Current state of K-based geopolymer cements cured at ambient temperature
Bibliographic record
Abstract
The increasing focus on global climate change, the public and consumer preferences for “green” products and the associated markets in carbon credits have promoted the use of alternate cements in place of pure Portland cement binders. Using alkali activation method, waste materials such as fly ash and slag can be modified to replace ordinary Portland cement. In the present study, a combination of sodium hydroxide pellets and sodium silicate solution is used for the alkali activation of fly ash to prepare geopolymer cement. In the same way, a mixture of KOH (pellets) and K-silicate solution has been used with fly ash and slag (used in British Columbia, Canada) for comparison. Ambient temperature curing has been considered in addition to oven curing. Compressive strength tests indicate that both duration and intensity of the temperature affect the properties of the geopolymer. Higher intensity of the temperature accelerates the polymerization process much faster and gives higher compressive strength for the same duration of curing. On the other hand, longer duration of curing leads to improved hardened properties compared to shorter span at the same intensity. This paper presents data for curing done at ambient temperatures and the effectiveness of using potassium- and sodium-based solutions for geopolymer cement. Further recommendations for future work are also included.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".