A Review on the Effect of Chemical and Physical Properties of Glass Powder Towards the Concrete Performance
Bibliographic record
Abstract
The escalating demand for construction materials and the concurrent increase in glass waste pose significant environmental challenges globally.This review synthesizes existing literature on the utilization of glass powder (GP) as a partial substitute for cement or sand in concrete, aiming to establish key determinants for optimizing its integration and enhancing concrete properties.Through a systematic analysis of various studies, it was found that the replacement ratio, GP particle size, water-to-cement (W/C) ratio, and curing time significantly influence concrete's mechanical performance, including compressive, flexural, and split tensile strengths.Notably, a 20% replacement ratio generally yielded optimal results, with cement replacement often outperforming sand replacement.Finer GP particles (typically <2.36 mm) were more effective due to enhanced pozzolanic reactions, which improved strength and filled voids, although excessive fineness could lead to cracks.Increased curing time consistently improved strength, while GP type and specific gravity influenced concrete density.This study proposes preliminary determinants for effectively recycling higher quantities of glass waste into concrete, offering practical guidance for sustainable construction practices and mitigating environmental impact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".