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Currently, the pulp and paper industry mainly uses average values of   mechanical pulp properties to characterize fibers, while printing paper   grammages keep decreasing, making every fiber more important for   strength, surface, and structure properties. Because fibers are   inhomogeneous, average values of the whole pulp may not be enough for   proper fiber characterization. This paper reports results from the   development of a method to measure the distribution of fiber bonding   ability in mechanical pulps.   Fibers from two commercial TMPs were fractionated into five   hydrocyclone streams, using a four-stage hydrocyclone system. The fiber   bonding ability of Bauer McNett fractions R16, P16/R30 and P30/R50   collected from each stream was analyzed. Five different methods of   evaluating fiber bonding ability all showed that fibers were separated   in the hydrocyclones according to their bonding ability.   Long fiber handsheets of the highest bonding fibers had up to 2.5 times   higher tensile strength for the P16/1330 fraction than handsheets from   the lowest bonding fibers. We also found that both the degree of   fibrillation and collapse resistance index (CRI) of the fibers obtained   from optical measurements are sufficient to predict quite accurately   the tensile strength of handsheets made from fiber fractions. Further,   we propose how to describe the distribution in fiber bonding ability   for mechanical pulps, by combining some of these five different   methods. A method to calculate fracture toughness of long fiber   handsheets based on acoustic emission is also illustrated.   A more rapid way to characterize fibers in mechanical pulps with   respect to their bonding ability distribution needs to be developed in   the future. It appears that it is time to move on from characterizing   pulp suspensions and handsheet properties using conventional approaches   based on average values.

This study discusses how fiber dimensions affect the tensile index and density of long fiber laboratory sheets. Five commercial mechanical pulps (three TMP grades, one SGW and one CTMP) were fractionated into five streams in a hydrocyclone pilot plant. Fiber dimensions and fibrillation were analyzed of the P16/R30 and P30/R50 fractions and compared to the sheet properties. For comparison, samples were also analyzed by SEM cross-sectional image analysis and in a MorFi Lab optical analyzer. Fibrillation index showed a high positive influence on long fiber tensile index and density, whereas fiber wall thickness, fiber width, and collapse resistance index a negative. Fiber width showed the vaguest correlation to long fiber tensile index and density of the analyzed fiber properties, but this increased when combined with fiber wall thickness into collapse resistance index, CRI. The correlations between fiber properties and sheet properties were on different levels for the different mechanical pulping processes, but a combination of collapse resistance index and fibrillation index into the novel factor BIN, Bonding ability INfluence, gave one linear relation of high correlation to long fiber tensile index for all pulps, except the SGW P30/R50 fraction, which showed the same linear correlation on a slightly lower level. BIN should be a useful tool in characterizing mechanical pulp fibers.

To improve the operation and energy efficiency of mechanical pulping processes, the effect of each stage of the process on the fibres should be carefully evaluated. Fibre-data from an optical analyser were used to predict tensile index by calculating BIN (Bonding ability /Nfluence). Wall volume weighted averages of wall thickness index and fibrillation index gave the most accurate predictions of the tensile index of laboratory sheets made from long fibre fractions of various mechanical pulps. Fibre width index, when used as a single factor, reduced the accuracy of the model. The ranking of some samples changed when fibre width was wall volume weighted compared to arithmetic. When fibre width was combined with wall thickness to give a collapse resistance index, no rankings changed. Weighted averages based on squared fibre length (length(2)) showed poor correlation to wall volume weighted averages for cross-sectional fibre dimensions, and resulted in different levels of correlation to long fibre tensile index for the five evaluated pulps.

Low consistency (LC) refining and high consistency refining (HC) has been studied in a TMP mill. When strength properties were increased, the development of fiber properties was different in LC- and HC-refining. Fiber curl decreased in LC-refining but increased in HC-refining. LC-refining decreased fiber curl and increased tensile index simultaneously in this study. It is therefore likely that the decreased fiber curl contributes to the increase of tensile index in LC-refining. Furthermore, fiber wall thickness decreased and external fibrillation increased in HC-refining, while these properties were only slightly influenced in the LC-refining. Fibrillation was found to decrease in most cases for LC-refining while fiber wall thickness index increased slightly but consistently, which might indicate a less dense structure of the fiber wall or its surface layers. Double-disc HC-refining with the same energy input as in a conical single-disc refiner resulted in fibers of higher external fibrillation, lower fiber wall thickness and higher fiber curl at a given fiber length. The results indicate that analyzing individual fiber dimensions could be a better tool for understanding how fibers develop in different kinds of refining than analyzing conventional handsheet properties.

Characterisation of fibres in mechanical pulps is important for process evaluation and control, and necessary to be able to optimise the refining process with respect to the total electric energy consumption. There are large variations of cross-sectional fibre characteristics in the wood raw material which influence the properties of the product. Despite this, it is common to evaluate the fibre characteristics as averages instead of distributions. This study shows that the raw data from a FiberLab analyser can be used to make distributions of measured and predicted fibre characteristics. The factor BIN (Bonding ability /Nfluence), which correlates to long fibre tensile index, includes both the external fibrillation and wall thickness of each fibre. Distributions of BIN, fibrillation and wall thickness which take the Characteristics of each fibre into Consideration have higher resolution than histograms. These distributions weighted by length and wall volume with maintained resolution revealed more information about the pulps than average values.