Startseite Preparation and dynamic simulation of a hemin reversible associated copolymer with self-healing properties
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Preparation and dynamic simulation of a hemin reversible associated copolymer with self-healing properties

  • Huijia Lu , Zhimin Ma , Xiaozhen Zhang , Jianxue Zhou , Hui Lv , Ye Tian , Xiaorong Wang ORCID logo EMAIL logo und Bin Pan EMAIL logo
Veröffentlicht/Copyright: 11. Oktober 2024
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Abstract

A reversible associated copolymer capable of healing at room temperature was constructed using acrylic acid (AA) and hemin as anionic monomers, and methacryloyloxyethyl trimethylammonium chloride (DMC) as the cationic monomer. Through optimization of the synthesis conditions, characterization by 1HNMR, infrared spectroscopy, ultraviolet-visible spectroscopy, Thermogravimetric analysis, differential scanning calorimetry, and construction of reasonable models for dynamic simulation, the following conclusions were obtained: The introduction of Hemin could convert light energy into heat energy, accelerating the healing of damaged areas; the predicted glass transition temperature value matched well with the experimental value, demonstrating the reliability of the constructed polymer model; the cohesive energy density (CED), dominated by electrostatic interactions, was identified as the key factor in the self-healing mechanism; the study also visually captured the microscopic process of self-healing within the polymer, providing a detailed understanding of the molecular rearrangements that facilitate this process. This work offers valuable insights into the design of reversible associated polymers, contributing to the broader goal of developing functional polymer materials aligned with circular economy principles.


Corresponding authors: Xiaorong Wang, School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, China, E-mail: ; and Bin Pan, College of Science, Liaoning Petrochemical University, Fushun, Liaoning 113001, China, E-mail:
Huijia Lu and Zhimin Ma contributed equally to this work.

Funding source: The general program of the Education Department of Liaoning Province

Award Identifier / Grant number: LJKMZ20220742

Funding source: Talent Scientific Research Fund of LNPU

Award Identifier / Grant number: No. 2016XJJ-010

Funding source: National Natural Science Foundation of China

Award Identifier / Grant number: No.61602228

Funding source: Liaoning Revitalization Talents Program

Award Identifier / Grant number: No. XLYC1807266

Acknowledgments

The authors would like to acknowledge Liaoning Petrochemical University.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Xiaorong Wang contributed to the conception of the study and wrote the manuscript; Huijia Lu and Xiaozhen Zhang performed the experiment; Bin Pan contributed significantly to analysis; Zhimin Ma performed the data analyses and manuscript preparation; Hui Lv helped perform the analysis with constructive discussions; Ye Tian helped do the revision; Jianxue Zhou helped perform the analysis with constructive discussions.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: This work is financially supported by the Talent Scientific Research Fund of LNPU (No. 2016XJJ-010), the general program of the Education Department of Liaoning Province (No. LJKMZ20220742), National Natural Science Foundation of China (No.61602228), and the Liaoning Revitalization Talents Program (No. XLYC1807266).

  7. Data availability: All data generated or analyzed during this study are included in this published article.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/polyeng-2024-0102).

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Received: 2024-06-02
Accepted: 2024-08-25
Published Online: 2024-10-11
Published in Print: 2024-11-26

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