Wood Science and Technology最新文献

This study proposed a linear model between internal bond strength and compressive elastic modulus based on Griffith’s fracture theory. The local compressive elastic modulus was determined by non-destructively detecting the inherent frequency of material vibration using a method based on rod longitudinal vibration theory. In the experiment, the inherent vibration frequencies of 10 types of medium-density fiberboard (MDF) were measured through excitation and vibration of piezoelectric ceramics based on longitudinal wave vibration theory. Then, the compressive elastic modulus of each board was calculated. The calculated compressive elastic modulus of MDF and the measured internal bond strength values were fitted into a linear regression model. A high linear correlation between them (r² = 0.972) was found, having a mean square error of (2.6times {10}^{-5}). In addition, the average error between the model prediction value and the measured value was 0.014 MPa, having an average relative error of 1.49%. The maximum error was 0.044 MPa with a maximum relative error of 5.06%, indicating that the developed model was highly consistent with reality and had very small deviations. The results indicated that this proposed method can be used to accurately estimate the internal bond strength by non-destructively detecting the compressive elastic modulus of MDF.

In this study, we have implemented the first lattice model that incorporates progressive material damage, taking into account ductile failure under compression and brittle failure under tension. The model also considers fracture energy within the constitutive model by incorporating progressive material degradation, where damage variables depend on the fracture energy of the material. In addition, the lattice fracture criterion includes a typical failure criterion for wood and assumes a coefficient of variation in elastic constants and strengths to account for the heterogeneity of wood. The lattice model relies on axial springs, with their mechanical properties explicitly calculated based on the wood’s macroscopic mechanical properties. The model’s capability is evidenced by simulating two fracture tests and comparing the results with previously presented numerical and experimental data. The observed results align well with experimental observations.

The paper production industry annually produces approximately 50 million tons of lignin, an intermediate product. While lignin has the potential for producing valuable chemicals and energy materials, an effective method for its conversion is yet to be developed. This study aims to establish a sustainable and environmentally friendly approach for electrochemically synthesizing valuable compounds from lignin with using natural deep eutectic solvents as electrolytes. The study used cyclic voltammetry (CV) for the electrochemical depolymerization of Kraft lignin, examining the effects of different scan numbers on depolymerization and the resulting lignin derivatives. Observed changes in the depolymerization peak current of lignin were reported as the number of scans increased. Choline chloride: Lactic acid (CC:LA), Choline chloride: Ethylene glycol (CC:EG), and Lactic acid:1,2-propanediol (LA:PR) were used as green electrolytes. Syringaldehyde was found to be the major compound obtained by this method. As a result of statistical analysis performed using The Grey Relations Analysis method, it was determined that the conditions that utilized Kraft lignin with the highest added value involved performing five cycles of CV scans with the CC:LA electrolyte. CV scans in DES environments increased the yield of lignin-derived phenolic compounds.

Water has different forms of existence in wood (free water and bound water), which can generate different effects on the microstructure of wood. Compared to other methods, the freeze-thawing method is equipped with simple, environmentally friendly, and low-cost features. In this paper, the permeability of wood with different ratios of free water to bound water (water content), as well as the pore structure characteristics and electrochemical properties after carbonization, were investigated by the freeze–thaw method. The results show that dry samples of poplar chips with a moisture content of 15–17% after KMnO₄ and freeze–thaw cycle treatment and carbonization (PC@15%-MnO) have a specific surface area of 936.94 m²/g. The areal specific capacitance is 4784 mF/cm² at a current density of 12 mA/cm², which is 3.3 and 22 times higher than those of wood-derived carbon without freeze–thaw treatment, respectively. Additionally, PC@15%-MnO maintains 80% of its specific capacitance after 2000 testing cycles, indicating that the freeze–thaw method effectively enhances the permeability, pore structure, and electrochemical properties of wood-derived carbon materials. This strategy offers new avenues for the research and application of wood in electrode materials.

Bamboo is one of the most rapidly growing plants with a highly sophisticated root and rhizome system in its culm base, where conducting tissue plays a key role in water and nutrient absorption and transportation. However, our knowledge of the three-dimensional structure of the conducting tissue is incomplete due to the opacity of the bamboo. In this paper, the spatial relationships of the conducting tissues among the main stem, root and rhizome of the culm base are explored. The culm base of a Chimonobambusa tumidissinoda was used for the analysis and high-resolution X-ray microtomography (μCT) was employed. A deep learning algorithm was used to segment the conducting tissue from the culm base. 3D model reconstruction and semi-quantitative characterization of the conducting tissue were realized. It was found that the anatomical characteristics among the main stem, root and rhizome are different, but the conducting tissues in these structures are interconnected in different ways. The transverse conducting tissue mainly originated from the rhizome rather than the root, and its thickness gradually decreased from the bottom of culm base to its top, contrary to the structure of the axial conducting tissue. The results indicate that μCT combined with deep learning segmentation effectively visualizes complex conducting tissue structures, volume filtering enhances detailed observation of network structures within conducting tissues, which provides new insights into the bamboo’s culm base structure and evidence of the sophisticated and interconnected fluid motion pathways among the different tissues of the culm base.

