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Step growth polymerization involves bi or multifunctional monomers. Bifunctional monomers react to form linear step growth polymers, whereas multifunctional monomers react to form non-linear or branched polymers.
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The extent of the...
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Age-aware constitutive materials model for a 3D printed polymeric foam.

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This study introduces a new model for 3D printed foams, predicting their long-term performance under stress and heat. This helps in designing more durable and reliable foam components for various applications.

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Polymer Science

Background:

  • Traditional elastomeric foams are widely used but have limitations.
  • 3D printing offers controlled micro-structures with potential for improved performance.
  • Characterizing long-term behavior of 3D printed foams is crucial for structural applications.

Purpose of the Study:

  • To develop a constitutive model for 3D printed close-packed foam structures under compression, considering thermal aging.
  • To accurately predict the evolution of stress-strain behavior, compression set, and load retention over time.

Main Methods:

  • Utilized the Ogden hyperfoam strain-energy functional within the Tobolsky two-network scheme.
  • Developed a thermal-age-aware constitutive model for 3D printed foam.
  • Applied time-temperature superposition to predict long-term changes and quantify uncertainty.

Main Results:

  • The model accurately describes experimentally measured stress-strain response, compression set, and load retention.
  • Predictions for long-term changes were enabled through time-temperature superposition.
  • Identified a single dominant aging mechanism at the molecular/network level based on Arrhenius activation barrier.

Conclusions:

  • The developed model provides a robust framework for predicting the long-term mechanical performance of 3D printed foams.
  • This enables the design of more reliable and durable components for demanding applications.
  • Understanding the aging mechanism facilitates material optimization and performance enhancement.