Research Articles

Poplar wood (Populus deltoides), a fast-growing and abundant species, holds promise for sustainable material use, but its low density, poor dimensional stability, and weak strength restrict high-value applications. This study examined property enhancement through resin impregnation with phenol-formaldehyde (PF), melamine-urea-formaldehyde (MUF), and polyethylene glycol (PEG) at 5%, 10%, and 15% concentrations. Modified specimens were tested for weight percent gain, bulking, water absorption, dimensional swelling, modulus of rupture, modulus of elasticity (MOE), impact strength, and surface hardness, as well as machinability and carving performance using expert evaluation and Computer Numerical Control (CNC) surface quality. Given the laboratory-scale dimensions of the specimens, the resins achieved satisfactory penetration, as also reflected in the WPG values. The 15% PF treatment produced the greatest improvements, yielding a WPG of 26.3%, MOE above 10,000 MPa, and reduced surface roughness to 2.90 µm. Compared with untreated samples, PF-modified wood showed superior dimensional stability, machining resistance, and carving clarity, approaching the properties of hardwoods such as walnut and beech. MUF led to moderate benefits, whereas PEG mainly caused bulk increase without significant strength or moisture resistance improvements. Overall, PF impregnation effectively upgraded poplar wood, indicating its potential as a cost-effective alternative for decorative and structural applications.

The purpose of this study was to fit and compare semi-empirical thin-layer drying models and an artificial neural network (ANN) model to describe the drying kinetics of wood fiber in a near-infrared (NIR) dryer. The drying kinetics of wood fiber were evaluated using 18 semi-empirical models at three temperatures (105, 120, and 135 °C), utilizing a halogen moisture analyzer. The ANN model was designed with temperature and time as input factors and moisture content as the output variable. The findings revealed that the drying process was mainly controlled by a diffusion mechanism, and all the process occurred in two falling drying rate periods. The fitness of drying curves on semi-theoretical models based on statistical parameters, including RMSE, SSE, and R² showed that there was not much difference between equations with a maximum of two constant parameters and equations with more than two constant parameters. Therefore, using a simple model can help to reduce the time of the analysis and is beneficial to avoid using complex drying models. Also, the results showed that at higher drying temperatures (120 to 135 °C), both ANN and the best-performing semi-empirical models (Page and Henderson–Pabis) produced comparable accuracy, whereas at lower temperature (105 °C), ANN performed better due to its flexibility.

Cacalia firma is known for its unique fragrance, and its young shoots are traditionally used as culinary herbs and for their active constituents. The leaves of C. firma and the residual material remaining after enzymatic treatment exhibit both nutritional and therapeutic potentials. Despite this, the application of enzyme-treated C. firma leaf residues in functional food development has received limited attention. According to existing research, these residues are abundant in health-promoting compounds, such as antioxidants and polyphenols. Moreover, preliminary in vitro studies have suggested their potential to alleviate gut microbiota-modulatory problems. Expanding studies in this field could support the future use of enzyme-treated C. firma residues as valuable components in functional food formulations. This study aims to detail the bioactive profiles and nutraceutical potential of various enzyme-treated C. firma leaf residues and assess their applicability in health-oriented food products.

Using waste wood to prepare recycled wood fiber (RWF) and using it to enhance low-carbon cement-based materials can achieve the recycling utilization of waste resources, which meets the needs of green and sustainable development strategy. In this study, the performance of high-belite sulfoaluminate cement (HBSC) composites reinforced with recycled wood fibers (RWFs) derived from construction waste wood was investigated. The effects of RWF content and water-to-cement ratio on mechanical properties, hydration characteristics, thermal conductivity, and micro-structure were systematically evaluated. Increasing RWF content resulted in an initial increase followed by a decrease in the mechanical properties of HBSC-based materials. A 20% RWF incorporation simultaneously optimized flexural and compressive strength while mitigating crack propagation. The addition of RWF decreased the dry density of HBSC. Thermal conductivity exhibited a linear correlation with dry density and decreased with higher water-cement ratios. At 20% RWF content and a water-cement ratio of 0.45, the microstructure of the HBSC composite became denser (or more refined in pore structure), resulting in the optimal comprehensive performance.

Wild plant-associated rhizospheric microbiomes represent largely unexplored reservoirs of carbohydrate-active enzymes (CAZymes) that have significant biotechnological potential. This metagenomic investigation examined glycoside hydrolase (GH) family distribution within rhizospheric microbial assemblages of two native Saudi Arabian plants: Moringa oleifera and Abutilon fruticosum. High-throughput shotgun sequencing revealed pronounced plant species-specific CAZyme specialization. Moringa oleifera rhizospheres exhibited exclusive enrichment in five GH families (GH105, GH106, GH25, GH28, and GH38), while A. fruticosum supported three distinct families (GH17, GH32, and GH33). Taxonomic analysis revealed differential microbial composition: M. oleifera communities were dominated by Actinobacteria (Streptomyces, Micromonospora) with significant eukaryotic representation, whereas A. fruticosum microbiomes showed bacterial predominance, primarily Proteobacteria (Pseudomonas, Bradyrhizobium). CAZyme-encoding sequences frequently exceeded 120 per GH family, indicating extensive catalytic potential. These specialized enzymes offer multifaceted applications across pharmaceutical glycoprotein synthesis, lignocellulosic biomass degradation for biofuels, food preservation systems, and biomaterial fabrication for tissue regeneration. The rhizosphere-specific enrichment of highly specialized CAZyme consortia positions these microbial communities as scalable biocatalytic platforms, providing eco-sustainable alternatives to conventional industrial methodologies across pharmaceutical, energy, food, and environmental sectors.

