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Degradation in cone-plate rheometry.

A J Giacomin1, P H Gilbert1

  • 1Chemical Engineering Department, Queen's University, Kingston, Ontario K7L 3N6, Canada.

The Review of Scientific Instruments
|January 3, 2019
PubMed
Summary
This summary is machine-generated.

This study quantifies oxidative degradation in rheometer tests, developing analytical models for oxygen diffusion and degradation rates. Cone-plate partitioning offers a superior method for accurate, longer measurements, even with oxygen-saturated samples.

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Area of Science:

  • Materials Science
  • Chemical Engineering
  • Polymer Science

Background:

  • Oxidative degradation can compromise rheological measurements.
  • Oxygen diffusion into samples is a key factor in degradation.
  • Accurate rheometer measurements require understanding and mitigating degradation.

Purpose of the Study:

  • To quantitatively analyze oxidative degradation in cone-plate rheometry.
  • To develop analytical expressions for oxygen concentration and degradation rates.
  • To evaluate methods for mitigating rheometer errors caused by oxidation.

Main Methods:

  • Quantitative analysis of oxidative degradation in a cone-plate rheometer.
  • Modeling inward radial oxygen diffusion from the free boundary.
  • Derivation of exact analytical expressions for oxygen concentration and degradation rate.
  • Integration of degradation rate over time to determine reacted oxygen.

Main Results:

  • Nitrogen blanketing reduces degradation but has limited benefits at short times.
  • Cone-plate partitioning offers a simpler solution for error mitigation.
  • Cone-plate partitioning enables longer, accurate measurements, even for oxygen-saturated samples.
  • Analytical expressions were derived for oxygen concentration and degradation rate.

Conclusions:

  • Nitrogen blanketing and cone-plate partitioning are effective strategies for mitigating oxidative degradation in rheometry.
  • Cone-plate partitioning is a more advantageous method for extending measurement times and maintaining sample integrity.
  • The derived analytical models provide valuable tools for predicting and controlling oxidative degradation during rheological testing.