Volume 20 Issue 4

Bamboo, despite its environmental advantages, often suffers from poor coating adhesion because of its natural surface characteristics, thereby limiting its application as an exterior material. This study aimed to improve the performance of coatings applied to moso bamboo (Phyllostachys edulis) by introducing surface sanding as a pretreatment. Sanding was performed using #100 sandpaper with stroke counts of 10, 20, 30, and 40; the resulting changes in the epidermal and fibrous layers and their influence on the coating adhesion were evaluated. The 40-stroke treatment exposed the fibrous layer and enhanced the surface wettability. According to the ISO 2409 (2020) cross-cut test, the sanded specimens exhibited excellent adhesion (Grade 1), in contrast to untreated specimens, for which coating delamination was evident. Furthermore, under accelerated-aging tests, coating adhesion was maintained for the sanded samples, whereas pronounced delamination was observed for the untreated samples. These findings demonstrated the effectiveness of surface sanding. In conclusion, surface pretreatment is essential for improving the durability and coating quality of moso bamboo, and the results of this study can serve as fundamental data for the practical application and broader utilization of bamboo materials.

Microfibrillated cellulose (MFC) is a promising bio-based material owing to its excellent mechanical, optical, and barrier properties. However, its inherent hydrophilicity limits its applicability in moisture-sensitive environments. In this study, the surface hydrophobicity of MFC films was enhanced by incorporating an alkyl ketene dimer (AKD) and thermal curing. MFC was prepared from hardwood bleached kraft pulp via high-pressure homogenization to fabricate AKD-modified MFC films using vacuum filtration. The water contact angles of the AKD-modified MFC films were measured after thermal curing to determine the optimum manufacturing conditions for MFC film hydrophobicity. The presence of the AKD in the MFC matrix was confirmed by the appearance of alkyl chain C–H stretching bands in the Fourier transform infrared spectroscopy spectra. The water contact angle measurements showed that the addition of AKD alone improved the hydrophobicity but did not yield contact angles greater than 90°. However, with subsequent thermal curing at 105 °C, the contact angles increased significantly, reaching 104° under optimal conditions. The highest hydrophilicities were achieved with 2% AKD and 30 min curing and with 3% AKD and 10 min curing. These findings demonstrated that thermal curing was essential for activating the hydrophobic potential of AKD and achieving uniform, water-repellent MFC films.

The organosolv method, using water and n-butanol with acid catalysts, separates biomass into three phases: n-butanol, aqueous, and solid, which primarily contain lignin, hemicellulose, and cellulose, respectively. In this study, maleic acid was applied as a catalyst in the water/n-butanol method to avoid using inorganic acids. Comparable or better component separation was achieved relative to using sulfuric acid as a catalyst. Furthermore, by using a high concentration of maleic acid, instead of a catalytic amount, lignin was extracted from softwood with a high yield (more than 97 wt.% lignin extracted) under the condition at 180 °C for 1 hour with approximately 10 wt% maleic acid. Additionally, the reaction temperature and time were varied to achieve better lignin fractionation and functionalization. The highest total fractionation extent and well-carboxylated lignin were obtained at 150 °C. The chemical properties of lignin were also analyzed, and their structure and molecular weight were investigated.

To expand the potential of cork composite wood flooring as an interior material, this study investigated the bending performance of sandwich-structured cork composite wood flooring. The cork composite wood flooring was composed of temperate and tropical wood species as face layer and a cork board reinforced with metal, glass fiber, or carbon fiber placed between two cork boards as the core layer. The MOE value of wood flooring with merbau (M) had the highest value (6.71 GPa) and that of larch (La) had the lowest value (5.40 GPa). Overall, the MOE value of wood flooring with tropical wood species had higher value than those with temperate wood species, which had lower densities. According to the core reinforcements, the CM (cork board-metal) type showed a higher MOE value than the CG (cork board-glass fiber) and CC (cork board-carbon fiber) types. However, within the specific MOE, the order was CG > CC > CM. The ratio measured to calculated MOE ranged from 1.0 to 1.1, it showed a similar or slightly higher value than the measured MOE. The MOR of wood flooring had the highest value (51.0 MPa) in that with teak (T) and had the lowest value (34.9 MPa) in that with larch (La). The specific MOR of the wood floorings with cork board reinforced with glass fiber and carbon fiber was 20 to 40% higher than those reinforced with metal. Stable fracture behavior was observed for the cork composite wood flooring reinforced with metal, glass fiber, or carbon fiber.

Hollow glued bamboo scrimber (HGBS) columns constructed from bamboo scrimber plates were proposed as structural load-bearing components instead of traditional solid bamboo columns to enhance the stable load of columns without increasing material consumption. To analyze the mechanical behavior of HGBS columns, tests were first conducted on the elastic modulus and compressive strength of bamboo scrimber made from Neosinocalamus affinis to theoretically assess the material’s mechanical properties. A total number of 22 HGBS square cross-section with dimensions of  100 mm columns, varying slenderness ratios and hollow ratios, were fabricated with glued and nailed connections. These columns were subjected to axial compression tests to evaluate their failure modes, axial stiffness, bearing capacity, and ductility. Theoretical calculation models were developed for the HGBS columns to estimate load-bearing capacity. This research provides a comprehensive understanding of HGBS columns and broadens their potential applications in structural engineering.

