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Manipulating Frontal Polymerization and Instabilities with Phase-Changing Microparticles.

Yuan Gao1,2, Mason A Dearborn3, Sagar Vyas1,2

  • 1Beckman Institute of Advanced Science and Technology, University of Illinois, Urbana, Illinois 61801, United States.

The Journal of Physical Chemistry. B
|July 6, 2021
PubMed
Summary
This summary is machine-generated.

Adding poly(caprolactone) microparticles to frontal polymerization (FP) stabilizes the process by absorbing heat, reducing instabilities, and controlling front velocity and temperature in thermoset manufacturing.

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Area of Science:

  • Polymer Science
  • Materials Science
  • Chemical Engineering

Background:

  • Frontal polymerization (FP) is a rapid, eco-friendly method for thermoset polymers and composites.
  • FP can exhibit thermo-chemical instabilities, leading to material property variations.
  • Controlling these instabilities is crucial for predictable material outcomes.

Purpose of the Study:

  • To investigate the effect of poly(caprolactone) microparticles on frontal polymerization instabilities.
  • To analyze the influence of microparticles on front velocity, temperature, and pattern formation.
  • To validate a reaction-diffusion model predicting these effects.

Main Methods:

  • Numerical analyses of reaction-diffusion models.
  • Experimental frontal polymerization of cyclooctadiene with poly(caprolactone) microparticles.
  • Measurement of front velocity, temperature, and instability characteristics.

Main Results:

  • Microparticle melting absorbs exothermic energy, reducing thermal instability amplitude and order.
  • Poly(caprolactone) microparticles suppress front velocity and peak temperatures.
  • Experimental data validated model predictions for velocity and temperature dependence on microparticle concentration.

Conclusions:

  • Homogeneously mixed poly(caprolactone) microparticles effectively stabilize frontal polymerization.
  • Microparticle addition offers a method to control FP dynamics and material properties.
  • The reaction-diffusion model accurately predicts the stabilizing effects of microparticles.