Distributions Of Fiber Characteristics As A Tool To Evaluate Mechanical Pulps

Mechanical pulps are used in paper products such as magazine or news grade printing papers or paperboard. Mechanical pulping gives a high yield; nearly everything in the tree except the bark is used in the paper. This means that mechanical pulping consumes much less wood than chemical pulping, especially to produce a unit area of printing surface. A drawback of mechanical pulp production is the high amounts of electrical energy needed to separate and refine the fibers to a given fiber quality. Mechanical pulps are often produced from slow growing spruce trees of forests in the northern hemisphere resulting in long, slender fibers that are well suited for mechanical pulp products. These fibers have large varieties in geometry, mainly wall thickness and width, depending on seasonal variations and growth conditions. Earlywood fibers typically have thin walls and latewood fibers thick. The background to this study was that a more detailed fiber characterization involving evaluations of distributions of fiber characteristics, may give improved possibilities to optimize the mechanical pulping process and thereby reduce the total electric energy needed to reach a given quality of the pulp and final product. This would result in improved competitiveness as well as less environmental impact. This study evaluated the relation between fiber characteristics in three types of mechanical pulps made from Norway spruce (Picea abies), thermomechanical pulp(TMP), stone groundwood pulp (SGW) and chemithermomechanical pulp (CTMP). In addition, the influence of fibers from these pulp types on sheet characteristics, mainly tensile index, was studied. A comparatively rapid method was presented on how to evaluate the propensity of each fiber to form sheets of high tensile index, by the use of raw data from a commercially available fiber analyzer (FiberLabTM). The developed method gives novel opportunities of evaluating the effect on the fibers of each stage in the mechanical pulping process and has a potential to be applied also on‐line to steer the refining and pulping process by the characteristics of the final pulp and the quality of the final paper. The long fiber fraction is important for the properties of the whole pulp. It was found that fiber wall thickness and external fibrillation were the fibercharacteristics that contributed the most to tensile index of the long fiber fractions in five mechanical pulps (three TMPs, one SGW, one CTMP). The tensile index of handsheets of the long fiber fractions could be predicted by linear regressions using a combination of fiber wall thickness and degree of external fibrillation. The predicted tensile index was denoted BIN, short for Bonding ability INfluence. This resulted in the same linear correlation between BIN and tensile index for 52 samples of the five mechanical pulps studied, each fractionated into five streams(plus feed) in full size hydrocyclones. The Bauer McNett P16/R30 (passed 16 meshwire, retained on a 30 mesh wire) and P30/R50 fractions of each stream were used for the evaluation. The fibers of the SGW had thicker walls and a higher degree of external fibrillation than the TMPs and CTMP, which resulted in a correlation between BIN and tensile index on a different level for the P30/R50 fraction of SGW than the other pulp samples. A BIN model based on averages weighted by each fiber´s wall volume instead of arithmetic averages, took the fiber wall thickness of the SGW into account, and gave one uniform correlation between BIN and tensile index for all pulp samples (12 samples for constructing the model, 46 for validatingit). If the BIN model is used for predicting averages of the tensile index of a sheet, a model based on wall volume weighted data is recommended. To be able to produce BIN distributions where the influence of the length or wall volume of each fiber is taken into account, the BIN model is currently based on arithmetic averages of fiber wall thickness and fibrillation. Fiber width used as a single factor reduced the accuracy of the BIN model. Wall volume weighted averages of fiber width also resulted in a completely changed ranking of the five hydrocyclone streams compared to arithmetic, for two of thefive pulps. This was not seen when fiber width was combined with fiber wallthickness into the factor “collapse resistance index”. In order to avoid too high influence of fiber wall thickness and until the influence of fiber width on BIN and the measurement of fiber width is further evaluated, it is recommended to use length weighted or arithmetic distributions of BIN and other fiber characteristics. A comparably fast method to evaluate the distribution of fiber wall thickness and degree of external fibrillation with high resolution showed that the fiber wallthickness of the latewood fibers was reduced by increasing the refining energy in adouble disc refiner operated at four levels of specific energy input in a commercial TMP production line. This was expected but could not be seen by the use of average values, it was concluded that fiber characteristics in many cases should be evaluated as distributions and not only as averages. BIN distributions of various types of mechanical pulps from Norway spruce showed results that were expected based on knowledge of the particular pulps and processes. Measurements of mixtures of a news‐ and a SC (super calendered) gradeTMP, showed a gradual increase in high‐BIN fibers with higher amounts of SCgrade TMP. The BIN distributions also revealed differences between the pulps that were not seen from average fiber values, for example that the shape of the BINdistributions was similar for two pulps that originated from conical disc refiners, a news grade TMP and the board grade CTMP, although the distributions were on different BIN levels. The SC grade TMP and the SC grade SGW had similar levels of tensile index, but the SGW contained some fibers of very low BIN values which may influence the characteristics of the final paper, for example strength, surface and structure. This shows that the BIN model has the potential of being applied on either the whole or parts of a papermaking process based on mechanical or chemimechanical pulping; the evaluation of distributions of fiber characteristics can contribute to increased knowledge about the process and opportunities to optimize it