Carbothermal Reductive Upgrading of a Bauxite Ore Using Microwave Radiation
Bibliographic record
Abstract
Abstract The utilization of microwave radiation as the energy source for the carbothermal reductive upgrading of a bauxite ore was investigated. The bauxite ore was mechanically mixed with carbon and reacted in a quartz crucible in a multimode cavity. The iron oxide in the bauxite ore was reduced to magnetite and/or iron and the magnetic fraction was separated using a Davis Tube Tester. Three experimental arrangements were utilized: (i) microwaving of the mixture, (ii) microwaving of the mixture plus charcoal layers under ambient conditions and (iii) microwaving of the mixture plus charcoal layers in argon. The utilization of the charcoal layers resulted in more uniform heating of the sample. The effects of irradiation time, sample mass and incident power on the mass of the magnetic fraction were determined. Both the iron and the aluminum contents of the magnetic fraction were measured and using these values, the iron removal from the bauxite ore and the alumina recovery in the non-magnetic fraction were calculated. It was shown that under mildly reducing conditions, almost half of the iron could be removed as magnetite. However, the formation of hercynite limited the iron separation as magnetite and higher iron removals could only be achieved through the formation of metallic iron under more highly reducing conditions.
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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".