Performance improvement of nanocolloidal silica-aluminate cement composite grouting materials with organic acids
Source abstract
Abstract
The combination of nanocolloidal silica and aluminate cement is a potential technical approach to solve the problem of mudstone grouting, but there is a lack of high-performance admixtures to improve early strength and gel time. The effects of three common organic acids, citric acid, tartaric acid and malic acid, on the properties of the composite slurry were explored. Meanwhile, the influence of citric acid on the fluidity and microstructure characteristics of the composite slurry was deeply analysed. Finally, the key engineering properties such as injectability and reinforcement of composite slurry were explored. The main conclusions were as follows: the citric acids had a significant beneficial effect on the compressive strength and gel time. After the addition of 4% citric acid, the consolidation rate of the composite slurry was 92.68%, the compressive strength was 39.22 MPa, the consolidation rate and compressive strength were at high levels, and the gel time was 90~110 min. The main reasons for the excellent strength performance were the dense microstructure, CAH10 and C2AH8 hydrates and 98.68% of pores having pore sizes less than 20 nm. The composite slurry can be injected in the rock with average pore throat diameter of 15.14 μm. The hydration products could be better combined with mudstone, the rock softening zone was smaller than that of ordinary Portland cement, and the composite slurry could reduce the softening phenomenon of mudstone. The findings of this work could provide guidelines for the development of high-performance grouting materials and solving the reinforcement problem of mudstone.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Grouting, Rheology, and Soil Mechanics · Concrete and Cement Materials Research · Microbial Applications in Construction Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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