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
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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 (E k =5–25 eV ) and at a high emission energy (E k =80–280 eV ). The linear portions were fit by exponential dependency P + ∝ exp (-v 0 /v n ) with two different values of the characteristic velocity v 0 . For the low emission energy, the value v 01 ~(3.3±0.2)×10 6 cm / 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 v 02 ~(5.3±0.3)×10 6 cm / s for Ne + and v 02 ~(8.1±0.3)×10 6 cm / s for Ar + ; the ratio v 02 ( Ne + )/v 02 ( 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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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it