Agglomeration growth model

Critical size / density Needle growth by agglomeration Figure 8.3 Sketch of the growth model for nanofibers via sublimation in high vacuum. 

Consider the erystal size distribution in a model MSMPR erystallizer arising beeause of simultaneous nueleation, growth and agglomeration of erystalline partieles. Let the number of partieles with a eharaeteristie size in the range L to L + dL be n L)dL. It is assumed that the frequeney of sueeessful binary eollisions between partieles (understood to inelude both single erystals and previously formed agglomerates) of size V to V + dV and L to Ll +dL" is equal to j3n L )n L")dL dL". The number density n L) and the eollision frequeney faetor (3 are related to some eonvenient volumetrie basis, e.g. unit volume of suspension. 

The model is able to predict the influence of mixing on particle properties and kinetic rates on different scales for a continuously operated reactor and a semibatch reactor with different types of impellers and under a wide range of operational conditions. From laboratory-scale experiments, the precipitation kinetics for nucleation, growth, agglomeration and disruption have to be determined (Zauner and Jones, 2000a). The fluid dynamic parameters, i.e. the local specific energy dissipation around the feed point, can be obtained either from CFD or from FDA measurements. In the compartmental SFM, the population balance is solved and the particle properties of the final product are predicted. As the model contains only physical and no phenomenological parameters, it can be used for scale-up. 

Concept used in sophisticated scaling models, whereby certain ions in aqueous solution are said to associate in pairs (e.g., CaS04, CaHC03-). These ion pairs are then deducted from the total analytical value, to provide an estimate of the free ion content available for seed crystal scaling or growth agglomeration and deposition. 

Particle Formation, Electron microscopy and optical microscopy are the diagnostic tools most often used to study particle formation and growth in precipitation polymerizations (7 8). However, in typical polymerizations of this type, the particle formation is normally completed in a few seconds or tens of seconds after the start of the reaction (9 ), and the physical processes which are involved are difficult to measure in a real time manner. As a result, the actual particle formation mechanism is open to a variety of interpretations and the results could fit more than one theoretical model. Barrett and Thomas (10) have presented an excellent review of the four physical processes involved in the particle formation oligomer growth in the diluent oligomer precipitation to form particle nuclei capture of oligomers by particle nuclei, and coalescence or agglomeration of primary particles. 

Turkevich who established the first reproducible standard procedure for the preparation of metal colloids [44] also proposed a mechanism for the stepwise formation of nanoclusters based on nucleation, growth, and agglomeration [45,46]. This model, refined by data from modern analydical techniques and results from thermodynamic and kinetic studies, is in essence stiU valid today (Figure 2) [82]. 

Kapur and Fuerstenau (K6) have presented a discrete size model for the growth of the agglomerates by the random coalescence mechanism, which invariably predominates in the nuclei and transition growth regions. The basic postulates of their model are that the granules are well mixed and the collision frequency and the probability of coalescence are independent of size. The concentration of the pellets is more or less fixed by the packing... 

The method of lines and system identification are not restricted in their applicability. System identification is preferred because the order of the resulting state space model is significantly lower. Another advantage of system Identification is that it can directly be applied on experimental data without complicated analysis to determine the kinetic parameters. Furthermore, no model assumptions are required with respect to the form of the kinetic expressions, attrition, agglomeration, the occurence of growth rate dispersion, etc. 

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