Impact of nano ZnO particles on the characteristics of the cement mortar

In practice, it is very common to estimate the strength of concrete by destructive or by partial non-destructive testing on concrete. However, it is a very challenging task to estimate the correct value of the strength of concrete or cement as it is depending on various factors. The present research work is focussed on the impact of zinc oxide (ZnO) nano-particles on the compressive strength of the cement mortar. To investigate the modified compressive strength of the mortar incorporated with ZnO nano-particles, four different types of mixes were prepared with 0%, 0.25%, 0.5%, and 0.75% of the ZnO nanoparticle by the weight cement, respectively. Experimental results show the enhancement in compressive strength up to 0.5%, later on, strength is slightly decreased. By considering the experimental results of cement strength, three different models are proposed to predict the strength of cement mortar as analysis of covariance (ANCOVA), neural network (NN), and principal component regression (PCR). These models also validate the results of experimentation by showing the optimum results at 0.5% of the addition of ZnO nano-particles. These models are trained and tested in excel programming for thirty-six standard cement specimens. At the end of the work, each model is compared with others. Out of three models, the NN model can predict the reliable results for the compressive strength. However, the PCR model is in second place after the NN model though its value of R-2 is lesser than the ANCOVA model. PCR gives less residue as compared to ANCOVA. For the prediction of the strength of mortar, ANCOVA is not so significant as compared to the other two models due to the residuals of ANCOVA models are the largest value, though its R-2 value is more than the PCR model.