462046 Tailoring the Crystal Size Distribution By Controlling the Crystallization Trajectory in Mass-Count Space

Wednesday, November 16, 2016: 4:35 PM
Cyril Magnin III (Parc 55 San Francisco)
Daniel J. Griffin, Martha A. Grover, Yoshiaki Kawajiri and Ronald W. Rousseau, School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA

Batch cooling crystallization is widely applied to isolate high-purity chemicals and pharmaceuticals. Control over the size of crystals produced by such operations can be critically important for efficient downstream processes. In this presentation we describe an approach for tailoring the crystal size distribution.

Previously, we proposed an alternative perspective on crystallization dynamics. Instead of understanding crystallization dynamics through the lens of the population balance framework, we viewed crystallization dynamics as movement in a 2D space mapped out by measured properties: the crystal mass and the chord count [1]. This, we found, revealed a simple, empirical model of crystallization dynamics and also facilitated the development of feedback schemes for controlling the mean crystal size [1, 2].

Here, a further use of the mass-count perspective will be described. By carefully controlling the mass-count trajectory we can rationally tailor the crystal size distribution. This will be demonstrated experimentally for paracetamol crystallization from ethanol.

[1] Griffin, D. J., Grover, M. A., Kawajiri, Y. and Rousseau, R. W. 2015. Mass-Count Plots for Crystal Size Control. Chemical Engineering Science 137, 338-351.

[2] Griffin, D. J., Grover, M. A., Kawajiri, Y. and Rousseau, R. W. 2016. Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization. Industrial & Engineering Chemistry Research 55, 1361-1372.

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