An alternative to NaOH in the alkali-activation of ground granulated blast furnace slag in the formulation of cemented paste backfills
Bibliographic record
Abstract
In the mining district of the Abitibi region (Canada), several underground mines use cemented paste backfill (CPB) for ground support. The binder typically used is a blend of 20% general use Portland cement (GU) and 80% ground granulated blast furnace slag (GGBFS), and qualified as the reference binder (RB). Using the RB always allows CPB to achieve the unconfined compressive strengths (UCSs) targets required. Due to its relatively high price, limited GGBFS availability and the high carbon footprint attributable to GU manufacturing, the search for alternative binders becomes imperative. Alkali-activated binders (AABs) made of GGBFS, and type F fly ash (FAF) activated using NaOH, were tested at the laboratory scale. This activation process achieved similar UCSs of CPB prepared with the RB. Unfortunately, the economic and environmental assessment of these AABs suffers from the high costs of NaOH, its high carbon footprint and GGBFS dosage, which is still significant. Consequently, the industrial application of these AABs in mine backfilling becomes challenging. The proposed alternative to NaOH consists of using circulating dry scrubber dusts (CDSD) from the desulfurisation process of Rio Tinto Iron and Titanium operations at Sorel-Tracy (Quebec, Canada). This byproduct was successfully tested in a CPB formulation. Moreover, FAF and fine glass powder (FGP) are proposed as partial replacement to GGBFS. The results show that at 28 days the UCS values of CPB prepared with the GGBFS/CDSD mixtures are comparable to the ones of the RB. At 7 days, satisfactory UCS are obtained and can reach the same UCS of the CPB prepared with the RB by adding only 5% clinker to the GGBFS/CDSD mixture. In addition, several mixtures have shown comparable and even higher UCSs to the RB with lower costs and smaller carbon footprints (CO2eq). The results are promising and encouraging for a future industrial application.
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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".