Bibliographic record
Abstract
Current practices for handling the nickeliferous pyrrhotite (Pyrr) tailings in Sudbury, Canada, pose the risk of Acid Mine Drainage (AMD) and incur significant costs for the mining companies to construct and manage the tailing impoundments. Meanwhile, there is a rising demand for electric vehicles, and consequently for the nickel which is used for making the Li-ion battery cathodes. The nickeliferous Pyrr tailings in the Sudbury region are increasingly recognized as a promising source of nickel. Thus, this study was undertaken to reduce the negative environmental impact of the Sudbury Pyrr tailings and to extract their nickel value by a thermal upgrading process.The thermodynamics for the Fe–X–S system in which X represents Ni, Co or Cu were evaluated with the aid of FactSageTM 7.3 [1]. The thermal upgrading process using metallic iron as the iron source was assessed, and the effects of the iron addition rate and temperature were examined. The reaction kinetics of iron sulfidization by Pyrr were found to follow a parabolic law, which indicates that the rate-controlling step is the diffusion of Fe cations within the newly formed sulfide. Three mechanisms of the ferronickel alloy formation resulting from the interaction between the metallic iron and the nickeliferous Pyrr were identified: (i) direct precipitation of the alloy particles from the original Pyrr; (ii) cross-diffusion of Fe and Ni cations within the newly formed Pyrr, which results in the precipitation of the alloy; and (iii) diffusion of Ni from the original Pyrr into the unreacted metallic iron. The mg-scale samples were heat treated using a thermogravimetric analysis (TGA) furnace under different conditions. The following variables which affect the extraction of nickel were identified: temperature, H_2 as the gaseous reductant, and addition of iron-containing materials either metallic iron or iron oxides together with a solid reductant. The thermal treatment tests were performed by mixing the nickeliferous Pyrr concentrate (assaying 1.59 wt.% Ni) with varying amounts of metallic iron or iron oxides (in the form of calcined Pyrr or commercial-grade iron ore fines) together with a carbonaceous material, pressed into briquettes, and then heat heated under different conditions. The results showed that the thermal treatment of briquettes followed by magnetic separation could recover >95% of the total Ni into a magnetic product assaying >4.0 wt% Ni. Additional benefits resulting from the thermal upgrading process included: (i) a high recovery of Co, i.e., >80% of the total Co is recovered to the magnetic product; and (ii) a high rate of sulfur rejection (>75% of the total sulfur) to the non-magnetic tails. The materials and energy balance calculations for the thermal upgrading process in which the iron ore fines are used as iron source were carried out for a hypothetical Rotary Hearth Furnace (RHF). The consumption of natural gas and the amount of energy produced in the form of high-pressure hot steam were estimated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".