Amid the rise of the experience economy, the integration of perceptual experiences into outdoor furniture evaluation was identified as a critical requirement. An integrated SD–AHP–GRA model, combining Semantic Differential (SD), Analytic Hierarchy Process (AHP), and Grey Relational Analysis (GRA), was employed. User emotional needs through semantic analysis were quantified, and the design elements were determined by expert assessments. The results showed that three core design dimensions, namely functionality, aesthetics, and interactive experience, were identified using the AHP method. Three design schemes were comparatively assessed using AHP–GRA, with Scheme B confirmed as optimal (weighted correlation: 0.873). The AHP–GRA composite model, which combines expert weights with grey relational analysis to reduce the subjectivity and uncertainty inherent in AHP weighting, highlighted excellence in high-weight attributes of outdoor furniture design, demonstrating its superiority in balancing multidimensional criteria. Overall, the SD–AHP–GRA method was validated as a means to resolve conflicts between subjective preferences and engineering constraints in outdoor furniture design.

This study investigated the fabrication of C/SiO₂ ceramics using kraft pulp fibers (KF) and phosphorylated kraft pulp fibers (PKF) impregnated with a ceramic precursor via a sol-gel route. The rheological behaviour coupled to infrared spectroscopy of the ceramic precursor was examined to optimize the drying process of the impregnated preforms. Thermo-gravimetric analysis and scanning electron microscopy were used to study the thermal behaviour and micro-structure of the ceramics. The PKF exhibited a superior thermal stability, and enhanced fiber/ceramic interactions compared to untreated KF. The impact of the fiber functionalization and of the pre-pyrolysis of PKF on fiber/ceramic interactions was also explored. The in-situ formation of carbon fibers during heat treatment from PKF appears to be a more effective approach for developing future environmentally sustainable ceramic matrix composites (CMCs).

The material properties of softwood species affect the safety of building structures, and wood identification is a key factor in material certification in specific institutions for green building certification. This study investigated an efficient wood species identification algorithm, aiming to provide a reliable method for material selection in construction and decoration industries. Using microscopic cross-sectional images of 36 softwood species applied in construction and decoration as research objects, 11 classic deep learning models were employed for species classification, combined with class activation map analysis to examine the key structural features for species identification. Specifically, the model structure and advantages of Swin Transformer were highlighted, in which hierarchical feature extraction and shifted window attention mechanism enable multi-scale fusion of wood structural features, such as tracheids, within global contexts, thereby improving classification accuracy for wood cross-sectional images. Experimental results showed that the Swin Transformer model achieved the highest classification accuracy of 99.97%, with both precision and recall exceeding 99% and an F1 score of 99%. These findings validate that deep learning networks based on the Transformer framework can achieve reliable image classification performance in wood research.

To address the issue of bending deformation in panel furniture shelves under prolonged loading, this study developed a 3D-printed shelf reinforcer using polyamide 6 (PA6) filament via fused filament fabrication (FFF) technology. Initially, the bending performance of PA6 models was analysed under varying process parameters (infill structure, infill thickness, and extrusion flow rate) using the three-point bending method. Subsequently, the reinforcer was custom designed and 3D-printed according to the target shelf’s actual dimensions. Experimental results indicated that, among the three infill structures, the honeycomb infill structure exhibited the best bending performance, followed by the grid infill structure, and the line infill structure performed the worst. As infill thickness and extrusion flow rate increased, the bending performance of PA6 models progressively improved. The shelf reinforcer, 3D-printed with a honeycomb infill structure, 1.2 mm infill thickness, and 12 mm³/s extrusion flow rate, exhibited superior surface quality and achieved a tight fit with the shelf. This reinforcer effectively enhanced the shelf’s bending performance and load-bearing capacity, extending the furniture’s service life and providing practical reference for the rapid development of similar household items.

The influence of hybrid matrix composition was investigated relative to the mechanical properties of composite materials reinforced with poultry feathers and recovered paper. The matrix composition was modified by varying the proportion of natural dammar resin. The reinforcement remained the same across all formulations and was maintained at a constant 60% by weight in the composite, regardless of the matrix type. The materials were tested under tensile, compressive, and flexural loading, as well as for Shore D hardness and mechanical vibration behavior. It was found that increasing the dammar content enhanced the ductility of the material while reducing its fracture strength, regardless of the destructive testing method applied. In terms of hardness, a decrease was observed with higher dammar content. Additionally, in vibration analysis, an increase in the damping factor and a decrease in the natural frequency were noted as the dammar proportion increased. All these findings were statistically validated using a one-way ANOVA test.