Abstract
Vitrimer, a class of dynamically crosslinked polymers, exhibits a unique combination of processability and mechanical robustness, positioning them as a compelling alternative to conventional thermosets. By facilitating network rearrangement through exchangeable covalent bonds, these materials maintain their structural integrity while enabling reshaping, reprocessing, recycling, and damage self-healing. This capability addresses key limitations in aerospace composites, where heal-ability, recyclability, and thermal stability are critical design requirements. Despite these advantages, several challenges must be overcome before vitrimer can be fully integrated into aerospace applications. Mechanical strength, stiffness, and toughness, long-term durability under extreme operating conditions, and compatibility with automated composite manufacturing processes such as Automated Fiber Placement remain areas of active research. Recent studies indicate that vitrimer-based carbon fiber composites demonstrate improved performance metrics, particularly in impact resistance and damage tolerance, suggesting their viability for structural applications. However, further investigations are required to optimize resin formulations, refine processing parameters, incorporate multifunctionalities, and establish industry-standard testing protocols. Addressing these factors could enable the broader adoption of vitrimer, advancing the development of sustainable, high-performance aerospace materials. Artificial intelligence (AI) and machine learning (ML) could be a powerful tool to help design and discover new multifunctional vitrimer for aerospace applications. The use of vitrimer in aerospace applications offers significant potential for reducing material waste, enhancing recyclability, and lowering lifecycle energy consumption, which aligns with the principles of cleaner materials and cleaner production and sustainable material engineering. This work bridges the knowledge gap between cleaner material design and system-level sustainability.
| Original language | English |
|---|---|
| Article number | 100353 |
| Journal | Cleaner Materials |
| Volume | 18 |
| DOIs | |
| Publication status | Published - Dec 2025 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
Free Keywords
- Aerospace materials
- Artificial intelligence
- Circular economy
- Machine learning
- Multifunctionality
- Recycling
- Self-healing
- Vitrimer
ASJC Scopus subject areas
- Environmental Engineering
- Waste Management and Disposal
- Mechanics of Materials
- Polymers and Plastics
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