An Innovative Computational Strategy to Optimize Different Furnish Compositions of Tissue Materials Using Micro/Nanofibrillated Cellulose and Biopolymer as Additives

Abstract

The furnish management of tissue materials is fundamental to obtain maximum quality products with a minimum cost. The key fiber properties and fiber modification process steps have a significant influence on the structural and functional properties of tissue paper. In this work, two types of additives, a commercial biopolymer additive (CBA) that replaces the traditional cationic starch and micro/nanofibrillated cellulose (CMF), were investigated. Different formulations were prepared containing eucalyptus fibers and softwood fibers treated mechanically and enzymatically and both pulps with these two additives incorporated independently and simultaneously with drainage in the tissue process range. The use of these additives to reduce the percentage of softwood fibers on tissue furnish formulations was investigated. The results indicated that a maximum of tensile strength was obtained with a combination of both additives at the expense of softness and water absorbency. With a reduction of softwood fibers, the incorporation of additives increased the tensile strength and water absorbency with a slight decrease in HF softness compared with a typical industrial furnish. Additionally, a tissue computational simulator was also used to predict the influence of these additives on the final end-use properties. Both additives proved to be a suitable alternative to reduce softwood fibers in the production of tissue products, enhancing softness, strength and absorption properties.

Keywords: absorbency; commercial biopolymer additive (CBA); micro/nanofibrillated cellulose (CMF); softness; strength; tissue paper materials.

Figure 1

SEM image of the CMF additive, highlighting a high magnification image (3000×) where it is possible to verify the micro and nanofibrils of this sample.

Figure 2

Coarseness as a function of the slenderness ratio of softwood fiber pulp (SW) with enzymatic treatment (SW + ENZ), with refining (SW + REF) and with the combination of both fiber modification treatments (SW + REF + ENZ).

Figure 3

SEM image of the softwood pulp with refining and enzymatic treatment with a high magnification image (500×) (a) and its pore diameter distribution (b).

Figure 4

SEM image of tissue formulation 4 (75% eucalyptus pulp + 25% softwood pulp-treated + 2% CBA + 2% CMF) with a high magnification image (1000×) where is possible to verify the inter-fiber bonding between CMF and the structure in more detail (a) and its pore diameter distribution (b).

Figure 5

FTIR-ATR spectrum of formulation 1 (blue), formulation 2 (red) and formulation 3 (green).

Figure 6

Properties of bulk and porosity (a), softness (b), tensile index (c) and water absorption capacity per unit of gram (d) of all tissue formulations.

Figure 7

SEM images of the cross-section of the tissue structures prepared with formulation 1 (a) and formulation 4 (b).

Figure 8

Percentage of variation in the properties of bulk, softness HF, softness TS7, tensile index and water absorption capacity of formulations 6, 7 and 8 compared with formulation 1 obtained with SimTissue.

Figure 9

Correlation between the tensile index and softness HF of tissue formulations.

Figure 10

Correlation between the water absorption capacity and softness HF (a) and tensile index (b) of the tissue formulations.

Figure 11

Klemm capillary rise method as a function of time for all tissue formulations.

Figure 12

Evolution of the end-use tissue properties of softness HF, tensile index and water absorption capacity with the incorporation of CBA (a), CMF (b) and softwood fibers (c) in formulations with 100% eucalyptus fibers. All variables were normalized to present the same scale range.