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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Chemical Engineering...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Chemical Engineering Science
Article . 2008 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Compositional distributions in multicomponent aggregation

Authors: K. Lee; T. Kim; P. Rajniak; T. Matsoukas;

Compositional distributions in multicomponent aggregation

Abstract

Abstract 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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Top 10%
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