Evaluation of the Performance of Low-Cement Strain-Hardening Cementitious Composites Containing Desert Sand and Ground Scoria Rocks

Materials (Basel). 2023 Aug 29;16(17):5896. doi: 10.3390/ma16175896.

Abstract

Fine aggregates are the main ingredients that control the success of the preparation and performance of strain-hardening cementitious composites (SHCCs). Worldwide deserts can be used as eternal sources of fine aggregates for the preparation of SHCCs. Arabian Peninsula desert sand spreads over the largest desert area in the world, covering an area of 2,300,000 km2 among the Arabian Gulf countries. White and dune desert sands were procured for use in this study. The morphological structure is important in selecting the appropriate sand for use in the preparation of SHCCs. The utilization of microfibers such as polyvinyl alcohol (PVA) has become common practice for the preparation of SHCCs. The presence of desert sand is proven to enhance the dispersibility of PVA due to its spherical structure, which alleviates the friction among the ingredients forming SHCCs. Two mechanisms are defined under the tensile force at the interface of microfibers and natural sand, namely, a strong frictional force leading to rupture or a weaker force causing pullout. The synergy between fibers and fine aggregate grains depends on their surface characteristics, which can be modified using different types of mineral admixtures. In this research, the alignment of microfibers as an indication of the quality of dispersion could be evaluated using a proposed approach based on an advanced technique of microstructural analysis. PVA dispersion and its relation to strain-hardening properties are visually correlated to the surface interaction of the mineral admixture and dune sand. The microdurability and cost effectiveness of SHCCs could be assessed using the proposed approach, as depicted by the results obtained in this research work.

Keywords: BSE microstructure-based technique of analysis; PVA microfibers; desert sands; strain-hardening properties.

Grants and funding

This research was funded by King Saud University, grant number RSPD2023R692.