RESUMEN
The development of greener and more sustainable synthesis processes for manufacturing commodity chemicals is of great importance. The majority of current phenol production methods involve harsh reaction conditions with high energy consumption, causing severe environmental pollution. In this study, we present a novel approach for the decarboxylation of hydroxybenzoic acids (HBAs) to phenol using a choline chloride-urea (ChCl-urea) deep eutectic solvent (DES). Our study reveals the remarkable dual performance of ChCl-urea both as a catalyst and solvent for the decarboxylation of HBA, resulting in a high phenol yield (94 mol%) under mild reaction conditions. The proposed reaction pathway, established through a combination of experiments and computational simulations, enhances our understanding of this process. The recyclability of the DES system during decarboxylation was also assessed. Our findings demonstrate that the integration of DES into conventional chemical processes can pave the way for sustainable manufacturing, exemplifying a novel approach for producing phenol from abundant natural resources using designer solvents.
RESUMEN
To achieve a sustainable and circular economy, developing effective plastic recycling methods is essential. Despite advances in the chemical recycling of plastic waste, modern industries require highly efficient and sustainable solutions to address environmental problems. In this study, we propose an efficient glycolysis strategy for post-consumer polyethylene terephthalate (PET) using deep eutectic solvents (DESs) to produce bis(2-hydroxyethyl) terephthalate (BHET) with high selectivity. Choline chloride (ChCl)- and urea-based DESs were synthesized using various metal salts and were tested for the glycolysis of PET waste; ChCl-Zn(OAc)2 exhibited the best performance. The DES-containing solvent system afforded a complete PET conversion, producing BHET at a high yield (91.6%) under optimal reaction conditions. The degradation mechanism of PET and its interaction with DESs were systematically investigated using density functional theory-based calculations. Furthermore, an intuitive machine learning model was developed to predict the PET conversion and BHET selectivity for different DES compositions. Our findings demonstrate that the DES-catalyzed glycolysis of post-consumer PET could enable the development of a sustainable chemical recycling process, providing insights to identify the new design of DESs for plastic decomposition.