The Recovery and Concentration of Spodumene Using Dense Media Separation
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
In coming years, global lithium production is expected to increase as the result of widespread electric vehicle adoption. To meet the expected increase in demand, lithium must be sourced from both brine and hard-rock deposits. Heavy liquid separation (HLS) and dense media separation (DMS) tests were conducted on the pegmatites from Hidden Lake, NWT, Canada to demonstrate the potential role of this technology in the concentration of spodumene (LiAlSi2O6) from hard-rock sources. A continuously operated DMS circuit test, conducted on +840 µm material, produced a concentrate grading 6.11% Li2O with ~50% lithium recovery. The circuit rejected 50% of the original mass to tailings, with only 8% lithium losses. Sensitivity analysis showed that minor changes (+/−0.05) in the DMS-specific gravity cut point resulted in significant changes to the mass rejected and to the concentrate grade produced; this may limit the feasibility and operability of the downstream grinding and flotation circuits. The results demonstrate the potential for DMS in the concentration of spodumene from the Hidden Lake pegmatites, and by extension, the potential for DMS in the concentration of spodumene from other hard-rock occurrences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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