Phenomena-Based Modeling of Alkaline Pulping Processes

This doctoral thesis focuses on developing a phenomena-based molecular-level model for kraft and other alkaline pulping processes by utilizing fundamental knowledge on reaction kinetics, thermodynamics and mass transfer. A major benefit from the fundamental approach applied is that the model is, in principle, valid regardless of the reaction environment. Modelling of the pulping process at molecular level provides a new way to examine the relative importance of various phenomena, the validity of theories and provide a platform for developing and testing new ideas. In comparison with experimental research, simulation can be a more cost-efficient way to study and rethink processes, to make them more efficient and environmentally friendly and to improve the quality products with minimal cost. The objective of this thesis work was to create a comprehensive pulping chemistry model, including carbohydrate degradation and delignification in kraft and other alkaline pulping processes. The work was divided into parts and problems were solved in turns. First, literature was reviewed with a target to find the necessary data on the reaction mechanisms and the kinetic parameters of the reactions involved. Secondly, the missing knowledge on the reaction kinetics of strong nucleophiles with non-phenolic lignin with α-carbonyl functionality was obtained experimentally through applying the dimeric model compound adlerone. Further, lignin and carbohydrates were modelled as monomeric pseudo-compounds with experimentally determined chemical characteristics. The macromolecular aspect of lignin was considered in lignin dissolution. The pulping model developed is formed of an extensive library of the reactions of hydroxyl and hydrogen sulfide ions with pseudo-lignin and carbohydrate structures. When simulating the pulping under given conditions, the outcome consists of time-dependent concentrations of the pseudo-structures and real chemical compounds. Additionally, some engineering parameters, such as kappa number, intrinsic viscosity and brightness, were included in the model that derives them from the chemical composition. Consequently, the model could be validated by analytical data as well as by engineering parameters values. The model prediction was compared against experimental results and demonstrated generally a good correlation. The Donnan effect included in the model was important for predicting the content of hexenuronic acid in the system correctly. Inclusion of thermodynamic and stereochemical aspect of lignin could possibly improve the model prediction further.