An improved, less erroneous protocol for the classical “cuen”, “cuoxam” or “cadoxen” viscosity measurements of pulps

Abstract

AbstractCorrectness and reliability of molar mass data by viscometry in organometallic solvents (cuen, cuoxam, cadoxen) are compromised by the alkalinity of these solvents which causes immediate depolymerization especially in the case of pulps with higher carbonyl content (oxidative damage). The viscosity values thus correspond to the molar mass after the beta-elimination reactions that underly these degradative processes, which is sometimes significantly smaller than the molar mass determined by gel permeation chromatography (GPC) in the non-degrading solvent system DMAc/LiCl. Despite this well-known drawback, viscosity measurements have become a standard approach for molar mass measurements due to their ease and fastness, especially in the pulp and paper industries. A potential way to reduce the inherent error of these molar mass determinations via viscosity measurements is a reductive treatment prior to dissolution of the pulp in the organometallic solvents, which converts the labile, alkali-sensitive carbonyl structures back to the respective alcohols. Using sodium borohydride (NaBH4) on different types of cellulosic pulps, we demonstrate the beneficial effects of such a reduction step on the determined degree of polymerization (DP) for all three common solvents: cuen, cuoxam and cadoxen. Molar mass distributions and profiles of carbonyl groups were determined by GPC and by carbonyl selective fluorescence labeling (“CCOA method”). Such a reductive treatment was especially valuable for hemicellulose-containing pulps. While the decreased measurement error according to the new protocol is beyond doubt, an immediate acceptance in the pulp and paper industries is at least questionable, because the new, more correct data would not agree with the old – wrong, but consistent – numbers accumulated over years and decades. In the long run, however, the new, improved protocol will prevail here as well due to its lower error rate.