(614b) Thermodynamic Model for Estimating Progress of Equilibrium Limited Reactive Crystallizations

Reactive crystallization is leveraged when the reaction between two species yields a product that can be crystallized from the solution due to its poor solubility. The reactions in the reactive crystallization can be irreversible or equilibrium limited depending on the reacting species. In the case of an irreversible reaction with a fast conversion timescale, monitoring the progress of the crystallization is relatively straightforward. The mass of solids that crystallizes on adding a certain amount of reactant species can be trivially estimated. This calculation only requires stoichiometric knowledge of the reaction, and the solubility of the product in the reaction mixture. On the contrary, in the case where the reaction is equilibrium limited, it is non-trivial to estimate the solids that crystallize on addition of a known amount of the reactant species. This is due to a lack of understanding of the equilibrium bottleneck. The unknown equilibrium constant dictates the final amount of product formed based on the initial concentration of reactants. Additionally, the removal of the product from the solution mixture by precipitation induced by crystallization drives the reaction forward according to the Le Chatelier's principle.

In this talk, we will discuss one of the strategies to model the progress of an equilibrium limited reactive crystallization in context of a salt formation reaction. The talk will aim to build a theoretical foundation for estimating the equilibrium constant. We will first discuss the immediate limitations of estimating the equilibrium constant based on literature data in pertinent solvent systems. We formulated a model that is motivated from thermodynamic principles but informed with experimental data from solubility assays. We will demonstrate that the model developed on experiments with reconstructed crude from lab grade pure solvents accurately captures the thermodynamic behavior of the real reaction crude. This model was used to inform a crystallization process that was successfully executed at scale.

Disclosure:

Kartik Kamat, Akshay Korde, Stephen P Lathrop, Travis B Dunn, Jeff Kallemeyn, Sharad Maheshwari, Daniel A Pohlman, Manish Kelkar, and Nandkishor Nere are employees of AbbVie. All authors may own AbbVie stock. AbbVie sponsored and funded the study; contributed to the design; participated in the collection, analysis, and interpretation of data, and in writing, reviewing, and approval of the final publication.