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A density-functional model for controlled release.

Timothy J Kosto1, E Bruce Nauman

  • 1Howard P. Isermann Department of Chemical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. tjk095@alumni.lehigh.edu

Journal of Controlled Release : Official Journal of the Controlled Release Society
|December 4, 2003
PubMed
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Density-functional theory models polymer diffusion in controlled release systems, revealing a diffusional exponent of 1/2 and an accelerated particle growth exponent of 2/3 due to particle elimination.

Area of Science:

  • Materials Science
  • Chemical Engineering
  • Computational Chemistry

Background:

  • Controlled release systems often involve complex biomolecule-polymer composites.
  • Understanding polymer diffusion is crucial for optimizing drug delivery device performance.
  • Existing models may not fully capture the multiphase nature of these systems.

Purpose of the Study:

  • To apply density-functional theory to model polymer diffusion in controlled release systems.
  • To investigate the diffusional driving forces and release rates.
  • To compare simulation results with traditional exponential models.

Main Methods:

  • Utilized the modified Cahn-Hilliard equation for polymer diffusion modeling.
  • Implemented one-dimensional periodic and two-dimensional near-zero concentration boundary conditions.

Related Experiment Videos

  • Incorporated Flory-Huggins free energy of mixing to determine chemical potential differences.

    • Main Results:

    • Simulations yielded a diffusional exponent of 1/2, consistent with Fickian diffusion at early stages.
    • Observed particle growth with a particle growth exponent of 2/3, double that of typical bulk ripening systems.
    • Identified particle elimination via diffusion out of the system as a key factor in accelerated growth.

    Conclusions:

    • Density-functional theory provides a robust framework for modeling polymer diffusion in complex drug delivery systems.
    • The model accurately predicts early-time Fickian diffusion and highlights unique particle growth dynamics.
    • The findings offer insights into optimizing controlled release formulations by accounting for multiphase behavior and particle dynamics.