Frontiers in Bioengineering and Biotechnology (Jul 2023)
Vitrimer synthesis from recycled polyurethane gylcolysate
Abstract
Polyurethanes and plastics have become ubiquitous in modern society, finding use in a wide variety of applications such as clothing, automobiles, and shoes. While these materials provide numerous benefits to human life, their persistence in the environment has caused ecological imbalances. Therefore, new processes are needed to make these materials more sustainable and re-usable. In 2011, Ludwik Leibler introduced a new class of covalent adaptable network (CAN) polymers called Vitrimers. Vitrimers possess self-repairing properties and are capable of being reprocessed due to dynamic exchange or breaking/recombination of covalent bonds, similar to thermoset materials. This study explores the synthesis of Vitrimers using waste polyurethane or plastics as feedstock. The raw materials were glycolysed to obtain the glycolysate, which was then used as a reagent for the Vitrimers synthesis. The main objective of this study was to achieve the maximum self-repairable rate of the prepared sample. The Taguchi orthogonal analysis was employed to guide the experiments. The optimized experimental conditions for polyurethane glycolysis were determined to be under ethylene glycol and catalyzed by sodium hydroxide at 180°C for 1 h, resulting in the highest hydroxyl concentration in the glycolysate. In the second stage of the experiment, the ratio of hexamethylene diisocyanate (HDI) to solvent was set to 2, HDI trimer to solvent was 2, and PGE/glycolysate was 0.5, with equal amounts of PEG and glycolysate used as the solvent. The reaction was carried out at 80°C for 1 h, achieving a self-repair ability of 47.5% in the prepared sample. The results of this study show that waste polyurethane or plastics can be effectively recycled and transformed into vitrimers with self-repairing properties. The use of glycolysis as a feedstock is a promising method for the sustainable recycling of polyurethane waste. The Taguchi orthogonal analysis is an effective approach for optimizing experimental conditions and improving the reproducibility of the results.
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