Effect of alkali activator dosage on compressive and tensile strength of ground granulated blast furnace slag based geopolymer concrete
Bibliographic record
Abstract
Use of ordinary portland cement contributes to environmental deterioration by releasing enormous quantities of CO2. To reduce use of cement, this research focuses on preparation of solely ground granulated blast-furnace-slag-based geopolymer binder, activated by a combination of sodium hydroxide and sodium metasilicate cured under ambient temperature at 27 °C. Engineering properties of geopolymer binder are evaluated and compared with conventional cement to assess its suitability as a binder for making geopolymer concrete. Compressive strength, flexure strength, and split tensile strength are determined for geopolymer concrete. Microstructural analysis of geopolymer is performed by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM) with energy dispersive X-ray analysis (EDAX), and Fourier-transform infrared spectroscopy (FTIR) tests. The concentration of alkali activators is optimized by laboratory trials and maximum compressive, flexural, and split tensile strengths of 44.07, 5.60, and 4.39 MPa, respectively, are obtained for geopolymer concrete at 2 mol/L concentration of sodium hydroxide solution with the ratio of sodium metasilicate to sodium hydroxide taken as 2.0.
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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 | 0.000 | 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) | 0.001 | 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 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".