamboo furniture is a traditional form of furniture made from bamboo with a low degree of industrialisation. The diverse development methods and profound cultural meanings behind bamboo furniture should be further explored to strengthen inheritance and innovation. This paper first summarises the characteristics and development status of bamboo furniture via a brief literature review. Then, through case studies and questionnaire surveys, the aesthetic trends of modern bamboo furniture design were analysed, and various ideas for innovation were proposed. The mode and path of the future development of bamboo weaving were discussed from the perspective of accelerating modernisation. To achieve sustainable development of bamboo furniture, to promote bamboo culture, and to enable bamboo enterprises to establish a good brand image, it is necessary to use the interactive design platform to coordinate the relationship between users, enterprises, and producers, and to grasp the balance between traditional craftsmanship and modern design and manufacture through modern advanced manufacturing technology and parametric design.