Compositional distributions in multicomponent aggregation

K. Lee, T. Kim, P. Rajniak, Themis Matsoukas

Research output: Contribution to journalArticle

23 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1293-1303
Number of pages11
JournalChemical Engineering Science
Volume63
Issue number5
DOIs
StatePublished - Mar 1 2008

Fingerprint

Kinetic theory
Granulation
Excipients
Aggregation
Agglomeration
kernel
Granular Flow
Kinetic Theory
Computer simulation
Initial conditions
Chemical analysis
Population Balance Equation
Gaussian Function
Segregation
Directly proportional
Predict
Numerical Simulation
Prediction
Demonstrate

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Cite this

Lee, K. ; Kim, T. ; Rajniak, P. ; Matsoukas, Themis. / Compositional distributions in multicomponent aggregation. In: Chemical Engineering Science. 2008 ; Vol. 63, No. 5. pp. 1293-1303.
@article{121686862731428583911c290185e6fc,
title = "Compositional distributions in multicomponent aggregation",
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.",
author = "K. Lee and T. Kim and P. Rajniak and Themis Matsoukas",
year = "2008",
month = "3",
day = "1",
doi = "10.1016/j.ces.2007.07.060",
language = "English (US)",
volume = "63",
pages = "1293--1303",
journal = "Chemical Engineering Science",
issn = "0009-2509",
publisher = "Elsevier BV",
number = "5",

}

Compositional distributions in multicomponent aggregation. / Lee, K.; Kim, T.; Rajniak, P.; Matsoukas, Themis.

In: Chemical Engineering Science, Vol. 63, No. 5, 01.03.2008, p. 1293-1303.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Compositional distributions in multicomponent aggregation

AU - Lee, K.

AU - Kim, T.

AU - Rajniak, P.

AU - Matsoukas, Themis

PY - 2008/3/1

Y1 - 2008/3/1

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

VL - 63

SP - 1293

EP - 1303

JO - Chemical Engineering Science

JF - Chemical Engineering Science

SN - 0009-2509

IS - 5

ER -