European Journal of Wood and Wood Products最新文献

Eucalyptus pellita is cultivated for pulpwood in tropical and subtropical regions but remains underutilised for structural applications, particularly in dry tropical environments. Compared to well-studied species such as Eucalyptus grandis and Eucalyptus globulus, its potential in engineered wood products is poorly understood. As plantation industries seek to diversify products and increase wood value, understanding the structural suitability of E. pellita hybrids is critical. This study evaluated the performance of E. pellita and its F1 and backcross hybrids across two dry tropical sites, spanning log quality, product recovery, structural properties, and genetic associations. Billets were assessed for form, diameter, and defects. Sawing and peeling trials quantified recovery rates and defects. Laminated veneer lumber (LVL) was fabricated from hybrid veneers and tested for density, modulus of elasticity (MOE), modulus of rupture (MOR), and bond quality. The E. pellita x Eucalyptus brassiana hybrid achieved highest recoveries among the materials tested (sawn board recovery up to 49.2%; green veneer recovery up to 83.6%). The highest-performing LVL (layup 3) from this hybrid achieved an MOE of 18.8 GPa and MOR of 139 MPa. Genetic analysis using a targeted panel of ~ 5500 single nucleotide polymorphism (SNP) markers identified significant associations above the –log₁₀(p) = 1.30 threshold for end split (SNP1358), knot diameter (SNP3201), and heartwood proportion (SNP2187). Although statistical power was limited by sample size, these findings highlight the potential of E. pellita hybrids for structural applications and demonstrate the value of integrating phenotypic and molecular data to support tropical hardwood breeding and utilisation strategies.

Robinia pseudoacacia L. has a valuable wood due to its natural durability and resistance to decay and external environments. This durability is attributed to its high content of extractives and the amount of tyloses in earlywood vessels. Given the widespread occurrence of black locust across Hungary, the wood chemical components may differ depending on site growth conditions. This research investigated the chemical extractives and color parameters of wood from Robinia pseudoacacia L. from different counties and growth conditions in Hungary. The relationship between chemical extractives and color based on the CIElab system was also analysed. The results indicated that both counties and growth conditions showed significant variations in chemical extractives and color parameters. The counties of Vas and Győr-Moson-Sopron exhibited the highest total contents of extractives, polyphenol, antioxidant capacity and intense lightness. Compatible outcomes were recorded under poor growth condition mixed species. Lightness was significantly associated with extractives from methanol-water and total phenol contents with lightness. While the extractive from the cyclohexane-ethanol solvent system was linked with all color parameters. Subsequent research will investigate the impact of extractives on wood durability under different locations and growth conditions.

Wooden dowels transfer load in timber connections through combined mechanisms, including longitudinal shear, bending and embedment. Shear properties parallel to the grain are essential for mechanics-based stiffness models and numerical simulations of wooden dowel connections, yet no standardised method exists for their determination. This study addresses this gap by investigating and optimising shear-testing methods for wooden dowels using experimental and numerical approaches. This study compares four shear-testing approaches for determining the shear strength of wooden dowels using a compression test setup, supported by experimental work, numerical modelling and fundamental mechanics. Parametric FEA in LS-DYNA was conducted to optimise specimen geometry, and the effects of notch-end shape, notch width, failure-plane height and specimen length on stress distribution and failure mode were assessed. Among the four methods, the 45° double-notched specimen was identified as the most effective for generating an approximately pure shear state. Digital Image Correlation (DIC) was used to evaluate five strain-gauge areas and five strain-calculation methods. The validated configuration was then used for further shear testing. The study shows that all optimised specimen configurations produce comparable shear strengths parallel to the grain, indicating the potential suitability of these methods for wooden-dowel shear testing. However, notch shape, notch width, failure-plane height and specimen length must be properly optimised to ensure shear-dominated failure. Smaller virtual strain-gauge areas, particularly the thin-line area method between notch tips, provide more representative shear-strain measurements and shear-modulus values. Numerical modelling using MAT-143 successfully captured the post-peak softening behaviour and supports its use for shear simulations.

