2e:T4c2,

This study focuses on xanthated cellulose fiber (XCF), a precursor of cellulose nanofiber (CNF), innovatively integrates orthogonal experiments, two-factor analysis of variance, stepwise regression, and particle swarm optimization to systematically analyze and precisely control its degree of substitution (DS). Based on a three-level four-factor orthogonal design and supplementary tests, a quadratic nonlinear regression model with R² = 0.9214 was established using 29 datasets, confirming the model’s significance. Carbon disulfide (CS₂) dosage was identified as the most influential factor, and all six interaction terms were statistically significant. The optimal process parameters obtained via particle swarm optimization were: NaOH concentration 7.47%, alkali treatment time 4.38 h, CS₂ dosage 0.53 mL, and xanthation time 2.74 h. A verification experiment under these conditions yielded a DS of 0.972, with only a 2.8% deviation from the predicted value. This study provides a precise and controllable pretreatment strategy for the efficient and low-energy preparation of CNF, demonstrating significant potential for industrial application.

2f:T52a,

Natural fiber-reinforced composites (NFRCs) are increasingly used in industries like automotive and aerospace due to their eco-friendliness and lightweight properties. However, drilling NFRCs poses challenges such as delamination, poor circularity, and cylindricity, which compromise structural integrity. This study addresses these issues by optimizing drilling parameters (spindle speed, feed rate, and drill material) using a hybrid multi-criteria decision-making (MCDM) approach. The preference selection index (PSI) and technique for order preference by similarity to ideal solution (TOPSIS) methods were employed to balance conflicting objectives (minimizing delamination while improving circularity and cylindricity), with ANOVA validating the significance of parameters. Results identified the optimal combination as HSS SUPER drill, 560 rpm spindle speed, and 40 mm/min feed rate, achieving minimal delamination and superior geometric accuracy. The study demonstrates that feed rate is the most statistically significant factor (p < 0.05), while PSI and TOPSIS rankings showed strong agreement, reinforcing the robustness of the methodology. This work provides a practical framework for multi-objective optimization in composite machining, enhancing both quality and efficiency.

30:T5fd,