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Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
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Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
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Polymorphism refers to the existence of a drug substance in multiple crystalline forms, known as polymorphs. Recently, this term has been expanded to include solvates (forms containing a solvent), amorphous forms (non-crystalline forms), and desolvated solvates (forms from which the solvent has been removed).
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Synthesis of Terpolymers at Mild Temperatures Using Dynamic Sulfur Bonds in PolyS-Divinylbenzene
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Predicting Solute Diffusivity in Polymers Using Time-Temperature Superposition.

Robert M Elder1, David M Saylor1

  • 1Center for Devices and Radiological Health, FDA, Silver Spring, Maryland 20903, United States.

The Journal of Physical Chemistry. B
|May 18, 2022
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Summary
This summary is machine-generated.

We developed a new method using time-temperature superposition (TTS) to predict solute diffusivity in polymers. This approach significantly reduces computational costs for molecular dynamics simulations.

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Area of Science:

  • Materials Science
  • Polymer Science
  • Computational Chemistry

Background:

  • Predicting solute diffusivity (D) in glassy polymers is crucial for material design.
  • Atomistic molecular dynamics (MD) simulations are powerful but computationally expensive for long timescales.

Purpose of the Study:

  • To develop a novel, computationally efficient method for predicting solute diffusivity in glassy polymers.
  • To apply the time-temperature superposition (TTS) principle to molecular dynamics simulations.

Main Methods:

  • Utilized atomistic molecular dynamics simulations combined with the time-temperature superposition (TTS) principle.
  • Incorporated the Debye-Waller factor (⟨u^2⟩) and thermodynamic scaling concepts.
  • Rescaled solute mean-squared displacement curves to generate a master curve for predicting diffusivity.

Main Results:

  • The TTS approach successfully predicted solute diffusivity (D) with reasonable accuracy across various polymer/solute systems.
  • The method effectively extended simulation timescales from nanoseconds to seconds and beyond.
  • Achieved significant reductions in computational cost compared to standard MD simulations.

Conclusions:

  • The novel TTS application provides a rapid and routine method for estimating solute diffusivity in polymers.
  • This simulation-based approach offers a valuable tool for materials research and development.
  • The method balances temperature and solute caging effects for accurate dynamic predictions.