Impacts of Nickel Nanoparticles on Mineral Carbonation
Bibliographic record
Abstract
This work presents experimental results regarding the use of pure nickel nanoparticles (NiNP) as a mineral carbonation additive. The aim was to confirm if the catalytic effect of NiNP, which has been reported to increase the dissolution of CO₂ and the dissociation of carbonic acid in water, is capable of accelerating mineral carbonation processes. The impacts of NiNP on the CO₂ mineralization by four alkaline materials (pure CaO and MgO, and AOD and CC steelmaking slags), on the product mineralogy, on the particle size distribution, and on the morphology of resulting materials were investigated. NiNP-containing solution was found to reach more acidic pH values upon CO₂ bubbling, confirming a higher quantity of bicarbonate ions. This effect resulted in acceleration of mineral carbonation in the first fifteen minutes of reaction time when NiNP was present. After this initial stage, however, no benefit of NiNP addition was seen, resulting in very similar carbonation extents after one hour of reaction time. It was also found that increasing solids content decreased the benefit of NiNP, even in the early stages. These results suggest that NiNP has little contribution to mineral carbonation processes when the dissolution of alkaline earth metals is rate limiting.
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How this classification was reachedexpand
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) | 0.002 | 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 teacher head, 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".