Experimental constraints on the diffusion of volatile and redox-sensitive elements in pyroxenes.
Bibliographic record
Abstract
Diffusion of major and trace elements (e.g. Fe-Mg, Li, etc.) in pyroxene group minerals is a powerful witness and tool to track the timescales of various processes in magmatic systems. Diffusion of volatile elements (e.g. Cu, Li) enable us to estimate timescales of volatile-driven processes. Redox-sensitive elements (e.g. V) may also be used to identify changes, if any, in the redox condition of a magmatic system. The relative variations in diffusion rates between these two groups of elements can provide a complementary record of timescales, as preserved in pyroxenes. In this study, we present preliminary data on diffusion experiments of Li, Cu, and V in gem-quality enstatite (‘Opx-7’) and naturally occurring diopside from Otter Lake, Canada (‘OL-Di’). For Cu and Li diffusion in pyroxenes, we designed an experimental setup in evacuated silica tubes, where two powder-couple diffusion experiments buffered by either NNO or IW solid powder were simultaneously annealed in a muffle furnace at T = 950-1100°C, P = 1 atm for 6-96 hours. For Vanadium diffusion, we used a thin film experiment following [1] in a vertical furnace buffered at log (fO2) = -10 at T = 950-1200°C, P = 1 atm for 66-162 hours. The pyroxene cubes were analyzed using laser ablation ICP-MS (Cu, Li) and Time-of-Flight secondary ion mass spectrometer (V). We find that in addition to Cu, which was deliberately added to the powder as a reservoir, the Otter Lake diopside also acted as a source of Li within the capsule. We propose that the light and volatile lithium diffused out of the diopside and into the Li-poor enstatite. The vacuum seal prevented the volatile Cu and Li from escaping the capsule. We modelled the diffusion profiles from both Opx-7 and OL-Di for Li, Cu, and V to constrain diffusion coefficients. Future directions include investigating the effect of fO2 diffusion for the elements of interest. The results of these studies may be useful to study volatile metal diffusion in magmatic and volcanic systems. [1] Dohmen R, Becker HW, Meissner E, Etzel T, Chakraborty S (2002). Eur J Mineral 14(6):1155–1168.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".