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Articles

Microcapsule synthesis and evaluation on fatigue and healing of microcapsule-based asphalt by the entropy and TOPSIS method

, , , &
Pages 4610-4621 | Received 13 May 2021, Accepted 10 Aug 2021, Published online: 27 Aug 2021
 

ABSTRACT

Encapsulation is a promising approach to enhance the self-healing ability of asphalt materials. In this study, microcapsules encapsulated waste engine oil was synthesised to improve the self-healing ability of asphalt. The factors affecting the synthesis of microcapsules, especially emulsification and core shell ratio, were investigated through a micro-observation. Dynamic mechanical properties of microcapsule-based asphalts were analysed. Fatigue and healing properties of asphalt binder were evaluated using the entropy and TOPSIS method. Results showed that a combination of sodium dodecyl sulphate and Span-60 showed better emulsification and the optimised dosage of emulsifier was 1.5 wt%. Increasing emulsifying speed, or decreasing core shell ratio, improved encapsulation efficiency. Addition of microcapsules decreased the asphalt stiffness at low frequency and the fatigue resistance of microcapsule-based asphalt went through relatively large decay when microcapsule addition exceeded 4 wt%. Three healing indexes increased with the addition of microcapsules. By entropy weight and the Technique for Order Preference by Similarity to an Ideal Solution analysis, healing index relating to fatigue life shows a larger entropy weight than others and asphalt with 2 wt% microcapsules perform better with respect to fatigue and healing properties.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data generated or analysed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: https://authorservices.taylorandfrancis.com/data-sharing-policies/repositories/.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [Grant Number 51978073].

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