Experimental Investigation into Waterproofing Performance of Cement Mortar Incorporating Nano Silicon
Bibliographic record
Abstract
Water ingress and penetration of aggressive fluids undermines the integrity of many concrete structures. For this reason, optimal performance of such structures up to their designed life cannot be guaranteed. This study introduces nano silicon as an alternative waterproofing admixture for increasing life span of cementitious materials, due to its non-vulnerability to deterioration, which is common to traditional surface coating solutions. Therefore, nano silicon was characterized using Field Emission Scanning Electron Microscope (FESEM), Energy Dispersion Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and surface Zeta potential. The Central Composite Design (CCD) tool was adopted to plan the experiment and further used to model the relationship between experimental variables and experimental response. The model was found to be nonlinear quadratic based on Analysis of Variance (ANOVA). Also, the validity of the model was evaluated and found to have accurate prediction with mean absolute percentage error (MAPE) of 1.62%. The optimum mix ratio necessary to increase resistance to capillary water absorption was established at a nano silicon dosage of 6.6% by weight of cement and w/c of 0.42. In conclusion, the overall results indicate that resistance to capillary water absorption was increased by 62%. Furthermore, while gas permeability was reduced by 31%, on the other hand, volume of water permeable voids decreased by 10%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".