Towards net-zero emission: A case study investigating sustainability potential of geopolymer concrete with recycled glass powder and gold mine tailings
Why this work is in the frame
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Bibliographic record
Abstract
This study explores the feasibility of utilizing waste materials, specifically glass powder (GP) and gold mine tailings (MT), as eco-friendly, net-zero emission alternatives in geopolymer concrete production. The optimal material proportions that yield maximum compressive strength are identified using response surface methodology. The optimized concrete mixtures are comprehensively evaluated for three core attributes; namely, fresh-state properties, such as workability and air content; mechanical characteristics, including compressive, flexural, and splitting tensile strengths; and long-term durability, assessed by freeze-thaw resistance and chloride permeability. In the evaluation of fresh-state properties, it was observed that GP improved workability, whereas MT had a decreasing effect due to its increased fineness and greater surface area. The study also revealed that the combined addition of GP and MT notably increased compressive strength by up to 25%, despite the addition of GP alone slightly reducing the mechanical properties. While these waste materials positively influenced flexural and splitting tensile strengths, the impact was less significant compared to that on compressive strength. Furthermore, in critical durability tests that involve 300 freeze-thaw cycles and rapid chloride permeability assessments, mixtures that contain GP and MT exceeded standard benchmarks. The results indicate that the incorporation of GP and MT together not only enhances mechanical properties but also improves durability. These results demonstrate the potential application of GP and MT as sustainable substitutes in concrete production.
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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 | 0.000 | 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 it