Improved Platinum‐Group Element Extraction by NiS Fire Assay from Chromitite Ore Samples Using a Flux Containing Sodium Metaphosphate
Bibliographic record
Abstract
Many chromite‐rich rocks contain relatively high concentrations of the platinum‐group elements (PGE). In many cases, the phases carrying PGE occur as either platinum‐group minerals (PGM) or as base metal sulfides in solid solution in sulfides. In some cases, such as the UG‐2 unit of the Bushveld Complex, the PGM are occluded inside chromite grains. Chromites are notably difficult to dissolve in most fluxes and if the chromite contains some PGM the possibility exists that not all the PGE will be recovered during fusion. In this work, shortcomings in published methods of analysis based on the nickel sulfide fire assay procedure were investigated and a new procedure developed based on the addition of sodium metaphosphate to the fusion mixture. Optimum composition of the fusion mixture was found to be 10 g sodium metaphosphate and 9 g silica to 10 g sample, 15 g sodium carbonate, 30 g lithium tetraborate, 7.5 g nickel and 4.5 g sulfur to achieve complete dissolution of chromite grains. The new flux mixture was evaluated by the analysis of reference material CHR‐Pt+ (which is known to contain PGM inside chromite grains) and no undissolved chromite grains were found in the glassy slag. Analysis of the nickel sulfide beads from this fire assay using neutron activation analysis showed similar results for Rh and Ru when compared with published conventional true (or accepted) values, while Au, Ir, Os, Pd and Pt values determined here were 10 to 30% higher than the corresponding published conventional true values. It was concluded that the addition of sodium metaphosphate improved chromite dissolution in the flux and appears to improve PGE recovery.
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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".