Return
Self-driven tandem alcoholysis for full upcycling of waste polycarbonate plastics
DOI:10.1038/s41467-026-71261-x.png)
Abstract
En 中文
Conventional alcoholysis processes for polycarbonate (PC) recycling require excess methanol input, high reaction temperatures and complicated downstream product separation steps, severely limiting environmental and economic sustainability. Here we report a facile, self-driven tandem alcoholysis process to address these challenges. Methanol-based PC alcoholysis reaction is coupled to a downstream glycerol transesterification step to rapidly convert the dimethyl carbonate intermediate into methanol, thus forming a closed-loop methanol flow to boost the overall reactions. Additionally, the reactions are catalyzed by eggshell-derived multimetallic CaO, which provides abundant acid–base sites for synergistically deprotonating alcohols and activating ester bonds to facilitate a selective conversion. This integrated design not only enables 98.8% less methanol usage and significantly lower reaction temperature than the PC-alone alcoholysis process (80 °C versus >130 °C), but also generates bisphenol A (96% yield) and 5-hydroxymethyl-1,3-dioxolan-2-one (90% yield) as higher-value products. The process is adaptable to treating mixed-plastic feeds with robust performance. The pilot-scale trials (>5 kg) using real mixed plastic waste demonstrate superior upcycling performance and distinctly improved environmental and economic benefits over the existing industrial synthesis routes. Overall, this scalable, self-driven tandem alcoholysis process offers a sustainable, industrially-viable platform for upcycling PC-containing waste plastics. Recycling polycarbonate plastics is energy intensive and depends on excess methanol. This work couples plastic breakdown with glycerol conversion to regenerate methanol in situ, reducing energy use while achieving high yields at pilot scale.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
15.7
Papers:
9.2W
Citations:
91.2W

