The behavior of noble-metal admixtures during fractional crystallization of As- and Co-containing Cu–Fe–Ni sulfide melts
Bibliographic record
Abstract
Abstract To study the behavior of macrocomponents and admixtures during the fractional crystallization of sulfide melts and the influence of As on noble metals in this process, we performed a quasi-equilibrium directional crystallization of melt of composition (at.%): Fe—35.5, Ni—4.9, Cu—10.4, and S—48.3, with admixtures of Pt, Pd, Rh, Ru, Ir, Au, Ag, As, and Co (each 0.1 at.%), which imitates the average (by Cu contents) compositions of massive ores at the Noril’sk Cu-Ni deposits. The following sequence of phase formation from melt has been established: mss (zone I) / mss + iss (zone II) / iss (zone III) (mss is (FezNi1–z)S1+δ, iss is (FexCuyNi1–x–y)zS1–z); it corresponds to the distribution of main elements along the sample (primary zoning). Distribution curves for macrocomponents in zones I and II of the sample were constructed, as well as the dependencies of their partition coefficients (k) between solid solutions and sulfide melt on the fraction of crystallized melt. The secondary (mineral) zoning resulted from subsolidus phase transformations has been revealed. Five subzones have been recognized: mss + cp (Ia) / mss + cp + pn (Ib) / mss + pc + pn (IIa) / mss + pc + pn + bn (IIb) / pc + bn + pn + unidentified microphases (III). Admixture species in the sample were studied: (1) admixtures dissolved in primary solid solutions and in main minerals resulted from solid-phase transformations and (2) admixtures forming their own mineral phases. The partition coefficients of Co, Rh, and Ru (mss/L), Ru, Ir, and Rh (mss/cp), and Co, Rh, and Pd (mss/pn) were determined. Minerals of noble metals have been recognized: Pt3Fe, PtFe, Au, (Ag,Pd), (Au,Pt), Ag, Ag3Cu, Au3(Cu,Ag,Pd,Pt), etc., and the regularities of their distribution in the sample have been established. It is shown that some noble-metal admixtures are prone to interact with As. Mineral arsenides and sulfoarsenides of noble metals produced during fractional crystallization have been recognized: PtAs2, Pd3As, (RhAsS), (IrAsS), and (Ir,Rh)AsS. The discovered drop-like inclusions of noble-metal arsenides suggest the separation of the initial sulfide-arsenide melt into two immiscible liquids. By indirect features, the micromineral inclusions are divided into primary, crystallized from melt, and secondary, produced in solid-phase reactions. The results of study are compared with literature experimental data obtained by the isothermal-annealing method and with the behavior of noble metals and As during the formation of zonal massive orebodies at the Noril’sk- and Sudbury-type deposits.
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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 | 0.001 |
| 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".