Variations of Major and Minor Elements in Pt–Fe Alloy Minerals: A Review and New Observations
Bibliographic record
Abstract
Compositional variations of major and minor elements were examined in Pt–Fe alloys from various geological settings and types of deposits, both lode and placer occurrences. They included representatives of layered intrusions, Alaskan-Uralian-(Aldan)-type and alkaline gabbroic complexes, ophiolitic chromitites, and numerous placers from Canada, USA, Russia, and other localities worldwide. Pt–Fe alloy grains in detrital occurrences are notably larger in size, and these are considered to be the result of a special conditions during crystallization such as temperature, pressure, geochemistry or time. In addition, the number of available statistical observations is much greater for the placer occurrences, since they represent the end-product of, in some cases, the weathering of many millions of tonnes of sparsely mineralized bedrock. Typically, platinum-group elements (PGE) present in admixtures (Ir, Rh, and Pd) and minor Cu, Ni are incorporated into a compositional series (Pt, PGE)2–3(Fe, Cu, Ni) in the lode occurrences. Relative Cu enrichment in alloys poor in Pt implies crystallization from relatively fractionated melts at a lower temperature. In contrast to the lode deposits, the distribution of Ir, Rh, and Pd is fairly chaotic in placer Pt–Fe grains. There is no relationship between levels of Ir, Rh, and Pd with the ratio Σ(Pt + PGE):(Fe + Cu + Ni). The compositional series (Pt, PGE)2–3(Fe, Cu, Ni) is not as common in the placer occurrences; nevertheless, minor Cu and Ni show their maximums in members of this series in the placer grains. Global-scale datasets yield a bimodal pattern of distribution in the Pt–Fe diagram, which is likely a reflection of the miscibility gap between the ordered Pt3Fe structure (isoferroplatinum) and the disordered structure of native or ferroan platinum. In the plot Pt versus Fe, there is a linear boundary due to ideal Pt ↔ Fe substitution. Two solid solution series are based on the Ir-for-Pt and Pd-for-Pt substitutions. The incorporation of Ir is not restricted to Pt3Fe–Ir3Fe substitution (isoferroplatinum and chengdeite, plus their disordered modifications). Besides, Ir0 appears to replace Pt0 in the disordered variants of (Pt–Ir)–Fe alloys. There is a good potential for the discovery of a new species with a Pd-dominant composition, (Pd, Pt)3Fe, most likely in association with the alkaline mafic-ultramafic or gabbroic complexes, or the mafic units of layered intrusions. The “field of complicated substitutions” is recognized as a likely reflection of the crystallochemical differences of Pd and Ir, extending along the Ir-Pd axis of the Ir–Pd–Rh diagram. The inferred solid solution extends approximately along the line Ir–(Pd:Rh = 2:3). Minor Pd presumably enters the solid solution via a coupled substitution in combination with the Rh. An Ir-enrichment trend in Pt–Fe alloys typically occurs in the Alaskan-type complexes. The large size of the Pt–Fe nuggets associated with some of these complexes is considered to be related to an ultramafic-mafic pegmatite facies, whereas significant Pd-enrichment is characteristic of gabbroic source-rocks (e.g., Coldwell Complex), resulting in a markedly different trend for the Pt versus Fe (wt.%). However, based on our examination of a large dataset of Pt–Fe alloys from numerous origins, we conclude that they exhibit compositional overlaps that are too large to be useful as reliable index-minerals.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".