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Influence of water-to-binder ratio on the optimum percentage of nano-TiO2 addition in terms of compressive strength of mortars: A laboratory and virtual experimental study based on ANN model
Carlos Moro (1), Hala El Fil, Vito Francioso, Mirian Velay-Lizancos - Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
Porosity; Hydration products; Water-to-binder ratio; Compressive strength; Artificial neuron network; TiO2 nanoparticles; Mortar
This research aims to study the effect of water-to-binder ratio (w/b) as a potential key factor that changes the optimum percentage of nano-TiO2 addition in terms of compressive strength of mortars. Data from previous literature were collected and analyzed. An artificial neuron network (ANN) model was trained and validated to predict the compressive strength of mortars as a function of the level of nano-TiO2, w/b, cement content, aggregate-to-binder ratio, and age. Then, a virtual experimental campaign evaluating 45,015 case scenarios, and using the ANN model, was performed to study the effect of the w/b on the optimum percentage of nano-TiO2. Results suggest that the higher the w/b and the lower the age, the higher the optimum percentage of nano-TiO2. Laboratory experimental compressive strength results are in agreement with these trends. Thermogravimetric analysis and 3D X-Ray scans show that the use of nano-TiO2 presents a double positive effect on compressive strength, reducing the porosity and increasing the hydration product content when the initial porosity of the reference cement paste is high (due to high w/b). However, when the porosity of reference samples is very low (due to low w/b), the use of nano-TiO2 may lead to a reduction of hydration products content due to the lack of space for the CH to grow. Since the initial porosity was already very low, the porosity reduction due to the use of nano-TiO2 would not be enough to overcome the negative effect on hydration. Therefore, it may lead to a decrease in the compressive strength of mortars. These results explain the dependence of the optimum percentage of nano-TiO2 on w/b and age.
Dragonfly was used to analyze 3D X-Ray scans.
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