Influence of high‐strain deformation on major element mobility in garnet: Nanoscale evidence from atom probe tomography
Bibliographic record
Abstract
Abstract Garnet is a common rock‐forming mineral that occurs in a variety of rock types and over a wide range of pressure (P)–temperature (T) conditions in the Earth's lithosphere. Because garnet is considered a high‐strength mineral stable across an extensive range of conditions (1–25 GPa, <300–2000°C), it is generally accepted that garnets can retain their microstructures and chemical composition during deformation and metamorphism. Therefore, garnet is commonly used as a geothermobarometer and geochronometer to provide P–T and timing constraints on tectonic events. Herein, we study garnet from an eclogite facies mylonite (central Australia) to investigate the mechanisms of element mobility during high‐strain deformation under relatively dry, lower crustal conditions. Electron backscatter diffraction (EBSD) and electron channelling contrast imaging (ECCI) reveal evidence of crystal plasticity associated with brittle deformation in the form of heterogeneous misorientation patterns and low‐angle grain boundaries developed over length scales of 20–50 μm in the rims of garnet porphyroclasts. Atom probe tomography (APT) analysis of a low‐angle grain boundary within a highly strained portion of a clast shows Ca enrichment and Mg depletion along dislocations, whereas APT data along the rim of a mostly undeformed clast reveal a homogeneous distribution of garnet major components in the specimen matrix with the exception of Ca, Fe and Mg enrichment within a healed microfracture. The above‐mentioned results suggest that under relatively dry conditions, crystal plasticity enhances bulk element mobility via pipe diffusion, highlighting the importance of deformation‐induced microstructures on element mobility, with important implications for the robust and reliable use of garnet as a petrological tool.
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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 | 0.001 |
| 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".