Application of controlled cooling and seeding in batch crystallization

Abstract

Some aspects of batch cooling crystallization in the industrial practice are analysed by computer simulations. The results indicate that without appropriate kinetics and very accurate process control, even the qualitative effects of applying controlled cooling and seeding are highly unpredictable. An increase in product size by applying controlled cooling is likely to be successful only rather randomly and the size distribution becomes broader. A linear or weakly non-linear cooling curve usually produces larger crystals than a natural cooling curve, and a better reproducibility than a controlled cooling curve. Seeding increases both size and reproducibility, but is also likely to increase significantly the coefficient of variation of the product distribution. The product weight mean size and coefficient of variation may increase or decrease at increasing amount of seeds, depending on governing kinetics. ~~~~ . ~~~Nous analysons dans cet article quelques-uns des aspects de la cristallisation par refroidissement discontinu dans la pratique industrielle B I'aide d'une simulation par ordinateur. Les resultats montrent que sans une cinCtique approprike et un contrBle de procede trks precis, meme les effets qualitatifs d'un refroidissement et d'un ensemencement contrcilis sont hautement non predictibles. Une augmentation de la taille du produit par un refroidissement contrBI& a peu de change de survenir et la distribution de taille s'accroit. Une courbe de refroidissement lineaire ou ICgkrement non lineaire donne des cristaux plus larges que dans le cas d'une courbe de refroidissement naturelle et donne une meilleure reproductibilite qu'une courbe de refroidissement contr61C. L'ensemencement augmente la taille et la reproductibilite mais augmente aussi probablement de faqon significative le coefficient de variation de la distribution du produit. Le poids moyen du produit et son coefficient de variation peuvent augmenter ou diminuer B des quantites de graines croissantes. en fonction de la cinitique gouvernant la reaction.Keywords: batch cooling crystallization, simulation of CSD, cooling profile and seeding influence. batch cooling crystallizer is supposed to produce a I20

Importance of macromixing in batch cooling crystallization

“…In total, this article is based on about 125 simulations for potassium sulfate. In addition, about 120 simulations have been made for batch cooling crystallization of citric acid monohydrate (for kinetics see Bohlin and Rasmuson, 1992a).…”

“…The specific set of parameters used in the simulations are given in Table 1. Kinetic parameters are based on (Bohlin and Rasmuson, 1992a) data for potassium sulfate. The operating conditions are such that the process behaves like a normal batch cooling crystallization, that is, typical peaks appear in supersaturation and nucleation rate vs. time (see Figure 1 of Bohlin and Rasmuson, 1992b).…”

“…The crystal growth rate and in particular the nucleation rate depend strongly on supersaturation. In a well-mixed batch cooling crystallizer, the product size distribution is sensitive to changes in supersaturation, nucleation and growth kinetics, and processing conditions (Bohlin and Rasmuson, 1992a). Garside (1985) estimated the supersaturation half-life (that is, the time needed to deplete the supersaturation to half its initial value) in continuous crystallizers.…”

Optimal seed recipe design for crystal size distribution control for batch cooling crystallisation processes

“…Seeding seems to be treated as an art rather than science (Adi et al, 2007;Jagadesh et al, 1999;Kalbasenka et al, 2007;Kubota et al, 2001;Ludwick and Henderson, 1968;Lung-Somarriba et al, 2004) and generally there is a lack of systematic methodologies related to the amount and size of seeds that should be added into a crystallizer to obtain a product with a desired size distribution. Although it is recognized that the most important manipulated variables for the optimisation of crystallisation processes are supersaturation trajectories as well as the seed characteristics (Bohlin and Rasmuson, 1996;Heffels and Kind, 1999;Kalbasenka et al, 2007;Ruf et al, 2000, Yannick et al, 2009, the number of approaches focusing on temperature or anti-solvent addition trajectory optimisations is disproportionally higher than contributions considering seed recipe optimisations. The approaches proposed so far, mainly consider the optimisation of the width and amount of a particular monomodal seed distribution (Chung et al, 1999;Kalbasenka et al, 2007).…”

Neural Network Based Modeling and Control for a Batch Heating/Cooling Evaporative Crystallization Process

“…The crystallization kinetics and physical properties of citric acid-water system are shown in Table 1 and the initial values as shown in Table 2 which were excerpted from Bohlin and Rasmuson [28],Choong and Smith [9] as well as Alexander Apelblat [26]. …”