Dataset Information

Vitrimerization of Crosslinked Unsaturated Polyester Resins: A Mechanochemical Approach to Recycle and Reprocess Thermosets.

ABSTRACT: Unsaturated polyester resins (UPRs) are expansively used in different applications and recycling the significant amounts of UPR waste is still a universal problem. Vitrimerization is a feasible, environmental-friendly, cost effective, and operative method, which can be used for recycling the crosslinked UPRs. In this method, the thermoset permanent network is changed into a dynamic network similar to the vitrimer-type polymers. The results show that the existence of a transesterification catalyst in the system significantly enhances the efficiency of vitrimerization. The vitrimerized UPR thermosets can be reprocessed three times with mechanical properties comparable to the initial UPR. The results show that the excess of external hydroxyl groups in the system can prevent the formation of zinc ligand complexes in the network and consequently reduce the crosslinked density and mechanical properties of vitrimerized samples. The vitrimerized thermoset powder can be reprocessed through injection molding, extrusion, and compression molding which are conventional thermoplastic processing techniques. The unrecyclable UPR thermoset wastes can be recycled and reused through vitrimerization with the least loss in mechanical properties.

SUBMITTER: Bandegi A

PROVIDER: S-EPMC9284659 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Vitrimerization of Crosslinked Unsaturated Polyester Resins: A Mechanochemical Approach to Recycle and Reprocess Thermosets.

Bandegi Alireza A Amirkhosravi Mehrad M Meng Haotian H Aghjeh Mir Karim Razavi MKR Manas-Zloczower Ica I

Global challenges (Hoboken, NJ) 20220428 7

Unsaturated polyester resins (UPRs) are expansively used in different applications and recycling the significant amounts of UPR waste is still a universal problem. Vitrimerization is a feasible, environmental-friendly, cost effective, and operative method, which can be used for recycling the crosslinked UPRs. In this method, the thermoset permanent network is changed into a dynamic network similar to the vitrimer-type polymers. The results show that the existence of a transesterification catalys ...[more]

PMID: 35860393

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Project description:Unsaturated polyester resins are widely used for the preparation of composite materials and fulfill the majority of practical requirements for industrial and domestic applications at low cost. These resins consist of a highly viscous polyester oligomer and a reactive diluent, which allows its process ability and its crosslinking. The viscosity of the initial polyester and the reactive diluent mixture is critical for practical applications. So far, these viscosities were determined by trial and error which implies a time-consuming succession of manipulations, to achieve the targeted viscosities. In this work, we developed a strategy for predicting the viscosities of unsaturated polyesters formulation based on neural networks. In a first step 15 unsaturated polyesters have been synthesized through high-temperature polycondensation using usual monomers. Experimental Hansen solubility parameters (HSP) were determined from solubility experiment with HSPiP software and glass transition temperatures (T g ) were measured by Differential Scanning Calorimetry (DSC). Quantitative Structure-Property Relationship (QSPR) coupled to multiple linear regressions have been used to get a prediction of Hansen solubility parameters δd, δ p , and δ h from structural composition. A second QSPR regression has been done on glass transition temperature (prediction vs. experimental coefficient of determination R 2 = 0.93) of these unsaturated polyesters. These unsaturated polyesters were next diluted in several solvents with different natures (ethers, esters, alcohol, aromatics for example) at different concentrations. Viscosities at room temperature of these polyesters in solution were finally measured in order to create a database of 220 entries with 7 descriptors (polyester molecular weight, T g , dispersity index Ð, polyester-solvent HSP RED, molar volume of the solvent, δ h of the solvent, concentration of polyester in solvent). The QSPR method for predicting the viscosity from these 6 descriptors proved to be ineffective (R 2 = 0.56) as viscosities exhibit non-linear phenomena. A Neural Network with an optimized number of 12 hidden neurons has been trained with 179 entries to predict the viscosity. A correlation between experimental and predicted viscosities based on 41 testing instances gave a correlation coefficient R 2 of 0.88 and a predicted vs. measured slope of 0.98. Thanks to Neural Networks, new developments with eco-friendly reactive diluents can be accelerated.

Dataset Information

Vitrimerization of Crosslinked Unsaturated Polyester Resins: A Mechanochemical Approach to Recycle and Reprocess Thermosets.

Publications

Vitrimerization of Crosslinked Unsaturated Polyester Resins: A Mechanochemical Approach to Recycle and Reprocess Thermosets.

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