Wood Science and Technology最新文献

The nitration reaction makes it possible to depolymerize the structures of condensed lignin to produce valuable chemical products. The physicochemical properties data of lignin nitro derivatives are necessary for their use. The nitrolignins were obtained on the basis of a slightly altered sample of dioxane lignin extracted from spruce wood. Water and ethanol solutions of nitric acid were used as nitrating agents. Changes in the elemental and functional composition, macromolecular, acid-base, redox, and electrophysical properties of lignin were determined by a complex of analytical methods. Characteristic changes in the conductive and dielectric properties of nitrolignins in the range of lower and medium frequencies of the electric field from 10^− 2 to 10³ Hz have been established. The interrelation of the functional nature and physicochemical properties of lignin was shown.

Most Japanese cedar heartwood is reddish in color, but some of the wood is blackened. This phenomenon is related to the high potassium concentration, weak alkalinity, and denaturation of norlignans. Owing to its dark color and high moisture content, blackened wood has a low timber price. In this study, binderless boards were produced from black heartwood, and the mechanical performance and water resistance were compared to those of normal (red) heartwood. The changes in the main wood components and extractives caused by heat and pressing were also analyzed. The results showed that the mechanical performance and water resistance of black heartwood boards were higher than those of red heartwood boards. The optimal production conditions were 220 °C for 20 min for red and black heartwood, or 240 °C for 10 min for black heartwood. Norlignan analysis revealed that more sequirin-C was lost during the hot- pressing of black heartwood. In the infrared spectra, a peak around 1717 cm^–1 appeared only after the black heartwood samples were hot-pressed. These results indicate that the hydroxy group–rich sequirin-C may have formed new ester bonds with the carboxyl group of hemicellulose during hot-pressing, thereby increasing the internal bonding strength.

Gnetum gnemon (Gnetales) is a woody gymnosperm exhibiting morphological characteristics similar to those of woody angiosperms. This study investigated the mechanism underlying negative gravitropism observed in the inclined stems of G. gnemon at two plantation sites on Java Island, Indonesia. The following results were obtained: On the upper side of the inclined stem of G. gnemon, (1) eccentric growth occurred in both the xylem and the phloem; (2) significant tensile growth stresses were generated on the surfaces of the xylem and the inner phloem; and (3) a small microfibril angle (MFA) along with high cellulose crystallinity were observed in both the xylem and the inner phloem. Furthermore, (4) G-fibers developed predominantly on the upper side of the inclined stem, especially in the inner phloem, while no G-fibers were detected in the xylem. From these results, it can be concluded that reaction wood with a small microfibril angle (MFA) and high cellulose crystallinity in the lignified secondary-wall of the xylem fiber, along with reaction phloem containing G-fiber, generate significant tensile growth stresses on the upper side of the inclined stem of G. gnemon. In other words, although G. gnemon is a gymnosperm, it exhibits negative gravitropism through a mechanism not typical of normal gymnosperms but rather similar to that observed in angiosperms.

Wood exposed to outdoor environments undergoes cyclical photodegradation and biological decay. This study investigated the alternating effects of accelerated ultraviolet (UV) weathering and brown-rot decay (Gloeophyllum trabeum) on southern pine (Pinus spp.) wood over two exposure cycles, focusing on the morphological, mass loss, porosity, wettability, chemical changes. Results showed that preceding photodegradation significantly impacted subsequent brown-rot degradation, transitioning from acceleration to inhibition in both cycles. This transition occurred earlier in the second cycle, linked to photodegradation-induced structural and chemical changes. Photodegradation increased wood porosity (61.1% in total pore volume, 27.5% in average pore size) and improved the surface wettability, providing fungal invasion pathways and moisture conducive for fungal growth. However, extended weathering accumulated antifungal lignin-derived compounds (e.g., quinones, phenols, aldehydes), inhibiting biodeterioration. Understandings this interaction aids in developing efficient protection strategies for outdoor wood products.

