Principal component analysis approach to dispersed graphene oxide decorated with sodium dodecyl sulfate cement pastes
| Autor: | Özge Bildi Ceran, Barış Şimşek, Tayfun Uygunoğlu, Semahat Doruk |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Cement
Materials science Calcium hydroxide Absorption of water 0211 other engineering and technologies Oxide 02 engineering and technology Building and Construction Nanomaterials chemistry.chemical_compound chemistry Chemical engineering Mechanics of Materials 021105 building & construction Architecture Zeta potential 021108 energy Sodium dodecyl sulfate Safety Risk Reliability and Quality Dispersion (chemistry) Civil and Structural Engineering |
| Zdroj: | Journal of Building Engineering. 38:102234 |
| ISSN: | 2352-7102 |
| DOI: | 10.1016/j.jobe.2021.102234 |
| Popis: | Although researchers have investigated the properties of nanomaterials in cement paste, the relationship between cement paste properties and dispersion properties is not yet understood. Understanding dispersion properties may reveal how nanomaterials changes cement paste properties. In this study, Taguchi-based principal component analysis (PCA) was used to uncover the mechanism of interaction between dispersion and cement paste properties. Using graphene oxide (GO) with smaller particles, higher zeta potential of dispersion, and higher sodium dodecyl sulfate levels led to greater splitting tensile strength, ultrasonic pulse velocity, and hydration rate and lower thermal conductivity, electrical resistance, porosity, and percentage of water absorption. Optimum sodium dodecyl sulfate usage significantly improves the mechanical properties and degree of hydration due to hydrophobic association. A significant improvement in thermal conductivity, calcium hydroxide content, and porosities of 21.33%, 13.88%, and 10.21% was achieved in the cement pastes using a 0.1% GO and a 0.1% sodium dodecyl sulfate by weight instead of cement. The dispersion properties significantly affect the properties of cement pastes, which accounts for 97% of product variability. |
| Databáze: | OpenAIRE |
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