journal article·2023-12Open access

Alkali resistance of selected waste fibres to model cement environment

Branka Mrduljaš, Ana Baričević, Irina Pucić, Ivana Carević, Katarina Didulica

Abstract

Synthetic fibres are often used to reinforce cementitious composites. However, their production has significant negative environmental impact. An ecological alternative could be to use waste fibre if their properties are found to be satisfactory. Therefore, the main objective of this study was to determine if selected waste fibres could withstand an aggressive and highly alkaline environment of cementitious composites. Three types of production waste fibres (alkali-resistant glass fibres, AR-GF, basalt fibres, BF and carbon fibres, CF and recycled tyre polymer fibres RTPF) were exposed to a synthetic pore solution simulating the cement matrix condition for 90 days. The mechanical properties of the production waste fibres and the morphology determined by scanning electron microscopy were the best predictors of fibre resistance. The sizing of the treated production waste fibres partially (CF) or completely (AR-GF, BF) decomposed. The pronounced deterioration of the BF structure was accompanied by a complete deterioration of the mechanical properties. A slight deterioration of mechanical properties was also observed in CF and to an even greater extent in AR-GF. The RTPFs were too short for mechanical measurements, so a combination of Fourier transform infrared spectroscopy and thermal analysis was required to evaluate effects of exposure to synthetic pore solution. The retained properties of treated RTPF seemed to be at least equivalent to those of AR-GF. Overall, the alkaline resistance of all studied waste and recycled tyre polymer fibres appears to be sufficient to restrain early age deformation of cementitious composite.
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Research context

OpenAlex topics: Innovative concrete reinforcement materials · Recycled Aggregate Concrete Performance · Concrete and Cement Materials Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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