Petrologic Thermodynamic and Diffusion Kinetic Modeling: Applications to Venus and the Western Tianshan Metamorphic Belt, China
Bibliographic record
Abstract
Slab subduction plays an essential role in plate tectonics and Earth's geological evolution. While conventional petrologic and thermodynamic modeling derive valuable P-T information from exhumed high-pressure terranes, assessing rates or timescales adds a new dynamic perspective on subduction processes. Recent studies, through calibrated diffusion models for minerals, have successfully formulated comprehensive P-T-t paths using diffusion speedometry. However, the intricate mathematics involved underscores the need for accessible and adaptable software, leading to the creation of DIFFUSUP, a user-friendly diffusion simulation tool introduced in this Ph.D. thesis.Garnet is a prevalent mineral in metamorphic rocks. The diffusion of divalent cations (Ca2+, Mg2+, Fe2+, Mn2+) in garnet is widely used for resolving transient geological events in diverse contexts. However, the available models have demonstrated inconsistencies, especially at low temperatures. This thesis then recalibrates the garnet diffusion model, focusing on Mn2+, utilizing samples from the Western Tianshan ultrahigh-pressure metamorphic belt. This recalibrated model, when applied to an eclogitic breccia, unveils a transient thermal phase during slab exhumation. For carbonate minerals, the existing diffusion models for Mg2+–Fe2+/Mn2+ in dolomite need re-evaluation due to notable disparities between model predictions and empirical observations. Through high-pressure experiments and natural sample examination, this research shows that the diffusion rates are considerably slower than previous insights from experiments, setting new upper limits at a series of temperatures. Such findings emphasize the critical role of spatial resolution of analytical methods in diffusion modeling. Beyond diffusion speedometry, an analysis of the physical properties of subduction slabs offers valuable insights into subduction geodynamics and broader consequences. The final chapter compares the buoyancy of subducting slabs on Archean Earth with Venus. Based on 2D thermo-metamorphic modeling, the results shed light on how the variation in eclogitization influences slab buoyancy on these two planets. The greater chemical buoyancy on Venus, posing resistance to subduction, may have hindered its transition to self-sustained subduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".