(231f) Morphology Prediction for Organic Salt Crystals
- Conference: AIChE Annual Meeting
- Year: 2020
- Proceeding: 2020 Virtual AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Monday, November 16, 2020 - 9:00am-9:15am
The above challenge inspired our group at UCSB to develop the first version of our automated crystal morphology prediction software ADDICT (Advanced Design and Development of Industrial Crystallization Technology) . Very recently, we have upgraded ADDICTâs software framework to enable it to implement crystal growth models for any crystal complexity.  and rewritten its code using object-oriented programming in Matlab as well as addition of new features in the third version of ADDICT (ADDICT3) . Therefore, based on these recent advances we can start attempting to predict the morphology for organic salt crystals.
Organic salt crystals are an important class of materials in the chemical, pharmaceutical, and nonlinear optical (NLO) industries. It is challenging to use mechanistic growth models to predict the morphology of such crystals, and in fact there are no other papers on the prediction of their morphology grown from solvents using such models. Organic salt crystals generally have stronger interactions than organic crystals, resulting in more complex periodic bond chains (PBCs) that are difficult to handle.
In this study, the concepts of a neutral growth unit, a building unit, and new PBC rules are proposed to predict the morphology of organic salts. We use two examples to study the morphology of such crystals grown from solvent. They are: (1) L-leucine hydrobromide and (2) glycinium trifluoroacetate. The predicted crystal shapes grown from water solution are consistent with the experimental results, which provides evidence for the reliability of the proposed method.
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 Zhao, Y., Tilbury, C. J., Landis, S., Sun, Y., Li, J., Zhu, P., & Doherty, M. F. (2020). Cryst. Growth Des., (Accept)