Wood Science and Technology最新文献

Addressing the challenges of low classification accuracy and protracted identification times posed by lightweight convolutional neural networks (CNNs) for wood micrograph classification, this study introduces ARNet, a novel model tailored for wood CT image analysis.ARNet significantly enhances the overall image recognition performance by boosting its dynamic feature extraction capabilities and refining its proficiency in processing salient features.The methodology employs residual dynamic convolution that dynamically aggregates convolutional kernels in response to the input image, optimizing adaptability.This optimized field of view across disparate feature layers facilitates the extraction of critical information such as wood texture, pore distribution, and cellular arrangement, thereby enhancing analytical depth.Additionally, ARNet incorporates multi-scale dilated attention mechanisms to capture nuanced feature maps across multiple scales, thereby broadening the scope of feature analysis.This approach not only achieves a profound understanding and efficient processing of the input data but also accentuates critical features, significantly enhancing the distinguishability between diverse image categories.The combination of CNNs and Transformers not only extracts rich local and global information but also captures unique features of images on a point-to-point basis, thereby improving classification accuracy. Experiments were conducted on the Mini-ImageNet, CIFAR100, and CIFAR10 public datasets. The results show that ARNet achieved top-1 accuracies of 65.21%, 78.32%, and 93.39% on Mini-ImageNet, CIFAR100, and CIFAR10, respectively, outperforming other models such as RMT, TCFormer, and SSViT. Additionally, we applied ARNet at the Shandong base of the national wood industry engineering research center to identify transverse section micrographs of 20 precious wood types, achieving an accuracy of 99.50% on the test set. After loading the parameters into the re-parameterized model, the validation set accuracy was 99.20%, with a detection time of 0.024s per image. This demonstrates that by combining residual dynamic convolution with multi-scale dilated attention, the accuracy and real-time performance of wood micrograph classification can be effectively improved.

The strength degradation resulting from duration-of-load (DOL) effect and bacterial decay poses significant challenges to historical timber piles. Many historical European cities still heavily rely on the infrastructure supported by their original timber foundations. A reliable modelling approach on the structural performance of timber piles is needed to avoid the economic loss caused by closing down infrastructure. In this work, we consider a simplified bacterial decay model and develop a numerical framework to integrate the decay model into a standard DOL model. Two approaches are proposed and compared: one considering the homogenised effect of bacterial decay over the entire cross section, and the other taking into account the localised failure accelerated by bacterial decay and applying stiffness reduction to allow stress redistribution. Although the homogenised failure criterion is found to potentially underestimate the effect of bacterial decay, both approaches are able to capture the designated decay pattern. Ultimately, there is a potential for future extension to more intricate loading conditions and decay patterns.

Biological deposition is commonly observed on wooden shipwrecks. This study employs analytical techniques, including optical microscopy (OM), scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS), X-ray diffraction (XRD) and Fourier infrared transform spectroscopy (FTIR), to investigate the microscopic morphology and structural composition of barnacles and their adhesion to the wooden surface of the Yangtze Estuary II shipwreck. Results indicate that microorganisms like diatoms and Trichoderma spp. were present at the interface between the barnacles and the wooden surface. These microorganisms played a crucial role in the formation of SiO₂, CaHPO₄•2(H₂O), FeO(OH) and CaCO₃. Specifically, the bio-mineralized cell walls of diatoms and their cellular contents, including polyphosphates, provided the necessary Si and P for SiO₂ and CaHPO₄•2(H₂O), respectively. Furthermore, during their metabolic processes, diatoms and Trichoderma spp. supply dissolved Fe ions, which contribute to the formation of FeO(OH) on the wooden surface. This study elucidates four types of bio-mineralized products resulting from microbial activity on the salvaged wooden shipwreck.

