CHARACTERIZATION OF<font>Al</font><sup>+</sup>SECONDARY ION EMISSION PRODUCED BY<font>Ne</font><sup>+</sup>AND<font>Ar</font><sup>+</sup>BOMBARDMENT OF ALUMINIUM SURFACE
Bibliographic record
Abstract
This paper reports the characterization of the velocity (energy) dependencies of the Al+secondary ion emission produced by 0.5 keV and 5 keV Ne+and Ar+bombardment of polycrystalline pure aluminium. The distributions of secondary Al+ions over their kinetic energy were measured for emission energies of 1–1000 eV without applying electric fields to force the ions into the mass–energy analyzer. To extract the ionization probability, the measured energy distributions of emitted ions were normalized with respect to reference energy distributions of neutral atoms. The reference distributions were obtained by original numerical simulations, as well as analytically, through a sophisticated normalization of the Thompson distribution. It was shown that for both extraction methods, the logarithmic plots of the normalized secondary ion fraction versus the normal component of the reciprocal ion velocity (the reciprocal or inverse velocity plots) are nonmonotonic, with two peaks and two linear portions situated at a low emission energy (Ek=5–25 eV ) and at a high emission energy (Ek=80–280 eV ). The linear portions were fit by exponential dependency P+∝ exp (-v0/vn) with two different values of the characteristic velocity v0. For the low emission energy, the value v01~(3.3±0.2)×106cm / s was independent of the mass and energy of the projectiles. However, for the high emission energy, the characteristic velocity depended on the projectile's mass, M, namely v02~(5.3±0.3)×106cm / s for Ne+and v02~(8.1±0.3)×106cm / s for Ar+; the ratio v02( Ne+)/v02( Ar+) is close to the value [Formula: see text]. This indicates that ballistic mechanisms might contribute to affect the high-energy part of the reciprocal velocity plots along with nonballistic ionization processes, which are generally believed to be the only significant factor for the plots.
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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 | 0.000 |
| 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) | 0.001 | 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".