A 2D and 3D nanostructural study of naturally deformed pyrite: assessing the links between trace element mobility and defect structures
Bibliographic record
Abstract
The links between deformation-induced micro- and nanostructures and trace element mobility in sulphide minerals have recently become a popular subject of research in the Earth sciences due to its connections with metallic ore paragenesis. It has been shown that plastic deformation in pyrite creates diffusion pathways in the form of low-angle grain boundaries that act as traps for base- and precious-metals. However, the plastic behavior of pyrite and the physiochemical processes that concentrate these trace elements in deformation-induced micro- and nanostructures remain poorly understood. In this study, we develop strategies for 2D and 3D analysis of naturally deformed sulphides by combining electron backscatter diffraction, electron channeling contrast imaging and atom probe tomography on pyrite in an attempt to better understand the underlying diffusion processes that mobilize trace elements. The combined results reveal structures associated with crystal-plastic deformation in the form of dislocations, stacking faults, and low-angle grain boundaries that are decorated by As and Co. Although our data support a dislocation-impurity pair diffusion model, we have evidence that multiple diffusion mechanisms may have acted simultaneously. In this study, we applied new data processing techniques that allow for orientation measurement of nanostructural crystal defects from atom probe tomography data. Dislocations within our studied sample occur along the (110) planes suggesting glide on {110}.
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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 | 0.001 | 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".