Improvements in the Engineering Properties of Cementitious Composites Using Nano-Sized Cement and Nano-Sized Additives - Rahman, Ibadur; Singh, Priyanka; Dev, Nirendra; Arif, Mohammed; Yusufi, Faiz Noor Khan; Azam, Ameer; Alam, M. Masroor; Singh, Sandeep; Chohan, Jasgurpreet Singh; Kumar, Raman; Sharma, Lovneesh; Tag-Eldin, Elsayed; et al. (Materials, 2022)
The findings of an extensive experimental research study on the usage of nano-sized cement powder and other additives combined to form cement–fine-aggregate matrices are discussed in this work. In the laboratory, dry and wet methods were used to create nano-sized cements. The influence of these nano-sized cements, nano-silica fumes, and nano-fly ash in different proportions was studied to the evaluate the engineering properties of the cement–fine-aggregate matrices concerning normal-sized, commercially available cement. The composites produced with modified cement–fine-aggregate matrices were subjected to microscopic-scale analyses using a petrographic microscope, a Scanning Electron Microscope (SEM), and a Transmission Electron Microscope (TEM). These studies unravelled the placement and behaviour of additives in controlling the engineering properties of the mix. The test results indicated that nano-cement and nano-sized particles improved the engineering properties of the hardened cement matrix. The wet-ground nano-cement showed the best result, 40 MPa 28th-day compressive strength, without mixing any additive compared with ordinary and dry-ground cements. The mix containing 50:50 normal and wet-ground cement exhibited 37.20 MPa 28th-day compressive strength. All other mixes with nano-sized dry cement, silica fume, and fly ash with different permutations and combinations gave better results than the normal-cement–fine-aggregate mix. The petrographic studies and the Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) analyses further validated the above findings. Statistical analyses and techniques such as correlation and stepwise multiple regression analysis were conducted to compose a predictive equation to calculate the 28th-day compressive strength. In addition to these methods, a repeated measures Analysis of Variance (ANOVA) was also implemented to analyse the statistically significant differences among three differently timed strength readings.