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Thermal Guanidine Metathesis for Covalent Adaptable Networks.

Alberto J Melchor Bañales1, Michael B Larsen1

  • 1Department of Chemistry, Western Washington University, Bellingham, Washington 98225, United States.

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|June 1, 2022
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We introduce thermal guanidine metathesis (TGM) as a new dynamic chemical reaction for creating covalent adaptable network (CAN) materials. These TGM-based CANs can be reprocessed, showing dynamic properties like dissolution and stress relaxation.

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Area of Science:

  • Polymer Chemistry
  • Materials Science
  • Chemical Engineering

Background:

  • Covalent adaptable networks (CANs) are cross-linked polymers that can be reprocessed.
  • Existing CANs often rely on specific reversible reactions for their dynamic behavior.

Purpose of the Study:

  • To introduce and characterize thermal guanidine metathesis (TGM) as a novel dynamic chemical reaction for CAN materials.
  • To demonstrate the reprocessable nature and dynamic properties of TGM-based CANs.

Main Methods:

  • Investigated the mechanism of TGM using small molecule studies.
  • Synthesized guanidine-cross-linked network polymers.
  • Evaluated dynamic behaviors including reprocessing, dissolution with exchange partners, and stress relaxation above the glass transition temperature (Tg).
  • Analyzed kinetic data and compared activation energies with theoretical models.

Main Results:

  • Confirmed that TGM proceeds via a dissociative mechanism.
  • Demonstrated that guanidine-cross-linked polymers can be reprocessed at elevated temperatures.
  • Observed dynamic behaviors such as dissolution and stress relaxation in TGM-based CANs.
  • Found consistency between experimental activation energies and the Semenov-Rubinstein model predictions.

Conclusions:

  • Thermal guanidine metathesis (TGM) is a viable dynamic reaction for developing reprocessable covalent adaptable network (CAN) materials.
  • TGM-based CANs exhibit tunable dynamic properties, including reprocessing and stress relaxation.
  • The study validates theoretical models for thermoreversible gelation in highly cross-linked networks.