Abstract
Plastic waste has become a major environmental crisis, with the majority of plastic being produced ending up in open landfills and waterways every year. Solvent-based recycling approaches offer an effective means of recovering high-quality plastic materials from waste by the use of a solvent to selectively dissolve the plastic waste and recover specific polymers. In this work, we report on the properties of 9587 potential glycerol-based solvents that can be synthesized from biomass-derived glycerol. We predict the density and dipole moment using quantum mechanical calculations, while LogS, LogP, and melting point are predicted using machine learning that outperforms other prediction methods such as Hansen Solubility Parameters in Practice (HSPiP). Additionally, we analyze the ability of the solvents to dissolve common plastic materials [polyethylene (PE), poly(ethylene terephthalate) (PET), poly(ether sulfone) (PES), polypropylene (PP), polystyrene (PS), and poly(vinyl chloride) (PVC)] based on a comparison of their Hansen solubility parameters (HSPs). Our results show that functionalization of glycerol can significantly alter its properties, and based on the HSPs and melting point, we recommend selective solvents for PE, PET, and PVC, while for PES, PP, and PS, we suggest using a combination of solvents in a solvent/antisolvent setup for solvent-based plastic waste recycling. Finally, based on stricter solvent selection criteria, we also propose a strategy that may help reduce the costs of sorting waste plastic whereby the waste feedstock is first separated into polar and nonpolar fractions.
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