Chemoorganotrophic Bioleaching of Olivine for Nickel Recovery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bioleaching of olivine, a natural nickel-containing magnesium-iron-silicate, was conducted by applying chemoorganotrophic bacteria and fungi. The tested fungus, Aspergillus niger, leached substantially more nickel from olivine than the tested bacterium, Paenibacillus mucilaginosus. Aspergillus niger also outperformed two other fungal species: Humicola grisae and Penicillium chrysogenum. Contrary to traditional acid leaching, the microorganisms leached nickel preferentially over magnesium and iron. An average selectivity factor of 2.2 was achieved for nickel compared to iron. The impact of ultrasonic conditioning on bioleaching was also tested, and it was found to substantially increase nickel extraction by A. niger. This is credited to an enhancement in the fungal growth rate, to the promotion of particle degradation, and to the detachment of the stagnant biofilm around the particles. Furthermore, ultrasonic conditioning enhanced the selectivity of A. niger for nickel over iron to a value of 3.5. Pre-carbonating the olivine mineral, to enhance mineral liberation and change metal speciation, was also attempted, but did not result in improvement as a consequence of the mild pH of chemoorganotrophic bioleaching.
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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 | 0.000 | 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) | 0.000 | 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 it