Effects of temperature and Ar <sup>+</sup> ion bombardment on the initial oxidation stages of polycrystalline aluminium with water vapour
Bibliographic record
Abstract
Abstract The initial stages of oxide formation following the interaction of water vapour with polycrystalline aluminium surfaces have been studied using x‐ray photoelectron spectroscopy (XPS) and Auger electron spectroscopy (AES). Attenuation of the electron signal from the metallic substrate has been used to follow the oxidation kinetics of aluminium as a function of energy and dose of Ar + ion bombardment and temperature. The effects of energy and doses of Ar + ion bombardment on oxidation kinetics have been examined in the energy range 1–5 keV and ion dose ranging from 1.3 × 10 16 to 3.8 × 10 17 ions cm −2 . Although the increase in energy of Ar + ion bombardment slightly modified the oxidation kinetics, the effects of ion dose on oxidation kinetics are shown to be more complex. There is a threshold dose of Ar + ions above which the surface activity becomes significantly reduced; this is ascribed to cluster formation blocking the surface diffusion pathway in the near‐surface region. The oxidation kinetics of aluminium also have been studied in a range of temperature from room temperature up to 573 K. As the temperature increases, the oxidation rate of aluminium decreases due to a decrease in the sticking probability of water molecules on the aluminium surfaces. The observed temperature dependence of the oxidation kinetics is likely to be due to a precursor mechanism of water desorption. Copyright © 2001 John Wiley & Sons, Ltd.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".