Investigates recycling outcomes of polyester using dynamic covalent networks, suggesting improved processability and performance.
The widespread application of thermoplastic polyesters in modern industries is overshadowed by their unsustainable recycling paradigms. Dynamic covalent networks (DCNs) have emerged as a potential strategy to circumvent this problem. We have systematically investigated the structure and performance evolution of polyester-based DCNs with varying network densities during recycling, using poly(ethylene terephthalate) (PET) as the model polymer. The results demonstrate that the strategic incorporation of DCNs distinctly improves the reprocessability of PET. Remarkably, samples with relatively low density of DCNs retain desirably ductile fracture behavior during multiple reprocessing cycles (with >75% elongation at break retention after four reprocessing cycles). Furthermore, these samples exhibit moderate viscosity suitable for continuous processing even after multiple reprocessing cycles. Meanwhile, samples with higher density of DCNs maintain higher but stable viscosity during reprocessing. Their pronounced shear-thinning behavior enables compatibility with high-shear-rate processing such as injection molding. These promising performance characteristics can be attributed to fundamentally different structural evolution pathways during reprocessing. In systems with low density of DCNs, the overall network structure is maintained through the synergistic effect of residual DCNs and physical entanglements, thereby preserving the processability and mechanical properties. In systems with high density of DCNs, the aggregation of DCNs induces phase separation into DCN-rich and DCN-poor domains. These findings provide critical insights into the rational design of polyester-based DCNs with optimized performance characteristics.
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Jia et al. (2025) studied this question.
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