Impact Resistance Enhancement of Sustainable Geopolymer Composites Using High Volume Tile Ceramic Wastes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The need for sustainable concrete with low carbon dioxide emissions and exceptional performance has recently increased in the building industry. Many distinct types of industrial byproducts and ecologically safe wastes have shown promise as ingredients for this kind of concrete. Meanwhile, as industrialization and lifestyle modernization continue to rise, ceramic waste becomes an increasingly serious threat to the natural environment. It is well known that free cement binder that incorporates tile ceramic wastes (TCWs) can significantly improve the material’s sustainability. We used this information to create a variety of geopolymer mortars by mixing TCWs with varied proportions of ground blast furnace slag (GBFS) and fly ash (FA). Analytical techniques were used to evaluate the mechanical properties and impact resistance (IR) of each designed mixture. TCWs were substituted for binders at percentages between 50 and 70 percent, and the resultant mixes were strong enough for real-world usage. Evidence suggests that the IR and ductility of the proposed mortars might be greatly improved by the addition of TCWs to a geopolymer matrix. It was found that there is a trend for both initial and failure impact energy to increase with increasing TCWs and FA content in the matrix. The results show that the raising of TCWs from 0% to 50, 60 and 70% significantly led to an increase in the failure impact energy from 397.3 J to 456.8, 496.6 and 595.9 J, respectively.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it