Phase-change transparent wood (TW/DO-OTS) has the characteristics of energy storage, light transmission and regulates environmental temperature by absorbing or releasing energy during the phase-change process, in line with the double carbon goal. This research proposes an optimization of the interfacial compatibility of TW/DO-OTS, aiming to further improve the photothermal performance and mechanical strength of the samples. The wood templates were obtained by removing lignin in the wood, then the wood templates were modified by octadecyl trichlorosilane (OTS) solution, and finally TW/DO-OTS was prepared by introducing dodecanol/epoxy resin (DO/EP). The setting of OTS processing parameters is the key step of interface optimization, which is determined by single-factor experiment and response surface method. The TW/DO-OTS obtained through interface optimization has the transmittance of 92.50%, the melting temperature of 25.54 °C, and the melting latent heat of 88.96 J/g. It has good dimensional stability and high tensile strength. The energy storage of TW/DO-OTS is jointly provided by dodecanol inside the wood cell cavity and the cell wall. This wood-based green composite with light temperature responsiveness will become an ideal material choice for energy-saving buildings, temperature sensors, and cold chain transportation packaging in the future.

Microbial degradation of lignocellulose is a complex process mainly carried out by filamentous fungi and bacteria. Among prokaryotes, the genus Streptomyces stands out, with laccases playing a key role in its lignocellulolytic enzyme system. However, bacterial laccases have a lower redox potential than fungal laccases, suggesting that their action on lignin is indirect, via high redox potential intermediates. Prominent examples of intermediates are hydroxyl radicals. In Basidiomycota fungi, the production of these radicals occurs through quinone redox cycling, involving a Fenton reaction. This study demonstrates, for the first time, extracellular hydroxyl radical production via quinone redox cycling in the bacterium Streptomyces cyaneus CECT 3335, with laccase playing an essential role. The process begins with the extracellular oxidation of quinones to semiquinones, catalyzed by laccase. In the presence of Fe³⁺, semiquinones produce hydroxyl radicals via a Fenton reaction. The cycle is restored through quinone reduction by mycelium-associated reductase activity. H₂O₂ production, Fe³⁺ reduction, and hydroxyl radical generation were confirmed in S. cyaneus. The key role of laccase was verified using a mutant strain lacking laccase activity, in which hydroxyl radical production was absent. The oxidative potential of this mechanism in S. cyaneus was evidenced by the degradation of non-phenolic lignin-related compounds homoveratric acid and veratraldehyde and by the ability to depolymerize kraft lignin. This novel finding of quinone redox cycling in bacteria has important implications for Streptomyces’ role in lignin degradation, as well as potential biotechnological applications, including lignin biotransformation and bioremediation of organic pollutants.

In regions where microbial contamination of groundwater and surface water remains a significant public health concern, leading to around 505,000 annual deaths, there is an urgent need for accessible, cost-effective, and simple household water treatment solutions. This study investigated the feasibility of wood as a filtration system, with a focus on its ability to remove nanoparticles. The research underscores the remarkable potential of wood filters, particularly in radial and tangential directions, exhibiting superior particle removal capabilities (> 99%) due to extended residence time and intricate microstructures. The study reveals that wood type selection in this study, i.e., yellow poplar (Liriodendron tulipifera), European beech (Fagus sylvatica), Douglas fir (Pseudotsuga menziesii), and silver fir (Abies alba), plays a crucial role in filtration efficiency, with beech emerging as a high-performing option alongside silver fir. Importantly, the optimal range of size exclusion was identified (160–490 nm), aiding in designing wood filters for specific particle size reduction goals. Wood filters also show great potential for removing a broad range of microorganisms, i.e., bacteria and protozoa, as well as nanoplastics and microplastics, which could have profound implications for water treatment and environmental remediation. Furthermore, the study highlights the adsorption/diffusion process through the amorphous domains of the wood biopolymers, i.e., cellulose, hemicelluloses and lignin, enhanced by electrostatic interactions in the filtration efficiency for small organic molecules, providing valuable insights into filtration mechanisms.

