From the weakest to strongest sulphide: how the strength of pyrite evolves during deformation
Bibliographic record
Abstract
Sulphides are common host minerals for trace elements, including critical and precious metals, and are widely associated with a range of ore deposit types. Recent work on natural sulphides has highlighted the link between the motion of dislocations—lattice defects that act as carriers of deformation—and the transport of trace elements through mechanisms such as pipe diffusion, in which dislocations act as fast diffusion pathways, or the correlated motion of dislocations and impurities, whereby impurities are entrained within the stress field of migrating dislocations. Despite the clear influence of deformation on the distribution of trace and precious metals and, therefore, on the economic viability of an orebody, the strengths of different sulphides are not well constrained. Flow laws for sulphides either do not exist or are not able to reproduce ductile flow, with experiments instead ending in brittle failure. This paucity of experimental studies makes interpreting natural microstructures challenging. In this work, we start by constraining the relative strengths and hardening behaviours of three sulphides, pyrite, sphalerite, and chalcopyrite, via nanoindentation experiments at room temperature. Through subsequent characterisation of the microstructures using electron backscatter diffraction and the concentration of trace elements and critical- and precious metals using LA-ICP-MS, we explore how grain size, orientation, and chemistry affect mineral strength. Although pyrite is widely considered to be stronger than other common sulphides, our data suggest that the intrinsic yield stress of pyrite may, surprisingly, be weaker than the yield stress of both chalcopyrite and sphalerite. However, as deformation proceeds and the density of geometrically necessary dislocations (GNDs) is elevated pyrite strengthens rapidly. These results suggest a strong size effect at low temperature in which elastic dislocation interactions are stronger within pyrite compared to other sulphides. Our results are consistent with observations of fine-grained pseudo-porphyroclasts in nature, for which the GND density is predicted to be inversely proportional to the grain size. Overall, this work provides a foundation for accurate models of how the strength of pyrite evolves and, as such, how transport of trace elements and upgrading of ore deposits may proceed.
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.
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 | 0.001 |
| Scholarly communication | 0.001 | 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".