Steaming of green timber, a common industrial process for various hardwood species, significantly influences wood properties, including coloration and drying characteristics. However, the environmental implications of substantial volumes of condensate generated during wood steaming underscore the urgency for its sustainable management. This study explores the chemical composition of the condensate obtained during the 90-hour indirect steaming of walnut timber (WTSC), aiming to identify potential applications for this wastewater while addressing environmental risks. Chemical characterization of WTSC included qualitative LC-MS/MS analysis, determination of the total phenolic content (TPC), total flavonoid content (TFC) and the content of selected phenolics. WTSC exhibited high TPC (188 mg gallic acid equivalents per L) and TFC (9.74 mg quercetin equivalents per L) values. Additionally, WTSC showed significant antioxidant activity (IC₅₀ (DPPH) = 61.4 µg/mL and 103 µg ascorbic acid equivalents per mL in FRAP assay). Specific phenolic compounds detected in the WTSC distinguish it from other wood industry effluents and are a consequence of the unique characteristics of walnut wood and conditions during steaming process. A variety of acids (p-hydroxybenzoic, protocatechuic, syringic, gallic, cinnamic, cinnamic, p-coumaric, o-coumaric, vanillic) and flavonoids (apigenin, genistein, naringenin, luteolin, kaempferol, chrysoeriol, isorhamnetin, apigenin 7-O-glucoside, vitexin, kaempferol 3-O-glucoside, catechin, epicatechin, and quercitrin) were identified and quantified. The condensate exhibited higher TPC value and antioxidant activity than other wood industry effluents, positioning it as a promising natural antioxidant with potential applications in pharmaceutical and food industries. However, our short-term goal is to explore the potential use of WTSC as received – without isolating individual compounds – in studies focused on plant protection, textile dyeing, and wood-based panel production.

The article investigates the charring and the char front temperature of beech, the most widespread hardwood species in Central Europe. The current Eurocode standard EN 1995-1-2 specifies the char front temperature to be 300 (^{circ })C, albeit this determination primarily applies to softwood species. Consequently, this article aims to examine whether this assumption applies to beech. Through advanced experimental analysis and numerical modelling, it was determined that the char front temperature for beech exceeds 300 (^{circ })C. This finding represents crucial information for the correct validation of fire-resistant design for structural elements made of beech. Moreover, it lays the groundwork for improving simplified methods of fire design, particularly for a more accurate determination of the charring depth.

Predicting the influence of structural parameters on wood elasticity is useful for engineering application, however due to the complex imbrication of several scales it is important to know which features need to be taken into account. The aim of this work is to investigate the influence on wood stiffness of waviness and interconnection of cellulosic fibrils, an observed feature usually overlooked in micromechanical models. For that, a multi-scale model estimating the macroscopic behavior of wood is developed. This model integrates three different scales of wood structure: that of the cell wall, that of the cellular tissue and that of the growth ring. It relies on both numerical and analytical homogenization procedures to determine their effective behavior by defining at each scale a periodic representative volume element. Using this multi-scale model, it is shown that the influence of the oscillations and interconnections of the fibrils is significant for certain moduli at the macroscopic level (ring scale), such as the macroscopic shear moduli, while it can be neglected for others. Furthermore, although the effect of fibril crosslinks is quite strong for certain components of elastic behavior at the cell wall level, it loses its importance at the macroscopic level, especially for low-density wood. This trend can be explained by the anti-symmetric tilt of fibrils in adjacent cell walls. On the other hand, for denser woods where the interactions between adjacent cell walls are less dominant, or in the case of softened wood, the effect of fibril oscillations remains important.

A new technique based on machine learning algorithms was introduced to detect internal wood defects. This technique relies on analyzing segmented propagation rays of stress waves and successfully generates the tomographic images of the defects by using the stress wave velocity. Utilizing a dual-stage methodology, the initial phase involves ray segmentation for the precise delineation of stress wave propagation, while the subsequent stage integrates advanced classification and clustering algorithms to facilitate the generation of tomographic images. This approach effectively tackles the inherent challenges associated with accurate segmentation and classification of stress wave velocity rays. The effectiveness of the proposed method was evaluated using both synthetic and experimental data. The results showed that the proposed method, when compared with some state-of-the-art methods, has a superior ability to accurately detect defective regions in the wood. The success of the proposed method is evaluated with four different evaluation metrics. It determined that over 90% success is achieved for all metrics. In comparison with related studies, it determined that the results are improved by 7–22% compared to the literature.

In this study, the rheological Burger model combining Maxwell and Voigt–Kelvin model units as well as modified mechanical models were employed to analyze the shear creep mechanism of wood. Off-axis compression tests were conducted on Japanese Hinoki cypress specimens (Chamaecyparis obtusa), and a mechanical analysis of the shear creep mechanism was performed. First, the measured creep compliance curves [J_TL(t)] were fitted using this Burger model, which is a typical model used to explain the creep behavior of wood. Furthermore, three modified Burger models with non-Newtonian dashpots were proposed to explain the measured data more accurately: model 1—only the dashpot in the permanent strain unit is non-Newtonian; model 2—both dashpots are non-Newtonian; and model 3—only the dashpot in the delayed elastic strain unit is non-Newtonian. The mean value of the coefficient of determination was highest for model 1. The number of specimens that could be fitted with a tolerance error of 0.1% was 43 out of 50 with the Burger model, 45 with model 1, 25 with model 2, and 45 with model 3. The Burger model exhibited large discrepancies between the theoretical and measured values, model 2 could not be used to explain several specimens, and model 3 exhibited a delayed elastic strain behavior that was inconsistent with the definition. Therefore, we conclude that model 1 is the most appropriate for studying the shear creep behavior of wood.