Issue 3, 2018, Issue in Progress

Dissolution of epoxy thermosets via mild alcoholysis: the mechanism and kinetics study

Abstract

Thermoset dissolution based on degradable bond or exchange reaction has been recently utilized to achieve thermosetting polymer dissolution and recycling. In this paper, an industrial grade epoxy thermoset was utilized as a model system to demonstrate the thermoset dissolution via solvent assisted transesterification (or alcoholysis) with high efficiency under mild conditions. The anhydride–cured epoxy thermoset was depolymerized by selective ester bond cleavage in 1,5,7-triazabicyclo[4,4,0]dec-5-ene (TBD)–alcohol solution below 180 °C at ordinary pressure in less than two hours. The epoxy dissolution proceeded in a surface erosion mode via transesterification that was coupled with catalyst–alcohol diffusion. Based on this observation, a surface layer model containing three layers, namely the gel layer, solid swollen layer and pure polymer layer was used to analyze the thermoset dissolution kinetics. The epoxy dissolution kinetics was derived from the surface layer model, which could be used to predict the dissolution rate during the diffusion-rate-controlled dissolution process well. The results show that alcohols with larger diffusivity and better solubility lead to a higher alcohol/catalyst concentration in the gel layer and promote faster erosion and dissolution of epoxy. This is the first work to show that it is possible to depolymerize industrial epoxy using the principle of dynamic bonds with fast dissolution rate at mild temperature under ordinary pressure.

Graphical abstract: Dissolution of epoxy thermosets via mild alcoholysis: the mechanism and kinetics study

Supplementary files

Article information

Article type
Paper
Submitted
26 Nov 2017
Accepted
22 Dec 2017
First published
04 Jan 2018
This article is Open Access
Creative Commons BY license

RSC Adv., 2018,8, 1493-1502

Dissolution of epoxy thermosets via mild alcoholysis: the mechanism and kinetics study

X. Kuang, Q. Shi, Y. Zhou, Z. Zhao, T. Wang and H. J. Qi, RSC Adv., 2018, 8, 1493 DOI: 10.1039/C7RA12787A

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