Wood, a renewable and eco-friendly resource, holds significant potential for developing sustainable structural materials. Nevertheless, in advanced engineering applications, natural wood often fails to meet requirements for mechanical performance and flame retardancy. Herein, we present a novel, simple yet highly effective strategy to fabricate tough flame-retardant wood (TF-wood). This approach involves partial delignification using alcohol-amine-based deep eutectic solvents (DESs), followed by N/P-functionalization of the dissolved lignin that is reincorporated into the wood matrix with subsequent hot-pressing. With the incorporation of 20% functionalized lignin, the resulting TF-wood demonstrates a remarkable increase in tensile strength (425.2 MPa), strain (2.9%), and the corresponding toughness reaching 8.1 MJ/m³, 27 times higher than that of natural wood. Additionally, the peak heat release rate (pHRR) of the TF-wood is reduced by 58.3%, and the total heat release (THR) is decreased by 47.8%. Crucially, TF-wood exhibits an ultralow water migration rate, further enhancing its structural stability in humid environments. These combined properties render TF-wood highly attractive for structural applications requiring enhanced fire safety and durability. This study paves the way for designing sustainable, high-performance building materials that integrate multiple functionalities.

Traditional construction is slow, labor-intensive and wasteful. Additive manufacturing (AM) enables faster, automated and efficient buildings with less waste and more design flexibility. This study looked at the possible applications of a biobased novolac (pyrolysis oil / phenol-formaldehyde) resin and hexamethylenetetramine (HMTA) hardener with either 40 mesh and 100 mesh wood fiber (30%), and extrusion of wood composites. Wood pyrolysis oil was partially substituted (50%) for phenol in the novolac resin preparation to increase its biobased content. The materials were characterized by a combination of thermal analysis, rheology, mechanical, and water absorption properties. The flow characteristics of the uncured resin and composites were determined by dynamic rheometry. The curing behavior of the resin and composites was determined by differential scanning calorimetry (DSC). The presence of wood decreased the curing enthalpies and increased the curing peak temperature. The wood resin composite blends displayed good pseudoplastic behavior. Composites made with smaller wood particles showed more thermal stability and lower glass transition temperature (T_g) because of the increased interaction between the fiber and the resin matrix. Extrusion experiments on the wood resin composites successfully produced a continuous rod. The extruded wood resin composite rods were cured (150℃ for 5 min) and showed good flexural properties. The successful extrusion of biobased novolac with wood demonstrates its potential for AM, making it a promising sustainable alternative for construction applications.

Automating wood identification through computer vision offers improved objectivity, time-efficiency, and accuracy over traditional methods. Conventional wood anatomical assessments rely on intact mature tissue, avoiding damage (cracks, fungi deterioration, insect damage) and other anomalies (pith, bark, traumatic canals). The impact of using images from anomalous surfaces on automated identification remains underexplored in current research. This study evaluates the performance of convolutional neural networks (CNNs) for classifying the presence of anomalies on images, and studies the impact of anomalies on genus identification by in- or excluding images of anomalous surfaces in the training data and assessing recall on the test data. The Xception network architecture was used to train the two types of classification models, on macroscopic cross-sectional images of 26 Congolese wood genera. The first model was trained for binary classification on the presence or absence of anomalies on > 250.000 images of ~ 1000 Congolese tree species, demonstrating accuracy, precision, recall and f1-score of ~ 93% on 25.000 test images. This shows that CNNs can learn patterns to detect the presence of anomalies. The second model was trained and evaluated on a subset of those Congolese tree species, consisting of 26 timber genera with abundant different types of anomalies (cracks, fungi deterioration, insect damage, pith, bark, traumatic canals). Three different wood identification models were trained and evaluated on the images featuring a model trained only on all images (regardless of anomalies), a second model trained only on perfect (anomaly-free) images, and a third model trained only on images with anomalies. The three models were evaluated on different specimens and demonstrated macro-averaged recall scores of 88.4, 90.5%, and 79.1% for the respective models, showing that a model trained on images from intact end-grain wood/anomaly-free images performed best. Class (genus) specific recall scores demonstrated for the three models that model performance varies between genera. The class (genus) specific recall scores of Millettia, Tessmannia, Celtis, Afzelia, Beilschmiedia, and Vitex are highest for the model trained on all images (with and without anomalies). Conversely, the recall scores of Cynometra and Microcos were lower for this model. GradCAM analysis was performed to visualize which regions on images were more activated for classification (wood identification), and revealed that the model focuses more on anomaly-free regions for wood identification, underscoring the importance of clear wood anatomy in training CNNs for wood identification.