Brittleheart, also known as compression failure, is a widespread phenomenon observed in numerous tropical wood species, significantly diminishing their strength properties. According to strength grading standards such as BS 5756, NEN 5493 and EN 16,737, timber exhibiting brittleheart characteristics must be rejected. Oftentimes brittleheart remains undetectable on the outer surface and cross-section of sawn timber. This study focuses on qualitatively characterizing compression failures in tropical hardwood and its mechanical properties. In this context, various non-destructive detection methods were explored. Five grades of compression failures were characterized based on the deformation and displacement of wood tissue. Results demonstrate that CT-scanning shows promising as a technique for detecting these five defined grades. Quantitative assessments of brittleheart on the mechanical properties were conducted to determine bending strength (f_m) and modulus of elasticity (E_m). Multiple regression models were developed to predict the bending strength with a highest coefficient of determination (R²) of 0.778 and a relatively high SEE of 17 N/mm².

Surface roughness of heat-treated and sanded wood is a crucial quality indicator in the furniture and woodworking industries. Predicting surface roughness in advance can reduce costs, improve production efficiency, and ensure better compatibility with subsequent material and coating applications, thereby improving overall quality and consistency while supporting more sustainable production. In this study, Siberian pine wood was heat-treated at different temperatures and subsequently sanded on a belt sander using various grit sizes. Taguchi design and Response Surface Methodology (RSM) were first employed to identify and quantify the significance of process parameters affecting surface roughness. Based on these results, several machine learning-based models, including Decision Tree (DT), Gaussian Process Regression (GPR), Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM), together with RSM, were developed to predict the roughness values of heat-treated and sanded wood. Heat treatment temperature, sandpaper grit size, and grain direction were considered as input variables for the prediction of Ra and Rz surface roughness parameters. Taguchi and RSM analyses revealed that all three factors have a statistically significant effect on surface roughness. Among the tested models, GPR achieved the highest prediction accuracy and was identified as the most suitable approach for modelling the roughness performance of sanded, heat-treated wood surfaces.

This paper investigates the potential of wood stabilisation techniques in improving the mechanical and acoustical properties of temperate wood species to make them suitable for musical instrument making. Many instruments or parts are usually made with tropical woods, specifically woodwind instruments and fingerboards of chordophones. For these applications, the wood must be stable, with low porosity and good machinability. The increasingly strict regulations on international trade of vulnerable species reduce the availability of such species. Therefore, a wood stabilisation process using methyl methacrylate impregnation is proposed, focusing on these specific domain criteria. This aims to achieve properties approaching those of African blackwood (Dalbergia melanoxylon) used for clarinet and oboes, and African ebony (Diospyros crassiflora) used for chordophones fingerboards. Ten different temperate wood species and six specimens (tubes) per species were tested with this process. The Shore-D hardness, hygroscopic behaviour of wood through roundness, moisture exclusion efficiency and anti-swelling efficiency, the acoustic loss factor of the cavity and the density of samples were compared before and after stabilisation. The results suggest that hornbeam (Carpinus betulus), maple (Acer spp.) and beech (Fagus sylvatica) can be used as stabilised materials, for several applications, with improved properties. Generally, the density and hardness are significantly improved and acoustic loss factors and swelling are reduced, to reach values suitable for instrument making, whilst not reaching absolute values of tropical reference woods.

For the natural fiber-reinforced composite materials, such as the recombinant bamboo obvious creep behavior is usually observed. In this paper, the compressive creep property of the material was chosen as the research subject. First the standard compressive fracture experiment was carried out to provide the basic stress level parameters for the compressive creep test. Then the creep experiment under four different stress levels was conducted to record the strain evolution process. Finally the creep property was analyzed based on different selected models and the stress level effect. The results showed that the stress level affects the creep property obviously. The creep strain growth speed under higher stress levels is much quicker than that under lower stress levels. In addition, compared with the traditional Burgers model, the combination of the variable-order fractional derivative defined Maxwell model and the stress level defined model parameters can provide excellent performance in fitting the strain evolution process during the whole experiment period, which makes it worth popularizing and utilizing in actual engineering.

