PAPER making! g! FROM THE PUBLISHERS OF PAPER TECHNOLOGY INTERNATIONAL ® Volume 12, Number 1, 2026
fiber drainage performance while improving water retention capacity. Paper tensile strength decreases from 80MPa to 28MPa with lower hemicellulose content, while tear strength shows an initial stability followed by an increase (647mN to 968mN). Break resistance initially increases from 601kPa to 654kPa but then declines to 243kPa, indicating an optimal hemicellulose level for maximum performance. Furthermore, cationic starch demonstrates a pronounced compensatory effect on paper with reduced hemicellulose content, particularly in enhancing elongation at break and partially offsetting strength losses. For instance, the tensile strength of the material decreased from 72MPa to 25MPa (a 65% reduction) after hemicellulose removal, and the subsequent addition of 6% cationic starch restored the strength to 41MPa (a compensation rate of 22%). However, it exhibits inherent limitations in completely replacing the strength and burst resistance performance. These findings highlight the importance of hemicellulose in papermaking and provide insights into optimizing paper properties through hemicellulose content control and additive application. “Global optimization of multiply enzyme synergic treatment in the pulp and paper industry through machine learning methodology”, Manli Yang, Hui Zhao, Chenyang Zhang, Shipeng Gao, Haorui Wang, Xianghong Guan, Shuangyan Han, Journal of Cleaner Production , Vol.519, 10 Aug. 2025, 146013. Enzymes offer an eco-friendly alternative to chemicals in the pulp and paper industry, but their activity, especially when multiple enzymes work together, is highly affected by papermaking variables, which poses challenges for large-scale pilot testing and application promotion. In this study, we simulated the papermaking environment to collect enzyme activity data and built a machine learning model, which was capable of predicting enzyme activity under a full range of conditions with an accuracy of R 2 of 0.93. Subsequently, we employed genetic approaches to achieve: 1) the prediction of optimal enzyme synergy conditions, and 2) the determination of enzyme activity under actual conditions. Experimental validation demonstrated that optimal conditions can be derived through the coupling of experimental and machine learning methods. Our work highlights the potential of machine learning-based approaches to improve the efficiency of parameter selection and reduce the cost of industrial application in pilot plants. PAPERMAKING “Understanding Sizing Conditions with Alkenyl Succinic Anhydride: Experimental Analysis of pH and Anionic Trash Catcher Effects on Softwood Kraft Pulp”, Franco, Jorge; Carlos Bastidas, Juan; Jameel, Hasan; Gonzalez, Ronalds, BioResources , Vol.20(2), 2025, p4378. A 32 factorial experimental design was conducted to evaluate the effects of pH and anionic trash catcher (ATC) dosage on Cobb number (1 min), cationic demand, and conductivity in softwood kraft pulp sizing with Alkenyl Succinic Anhydride (ASA). Results indicated that acidic conditions tended to enhance ASA's reaction with cellulose, leading to superior hydrophobicity (Cobb number, 1 min = 23 g/m² at pH 4.0 and 121μeq/L cationic demand). Statistical analysis confirmed that pH exerted a stronger influence on ASA performance (p-value 2.0x10 -7 ) compared to ATC dosage (p-value 0.0297), while conductivity had minimal effect. The findings suggest that optimizing ASA application in acid conditions improves water resistance, reducing reliance on high ATC dosages. This study provides valuable insights into ASA application strategies for papermaking, particularly in furnishes that do not require alkaline conditions to retain fillers, by optimizing wet-end chemistry control for enhanced sizing efficiency.
Technical Abstracts
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