The increasing emphasis on sustainable biorefinery processes has brought black liquor, a complex byproduct of pulp mills, to the fore as a pivotal source for extracting valuable organic compounds, particularly lignin. The chemical composition of black liquor exhibits significant variations depending on the lignocellulosic source, the pulping method, and the conditions during processing. By examining pH adjustments and analytical methods such as HPLC and GC-MS, this study provides insights into the chemical behavior of black liquor and proposes strategies for its efficient characterization and utilization. The presence of different acids (H₂SO₄, HCl, and H₃PO₄) and pH adjustments (2, 5.5, 7, 9) in black liquor significantly influence its physical properties, such as density and viscosity, as well as its chemical composition. Softwood black liquor showed greater viscosity changes due to pH levels, while hardwood black liquor was primarily affected by the type of acid used. Syringyl-type compounds dominate in hardwood black liquor, whereas softwood black liquor is richer in guaiacyl-type compounds such as vanillin and catechol. HPLC analyses revealed higher phenolic yields at higher pH levels (7–9), with vanillin and protocatechuic acid being most abundant in softwood samples and syringaldehyde and syringic acid in hardwood samples. The optimal pH for extracting lignin-derived phenolics is 5.5–7, while pH 2 is preferred for extracting organic acids, highlighting the critical role of pH in maximizing extraction efficiency.

Addressing the issue that thick bamboo slices (≥ 1 mm) exhibit high bending stiffness and cause premature cutting-tip splitting, resulting in poor surface quality. This study investigated the effects of saturated steam treatment on the surface quality and mechanical properties of the bamboo during slicing process, and analyzed physicochemical mechanisms through XRD, FTIR, and SEM test. The results show that chemical functional groups, microstructure, and relative crystallinity of bamboo were changed, glass transition temperature and bending stiffness was reduced, and Mode I fracture toughness was enhanced, so that saturated steam treatment mitigates the degree of premature splitting during slicing and significantly improves surface quality. Under optimal softening conditions (160 °C/10 min), saturated steam treatment reduced sliced surface roughness by 37.98%, and lowered glass transition temperature by 19.67%, flexural strength and elastic modulus decreased by 59.66% and 42.88%, respectively, while Mode I critical displacement increased by 113.08% and ({G_{IC}})increased by 179.08%. Studying bamboo surface roughness, chemical, and mechanical properties are expected to lay a foundation for bamboo slicing, mechanics research, and slicing cracking.

Douglas-fir (Pseudotsuga menziesii) is the principal species for lumber production in the Pacific northwest and has been the subject of ongoing tree improvement and silvicultural research aimed at enhancing growth. With industry shifting to lower planting densities, it is critical that we improve our knowledge of the wood quality implications of these practices. Hyperspectral imaging (HSI) presents a promising tool for studying within-tree variation of wood properties and it was utilized to provide data for the development of maps illustrating within-tree variation of physicomechanical, tracheid and chemical properties of 25-year-old Douglas-fir grown at different spacings (narrow, conventional and wide). Property maps showed that the different spacings had similar patterns with a more abrupt change in wood properties radially in narrowly spaced trees compared to those widely spaced, regardless of the property assessed. Radial variation patterns showed increases from pith to bark in density, stiffness, tracheid length and width, and glucose/cellulose content, while microfibril angle, lignin, and xylose decreased. Although planting density may not determine absolute wood quality traits, it can influence their developmental patterns across the stem.