Crystallization is an important processing step for the manufacture of alpha lactose monohydrate (α-LM) from whey solutions. The efficient recovery of α-LM is an important issue for the Australian dairy industry, due to its value as a food and pharmaceutical ingredient and as a way to reduce the environmental impact of waste whey streams from cheese manufacturing processes. Knowledge of crystal growth and nucleation kinetics enables model construction to allow confident simulation of the manufacturing processes.
It has been demonstrated that impurities affect many mechanisms that occur during the crystallization of α-LM. However, studies concerning the effects of impurities on the nucleation kinetics of α-LM have not yet appeared in the scientific literature. The impact of impurities on the nucleation characteristics of α-LM is the major focus of this research, with nucleation rates being measured in pure lactose solutions, m lactose solutions with added impurities and in industrial whey permeate solutions.
The effect of process conditions on nucleation rates was investigated using pure lactose solutions. The following process conditions were investigated: absolute α-lactose supersaturation, solution temperature, stirring speed, number of seed crystals and seed crystal size. Nucleation rate was found to increase with the following variables, and a power law model was fitted to each: α-lactose supersaturation, stirring speed, and seed crystal size. Nucleation rate was found to increase linearly with increased numbers of seed crystals. An Arrhenius model described the relationship between nucleation rate and solution temperature, with nucleation rate decreasing with increasing temperature. A multiple linear regression model was constructed to model the effect of all variables on the nucleation rate in pure lactose solutions.
α-LM nucleation rates in solutions with added soluble salts were found to be significantly higher than the corresponding nucleation rates in pure solutions. Soluble salts were added individually and in combination to lactose solutions, and the nucleation rate measured. The investigated range of impurity concentration was 0.1% to 30% (expressed as mass impurity / mass of solid in solution). It was found that higher nucleation rates occurred irrespective of the type or combination of impurities, or the amount added. For solutions containing soluble impurities with lactose concentrations of 50 g anhydrous lactose / 100 g water, the nucleation rates were approximately 6 times higher than in corresponding pure lactose solutions. As for pure lactose solutions, in lactose solutions containing soluble impurities a power law modelled the relationships between nucleation rate and a-lactose supersaturation - the exponent term for pure solutions being significantly smaller.
The position of the secondary nucleation threshold (SNT) in lactose solutions containing soluble impurities was measured. Addition of soluble impurities does not measurably affect the position of the SNT, despite causing significant increases in the nucleation rate.
The effect of an insoluble impurity, calcium phosphate, on nucleation rate was also investigated. Calcium phosphate was found not to catalyse secondary nucleation in a lactose solution with concentration of 50 g anhydrous lactose / 100 g water. The impact of calcium phosphate on primary nucleation at higher supersaturations was not investigated and this is a recommendation for further research.
Nucleation rates in industrial permeate solutions were also measured. Nucleation rates in a highly purified whey permeate solution were consistent with rates measured in model whey permeate solutions. Nucleation rates in the equivalent impure industrial solution were lower than expected and it is hypothesised that other solution components such as protein and fat may have some influence.
Finally, two models for continuous nucleation with growth rate dispersion (GRD) growth are presented and described. Experimental data from Chapter 4 (manual sampling and off-line size measurement) are used to illustrate how one of the models works. In the future, the models may be useful for determining crystallization kinetics using data from continuous in-situ size distribution measurements. The shortcomings of in-line measurements using the Malvern Mastersizer are discussed, and recommendations for improvement are made.