Test of the Ardell distribution function for two-dimensional adsorbate islands using thermal desorption spectroscopy
Bibliographic record
Abstract
The thermal desorption of atoms from two-dimensional deposit islands on a substrate may be limited by the rate of desorption from island edges. In earlier work, Slavin and Young developed a theory for the form of the desorption curves for such systems, as a function of the average island size, that agreed well with experimental data until just beyond the peak maximum. The fitting procedure provided values for the desorption energy, the average island radius, the standard deviation of the island-size distribution function, and the frequency of vibration of an atom at an island edge. The current study extends this work by incorporating a theoretical expression for the initial distribution of island sizes, due to Ardell, into the previous theory. The Ardell function provides a value for the average initial island radius and the standard deviation of the distribution without any curve fitting, if the surface coverage and the number of islands are known. It also enables the experimental thermal desorption data to be fitted over the entire desorption curve, which provides an independent check on the experimental value for surface coverage. The results using the Ardell distribution are in good agreement with all the parameters obtainable from the experimental data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".