Computational Simulation Tools to Support the Tissue Paper Furnish Management: Case Studies for the Optimization of Micro/Nano Cellulose Fibers and Polymer-Based Additives

Abstract

Tissue paper production frequently combines two main types of raw materials: cellulose fibers from renewable sources and polymer-based additives. The development of premium products with improved properties and functionalities depends on the optimization of both. This work focused on the combination of innovative experimental and computational strategies to optimize furnish. The main goal was to improve the functional properties of the most suitable raw materials for tissue materials and develop new differentiating products with innovative features. The experimental plan included as inputs different fiber mixtures, micro/nano fibrillated cellulose, and biopolymer additives, and enzymatic and mechanical process operations. We present an innovative tissue paper simulator, the SimTissue, that we have developed, to establish the correlations between the tissue paper process inputs and the end-use paper properties. Case studies with industrial interest are presented in which the tissue simulator was used to design tissue paper materials with different fiber mixtures, fiber modification treatments, micro/nano fibrillated cellulose, and biopolymer formulations, and to estimate tissue softness, strength, and absorption properties. The SimTissue was able to predict and optimize a broader range of formulations containing micro/nanocellulose fibers, biopolymer additives, and treated-fiber mixtures, saving laboratory and industrial resources.

Keywords

• absorption
• cellulose fibers
• computational simulation
• furnish optimization
• modeling
• polymeric additives