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Polymers02:34

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The word polymer is derived from the Greek words “poly” which means “many” and “mer” which means “parts”. Polymers are long chains of molecules composed of repeating units of smaller molecules, known as monomers. They either occur naturally, such as DNA and proteins, or can be constructed synthetically, like plastics. They have varied structural characteristics, such as linear chains, branched chains, or complex networks, that contribute to the...
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Thermoset Polymer Matrix Structure and Properties: Coarse-Grained Simulations.

Vladimir Yu Rudyak1, Elizaveta A Efimova2, Daria V Guseva3

  • 1Faculty of Physics, Lomonosov Moscow State University, Leninskie gory, 1-2, Moscow 119991, Russia. vurdizm@gmail.com.

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|April 10, 2019
PubMed
Summary

This study reveals how initiator and plasticizer concentrations influence phthalonitrile thermoset properties using advanced simulations. A new method characterizes network topology, predicting mechanical modulus for polymers.

Keywords:
curingdissipative particle dynamicselastic modulusmesoscale chemistrynetwork topologynetworksphthalonitrilepolymerssimulations

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Area of Science:

  • Polymer Science
  • Materials Science
  • Computational Chemistry

Background:

  • Thermoset polymer network formation is complex and variable.
  • Understanding network topology is crucial for predicting material properties.

Purpose of the Study:

  • Investigate phthalonitrile thermoset curing and network topology.
  • Reveal the influence of initiator and plasticizer concentration on properties.
  • Propose a novel method for characterizing network topology.

Main Methods:

  • Dissipative particle dynamics simulations.
  • Graph theory tools for network analysis.
  • Correlation of topological parameters with material properties.

Main Results:

  • Developed a novel characterization of network topology based on simple cycle length and cycles per bond.
  • Initiator concentration primarily affects simple cycle length (mesh size).
  • Plasticizer concentration primarily determines cycles per bond (sponginess).

Conclusions:

  • The proposed topological parameters implicitly and precisely characterize polymer networks.
  • This approach predicts resulting network properties, including mechanical modulus.
  • The method is potentially applicable to other polymer networks like rubbers and gels.