Species identification of carbonized wood holds significance for various scientific disciplines, including botany, palaeontology, and archaeology. Identification also contributes to the preservation of endangered wood species and forests, and supports climate research. With regard to the identification of wood and wood products, all international research institutions adhere to the IAWA list of microscopic features for hardwood and softwood identification, established by the IAWA Committee in 1989.

Our comparative anatomical studies of 30 different species reveal significant dimensional losses of quantitative features during the charring process. Specifically, the findings indicate a shift in size classes, with varying percentages of loss in anatomical features from solid wood to charcoal for most of the taxa analyzed. Consequently, the size classes defined in databases for solid wood differentiation cannot be directly applied to charcoal identification. Furthermore, the present study employs statistical evaluations to illustrate the application of conventional size classes for the parameters: tangential diameter of vessel elements, intervessel pit diameter, ray height, and width. The implications of these findings for charcoal research are discussed in detail.

The Young’s modulus and loss tangent of a Sitka spruce wood sample in the longitudinal direction were determined using free flexural vibration (FRFV) and forced flexural vibration (FOFV) tests. During the tests, the attached weight and sample length were varied, and their effects on the Young’s modulus and loss tangent of the sample were examined. The Young’s modulus could be accurately and easily obtained from both the FRFV and FOFV tests using a modified Euler-Bernoulli’s equation, with the effect of the attached weight mitigated. No significant difference was observed between the two values of the Young’s modulus obtained from the two tests. The loss tangent slightly increased as the attached weight increased when the ratio of attached weight/sample weight was below 10%; however, it significantly increased with the increase in the attached weight when the ratio of the attached weight/sample weight exceeded 10%. The values of the loss tangent obtained from the FOFV tests for different samples were often higher than the corresponding values obtained from the FRFV tests, whereas the loss tangent values of different samples obtained from the FOFV tests were lower than the corresponding values obtained from the FRFV tests.

Monomer impregnation is a great strategy to modify various wood properties. By choosing the right impregnant, it may lead to a higher flame retardancy of treated wood, contributing to its use in specific sectors such as building interior finishes. Yellow birch (Betula alleghaniensis Britt.) and sugar maple (Acer saccharum Marsh.) were surface-impregnated with an acrylate and a phosphorus acrylate monomer under vacuum and exposed to an electron beam for polymerisation. A surface chemical retention of 100 g.m^− 2 was obtained for sugar maple, while the impregnation of yellow birch samples reached one around 200 g.m^− 2. X-ray densitometry confirmed an asymmetric density profile due to the monomer penetration concentrated in the first millimetres of the samples. Microtomography and Raman spectroscopy highlighted the penetration path of the monomers in the wood, mainly through the vessels. The lumens of the cells close to the surface were also filled with polymers. The phosphorus monomer surface impregnation positively impacted the thermal and fire properties of the modified wood. A 25% decrease in the peak of heat release rate was observed, and the residual mass was multiplied by two compared to the reference. The phosphorus monomer contributed to the char formation.

Wood pyrolysis is a complex process, and understanding its mechanism is challenging due to the interaction of multiple components. In this study, the pyrolysis kinetic properties of experimentally extracted wood components and wood pseudo components simulated via Fraser–Suzuki function deconvolution methods were analyzed. Additionally, the differences between the independent parallel reaction model (IPRM) and the deconvolution method were compared to investigate the pyrolysis characteristics of wood. The activation energy (E) and pre-exponential factor (A) were calculated using the Flynn-Wall-Ozawa (FWO) method. The results indicated that the average E for chemically extracted cellulose from Chinese fir was 165.4 kJ/mol and 157.1 kJ/mol for birch cellulose. The corresponding values for their pseudo-cellulose were 109.9 kJ/mol and 153.8 kJ/mol, respectively. Within the range of conversion rates less than 0.8, the pseudo components required a higher temperature to achieve the same conversion rate as the experimentally extracted components. The IPRM method accurately predicted the pyrolysis properties by combining holocellulose and lignin. However, its accuracy was low when combining cellulose, hemicellulose, and lignin, which was attributed to the interaction between in-situ components influencing wood pyrolysis.