Ethanolysis of PLA using ChCl/ZnAc deep eutectic solvent for sustainable ethyl lactate production

Polylactic acid (PLA) is a biodegradable polyester derived from renewable resources and is increasingly used as a sustainable alternative to conventional plastics. However, due to limitations in mechanical recycling, chemical recycling methods are needed to promote a circular plastic economy. One promising approach is the ethanolysis of PLA to produce ethyl lactate (EtLa), a valuable green solvent used across several industries.

Previous studies have explored the use of deep eutectic solvents (DES) as sustainable catalysts for PLA depolymerisation. However, limited work has been done on the influence of catalyst composition and reaction kinetics. In this study, the ethanolysis of PLA using a DES composed of choline chloride (ChCl) and zinc acetate (ZnAc) in a 1:1 molar ratio was investigated, with a focus on the effect of ZnAc form (anhydrous vs. dihydrate) on catalytic performance.

Reactions were carried out using PLA in powder and film forms (3g) with ethanol (50 mL, ≥99.5%) and ChCl/ZnAc DES (1:1) under continuous stirring. A range of temperatures (80 °C to 180 °C) and reaction times (up to 8 hours) were tested using a 100 mL glass reactor with oil bath heating at atmospheric pressure. After reaction, mixtures were filtered under vacuum, and the yield of EtLa was quantified by using gas chromatography. PLA conversion and EtLa yield were systematically evaluated as functions of morphology, temperature, and reaction time.

The highest EtLa yield of 92% was achieved after 8 hours at 140 °C using PLA film, with complete conversion observed. In comparison, PLA powder yielded lower conversion under the same conditions, indicating that film morphology enhances degradation efficiency. Compared to existing studies, the method enabled higher EtLa yields at lower temperatures and shorter times, demonstrating improved efficiency. A temperature-dependent kinetic model was developed to describe the ethanolysis process and predict optimal conditions based on reaction parameters.