TY - JOUR

T1 - Compositional distributions in multicomponent aggregation

AU - Lee, K.

AU - Kim, T.

AU - Rajniak, P.

AU - Matsoukas, T.

N1 - Funding Information:
K.L. acknowledges the financial support of KOSEF through Basic Research Fund (R01-2004-000-10944-0) and National Core Research Center for Nanomedical Technology (R15-2004-024-00000-0).

PY - 2008/3

Y1 - 2008/3

N2 - We consider the granulation of two components, a "solute" (the component of interest) and an excipient. We specifically focus on cases such that the aggregation kernel is independent of the composition of the aggregating granules. In this case, theory predicts that the distribution of components is a Gaussian function such that the mean concentration of solute in granules of a given size is equal to the overall mass fraction of solute in the system, and the variance is inversely proportional to the granule size. To study these effects, we perform numerical simulations of the bicomponent population balance equation using a constant aggregation kernel as well as a kernel based on the kinetic theory of granular flow (KTGF). If the solute and excipient are initially present in the same size (monodisperse initial conditions), both kernels produce identical distributions of components. With different initial conditions, the KTGF kernel leads to better mixing of components, manifested in the form of narrower compositional distributions. These behaviors are in agreement with the predictions of the theory of aggregative mixing. We further demonstrate that the overall mixedness of the system is controlled by the initial degree of segregation in the feed and show that the size distribution in the feed can be optimized to produce the narrowest possible distribution of components during granulation.

AB - We consider the granulation of two components, a "solute" (the component of interest) and an excipient. We specifically focus on cases such that the aggregation kernel is independent of the composition of the aggregating granules. In this case, theory predicts that the distribution of components is a Gaussian function such that the mean concentration of solute in granules of a given size is equal to the overall mass fraction of solute in the system, and the variance is inversely proportional to the granule size. To study these effects, we perform numerical simulations of the bicomponent population balance equation using a constant aggregation kernel as well as a kernel based on the kinetic theory of granular flow (KTGF). If the solute and excipient are initially present in the same size (monodisperse initial conditions), both kernels produce identical distributions of components. With different initial conditions, the KTGF kernel leads to better mixing of components, manifested in the form of narrower compositional distributions. These behaviors are in agreement with the predictions of the theory of aggregative mixing. We further demonstrate that the overall mixedness of the system is controlled by the initial degree of segregation in the feed and show that the size distribution in the feed can be optimized to produce the narrowest possible distribution of components during granulation.

UR - http://www.scopus.com/inward/record.url?scp=38149093234&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38149093234&partnerID=8YFLogxK

U2 - 10.1016/j.ces.2007.07.060

DO - 10.1016/j.ces.2007.07.060

M3 - Article

AN - SCOPUS:38149093234

SN - 0009-2509

VL - 63

SP - 1293

EP - 1303

JO - Chemical Engineering Science

JF - Chemical Engineering Science

IS - 5

ER -