PAPERmaking! FROM THE PUBLISHERS OF PAPER TECHNOLOGY Volume 6, Number 2, 2019
Impact of 5-Ply toilet paper configuration on its mechanical and absorption properties, Costa Vieira, J., Mendes, A., Carta, A., Fiadeiro, P., and Costa, A. BioResources , 15(4), DOI: 10.15376/biores.15.4.7475-7486. Several physical and mechanical properties can characterize tissue papers. In particular, low grammage but high values of bulk, flexibility, liquid absorption capacity, and softness are common properties for tissue papers. These properties must be adapted to meet the requirements of the final consumer, which can vary greatly in different countries. This work resulted from a study regarding the impact of two different stacking sequences of 5-ply toilet paper with configurations 1 and 2 (deco:micro embossing of 3:2 and 2:3 plies, respectively), which had the same base tissue papers in each mother reel, on their mechanical behavior and absorption capacity. The stacking sequence of the plies influenced the properties of the finished toilet paper. For configurations 1 and 2, after the embossing process, bulk increases of 46% and 40%, respectively, and water absorption capacity increases of 2% and 17%, respectively, were registered. In this case, the bulk increase was not the key property that influenced the water absorption capacity. Regarding mechanical properties, both configurations showed a higher negative impact caused by the deco embossing. For commercial purposes and to adhere to the final consumers’ preferences for toilet paper, configuration 1 was more suitable for mechanical strength, and configuration 2 was more suitable for absorption capacity. 3D fiber models to simulate and optimize tissue materials, Morais, F.P., Carta, A.M. N.S., Amaral, M.E., & Curto, J.M.R., BioResources , 15(4), DOI: 10.15376/biores.15.4.8833-8848. Tissue materials development using 3D computational tools to predict the influence of the combination of different fibers can be employed in the design of innovative tissue products and furnish optimization. Fibrous materials can be designed using different 3D fiber models for each type of fibers, detailed to the point where the wall fiber thickness, fiber lumen, and collapse degree are considered and presented in this work. Eucalyptus, Pinus, and Picea kraft cellulose pulp fibers were selected because they are representative of differentiated fiber types. The fiber morphological measurements were obtained using two methods: one uses the fibers in suspension, without restraints, and the other uses a capillary fiber alignment. The results indicate good repeatability for both methods but differences of 14% for fiber length weighted in length, 2% for fiber width, 11% for coarseness, 35% for curl, and 88% for fines content. Scanning electron microscopy images were used to identify the fiber dimensions inside the tissue structure. Four different types of fiber models for eucalyptus fibers, with different fiber wall thickness and lumen dimensions, were presented and used to predict 3D computational fibrous structures. WASTE TREATMENT A novel effluent quality predicting model based on genetic-deep belief network algorithm for cleaner production in a full-scale paper-making wastewater treatment, Guoqiang Niu, Xiaohui Yi, Chen Chen, Xiaoyong Li, Donghui Han, Bo Yan, Mingzhi Huang & Guangguo Ying, Journal of Cleaner Production , 265, Aug. 2020, https://doi.org/10.1016/j.jclepro.2020.121787. Recycling wastewater of the pulping and paper-making industry are widely considered for clean production, which heavily rely on the timely and accurate monitoring in paper-making wastewater treatment processes. A novel predicting model based on genetic-deep belief network algorithm was proposed to improve the predictive accuracy and reliability for process monitoring. Considering the deep belief networks (DBN) as a deep learning model is aiming to describe the relationship among variables in a complex process modeling, genetic algorithm (GA) was employed to reduce the input variables dimensionality, simplify the network structure and
Technical Abstracts
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