The phin is a lute that originated in Thailand’s Isan region. The strings 1, 2, and 3 for the phin is E4, A3, and E3. It was tuned to the key of G major.  The strings 1, 2, and 3 running notes are E4, F4, F4#, G4, A4, B4, C5, D5, E5, F5, G5, A5, B5, C6, D6, and E6; A3, A3#, B3, C4, D4, E4, F4, G4, A4, A4#, C5, D5, E5, F5, G5, and A5; and E3, F3, F3#, G3, A3, B3, C4, D4, E4, F4, G4, A4, B4, C5, and D5, respectively. The keys F4#, B3, and F3# appear in the first octave only from strings 1, 2, and 3, respectively. In this study, the sound was analyzed with a PicoScope oscilloscope and Adobe Audition. The equation for the polynomial (i.e., the fret number versus the partial frequency) for open strings 1, 2, and 3 is y_string1 = 3.14x² + 9.10x + 316.07, y_string2 = 2.15x² + 5.51x + 214.55, and y_string3 = 1.51x² + 6.53x + 146.24. The changes in frequency (the multiplication factor of the x²) increased gradually with the pitch. Strings 3 (E3), 2 (A3), and 1 (E4) showed the multiplication factor of 1.51, 2.15, and 3.14.

To explore the effects of support stiffness and grinding media shape on the superfine grinding performance of wheat bran, a vibration grinding platform with adjustable support stiffness (25 to 55 kN/m) was used for tests with stainless steel spherical grinding media (SGM) and cylindrical grinding media (CGM), respectively. The results showed that both factors significantly affected the grinding effect. When stiffness exceeded 35 kN/m, micro powder quality and yield improved for both media. Below 35 kN/m, SGM’s micro powder quality deteriorated, while CGM’s micro powder quality peaked at 30 kN/m. At 30 kN/m, fine powder, micro powder, and superfine powder yields reached their maximum for both media. The mass fraction of superfine powder was 52.9% for CGM, and that of SGM was 29.3% higher than at 35 kN/m. SGM consistently produced better particle size distribution than CGM, with the smallest median particle size (D₅₀) difference (21.5%) at 30 kN/m. The superfine yield of CGM was not always higher than that of SGM. Their mass fraction difference showed a quadratic nonlinear relationship. A coupling effect between media shape and stiffness was found to determine grinding performance. Overall, this work provides a basis for optimizing the superfine grinding performance of wheat bran in vibration mills.

The aim of this work was to assess the suitability of selected methods of surface treatment on X48CrMoV8-1-1 tool steel for application on chipping knives in wood-chipping machines. Three material surface conditions of X48CrMoV8-1-1 tool steel were evaluated for their tribological scratching behavior. The first surface condition was related to the conventionally machined chipping knife from the manufacturer without surface treatment. The second condition involved plasma nitriding treatment, and the third was a PVD-coated surface with “CROSAL ® Plus” (AlCrN based) coating. Several complementary analyses were carried out, namely microstructural observations, nano-indentation measurements, and tribological scratch tests. From the scratch tests, friction coefficients depending on applied load were determined. The best nano-indentation results were obtained for the PVD-coated surface, namely 23.7 ± 1.6 GPa for nanohardness and 270.3 ± 19.0 GPa for elasticity modulus. The best results of tribological and scratching behavior were obtained for the plasma-nitrided surface, namely 0.34 ± 0.21 for coefficient of friction and 1.88 ´ 10^-6 mm³/N.m for specific wear rate. Based on the obtained results of laboratory tests, it can be concluded that the plasma-nitrided surface of X48CrMoV8-1-1 tool steel can ensure its better tribological performance compared to other investigated material conditions.

Video Abstract

The togunggak is a traditional musical instrument made of bamboo. This work observed the unique sound characteristics to define the notes using Fast Fourier Transform (FFT) via a picoscope. The sound characteristics are represented by the dominant frequency with the corresponding intensity. The note of the biggest (tog. 6) to the smallest (tog. 1) bamboo tube is recorded as from G3 to G4. This work reveals that tog. 2 to tog. 5 for togunggak A produce the notes E4, D4, B3, and A3, which is not similar to togunggak B, i.e., E4, D4, C4, Bb3. All bamboo tubes produced fundamental frequency with the presence of two lower partials at 100 Hz and 200 Hz and weaker overtones (except tog. 6)  in their frequency spectrum. Using symbol S for semitone dan T for tone (i.e. 2 semitone), the note interval of the tog. 6 to tog. 1 can be presented as TT2TT2T i.e., the G3, A3, B3, D4, E4, G4 note interval are presented by G3-A3 as T, A3-B3 as T, B3-D4 as 2T, D4-E4 as T and E4-G4 as 2T. The time frequency analysis (TFA) displays all the spectrograms with distinct prominent fundamental frequency peak.

The rapid growth of e-commerce platforms presents unique opportunities to analyze consumer behavior and predict product preferences in the furniture industry. This study explores the use of machine learning techniques to predict consumer choices for furniture products based on favorite listing data from e-commerce platforms. A dataset of 239 furniture products was collected, categorized into three groups: most preferred, moderately preferred, and least preferred. Key attributes, including furniture type, dimensions (width, depth, height), color, material, and price, were analyzed. Machine learning models, specifically Decision Trees and Random Forests, were applied to develop prediction models for these categories. The models were assessed using metrics such as accuracy, precision, sensitivity, and F1-score. Results indicated that the Random Forest model outperformed the Decision Tree, achieving 83% accuracy in predicting preference categories. Feature importance analysis highlighted that price and physical dimensions were the most significant factors influencing consumer preferences. These findings suggest that practical and economic aspects are prioritized over aesthetic features when choosing furniture. The study demonstrates the potential of machine learning in predicting consumer behavior, offering valuable insights for manufacturers and retailers in optimizing product development, inventory management, and marketing strategies.