Recently, utilization of Wood Plastic Composite (WPC) panels has grown in both indoor and outdoor settings. Drilling these panels are essential for installation, assembly, and securing components productivity. This study focuses on developing predictive modeling and optimization for drilling WPC composite panels by considering the machining parameters, mean roughness depth (R_z), and average surface roughness (R_a). An experimental design based on an L₂₇ orthogonal array is employed, along with regression and Artificial Neuro-Fuzzy Inference System (ANFIS) approaches to enhance prediction accuracy for R_a and R_z. Also, the key input parameters have included diameter of drill bit (d), feed rate (f), and spindle speed (N). The results have indicated that R_a and R_z are mainly influenced by f and d, which increase the roughness owing to enhanced cutting forces and poor chip evacuation. Conversely, higher N and lower f reduce the R_a and R_z. Optimized parameters identified through desirability-based methods are N = 3000 rpm, f = 75 mm/min, and d = 6 mm. Results showed that ANFIS prediction models outperform response surface methodology (RSM) models with higher R² values of 0.9525 and 0.9581 for R_a and R_z with root mean squared error value of 0.87 and 2.52 (R_a and R_z) that are lower than RSM models. This study introduces the ANFIS model approach integrated with particle swarm optimization (PSO) and hippopotamus optimization algorithm (HOA), to enhance the performance of the drilling of WPC. This enables more accurate and reliable optimization of R_a and R_z compared to previous single or non-hybrid algorithm approaches.

This study explores the optimal loading and processing parameters for incorporating nano-zinc oxide (nano-ZnO) into urea–formaldehyde (UF) resin to fabricate enhanced medium density fibreboards (MDFs). Enhanced MDF panels would in turn address challenges such as moisture sensitivity, biological durability, and formaldehyde content. Nano-ZnO was added at three loadings (1%, 2%, and 3%) and sonicated for 5, 10, and 15 min to optimize dispersion quality and evaluate the structure–property relationship. MDFs prepared with these formulations were tested for physical, mechanical, mycological properties, and formaldehyde content. Nano-ZnO loaded UF resin dispersions were characterised using SEM and XRD and showed well-dispersed formulations. Incorporation of nano-ZnO improved dimensional stability and strength, reduced fungal spread, and lowered the formaldehyde emission by up to 73%. These improvements are attributed to enhanced resin cross-linking and uniform nanoparticle dispersion, which reduced hydrophilicity and increased bonding efficiency. The 1% nano-ZnO formulation showed the highest mechanical improvement, while 3% provided the best antifungal performance. The study demonstrates that controlled sonication and optimal nano-ZnO loading can significantly enhance the performance and sustainability of MDF panels.

In this study, Eucalyptus urophylla × grandis particles were used as the raw materials and poly-4,4′-diphenylmethane diisocyanate (pMDI) served as the adhesive. A two-way experimental design was employed to systematically investigate the combined effects of particle moisture content (PMC, 3%, 6%, 9%, and 12%) and resin content (RC, 3%, 6%, and 9%) on the physical and mechanical properties of particleboard. Fluorescence microscopy and digital image correlation (DIC) were integrated to elucidate the structure-property relationships between bonding interface characteristics and board-level mechanical behavior. The results showed that a balanced combination of PMC and RC markedly improved the bonding quality and overall performance of particleboard. Optimal performance was achieved at 9% PMC and 3% RC, where all mechanical and dimensional stability indicators met the GB/T 4897 − 2015 P2 type standard. Fluorescence microscopy revealed that moderate increase in PMC and RC enhanced adhesive dispersion and promoted the formation of a continuous three-dimensional bonding network at the particle interface. DIC analysis further indicated that optimized bonding conditions led to more homogeneous strain distribution and reduced localized shear concentration during bending. These findings provide fundamental insights into the interfacial mechanisms governing pMDI-bonded particleboard performance and offer valuable guidance for the design and production of high-performance, moisture-adaptive particleboard.