A new method to quantitatively control oxygen fugacity in externally heated pressure vessel experiments
Bibliographic record
Abstract
Abstract. Oxygen fugacity (fO2) is a fundamental variable affecting phase equilibrium in magmas, and in externally heated pressure vessel experiments it is typically controlled by using redox buffer assemblages. However, these do not allow fine enough resolution; for example, most arc magmas fall between the fO2 imposed by the neighboring Ni–NiO and Re–ReO2 buffers and so does the transition of S2− to S6+ in magmas. Here we propose a new method to quantitatively impose fO2 in hydrous high-P–T experiments in molybdenum hafnium carbide (MHC) pressure vessels by admixing small amounts of hydrogen into the Ar pressure medium. The thermodynamic calculation procedure used to determine the initial amount of hydrogen to be loaded to constrain desired fO2 values was verified by CoPd alloy redox sensor experiments to be accurate within ±0.3 log units for the pressure (P) – temperature (T) range of 940–2060 bar and 800–1100 ∘C. As hydrogen can be slowly lost from the pressure medium due to diffusion through the vessel walls at high T, we also determined the hydrogen permeability of the MHC alloy as a function of T. The such-obtained hydrogen permeability equation for the MHC alloy can be used to determine the rate of fO2 increase for any MHC pressure vessel configuration. As the rate of fO2 increase is slow (e.g., 0.36 log units per day in our setup at T= 1000 ∘C), we propose that H2 addition to the Ar pressure medium is an effective way to accurately impose fO2 in many types of experiments conducted in MHC vessels allowing experimentation up to T= 1200 ∘C and P= 300 MPa.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".