The design and evaluation of biobased processes involving crystallization can be challenged owing to the lack of experimental data, leading to inaccurate predictions. This study presents a method for predicting the crystal purity and recovery yield of biobased amino acids, including l-alanine (ALA), l-histidine monohydrochloride monohydrate (HIS), and l-citrulline (CIT), in evaporative crystallization processes. An effective distribution model was proposed to describe the relationship between liquid and crystal purity by using an empirically modified logistic curve. By coupling mass balance with an effective distribution model, a method to predict the crystal purity was developed on the basis of the feed purity and recovery yield of the crystallization process. Furthermore, a statistical approach was applied to predict the defective product disturbances. Our results demonstrate that HIS achieves a higher crystal purity more easily than does ALA. Additionally, a quantitative analysis revealed that for all amino acids, the defective product rate decreases as the target crystal purity increases and minimum specification purity decreases. This study provides a basis for considering downstream recovery yield as an important metric in the design and evaluation of biobased processes involving crystallization.
Hong et al. (Sun,) studied this question.