Experiments and kinetic modeling of the ion energy distribution function at the substrate surface during magnetron sputtering of silver targets in radio frequency argon plasmas
Bibliographic record
Abstract
The quality of the films obtained by magnetron sputtering depends on numerous parameters, including the energy of the ions impinging on the substrate. The energy distribution functions of Ar and Ag ions during magnetron sputtering of a silver target in rf argon plasmas are hereby reported. Measurements were carried out by plasma sampling mass spectrometry at (i) various bias voltages on the surface of the target at constant pressure and (ii) various operating pressures at constant bias voltage. A distinct high-energy tail is observed for the sputtered silver ions (ionized in the plasma) in comparison to the argon gas ions. The results indicate that the sputtered Ag atoms are not completely thermalized by collisions with background gas atoms over the range of experimental conditions investigated. To confirm such assertion, a model has been developed for the ejection of Ag atoms from the target, their transport in the gas phase, and their acceleration in the sheath at the surface of the mass spectrometer. Since sputtering occurs at low impinging ion energies, the energy distribution function of the extracted atoms cannot be represented by the usual Sigmund–Thomson distribution. It is rather assumed to be characterized by a bi-Maxwellian distribution, with one population related to the direct “classical” sputtering and the other one to indirect “2-step etching.” During the transport of Ag neutrals, both ionization and thermalization processes are considered. Finally, the rf sheath near the entry of the mass spectrometer oscillates at a period close to the transit time of the ions passing through it. This induces a complex energy gain also implemented in the model. An excellent agreement between the latter and experimental measurements is obtained. The results are used to probe the effect of the bias voltage and pressure on the fitting parameters, namely, the dc and rf components of the voltage drop in the sheath, the mean energy of the sputtered atoms, and the relative importance of the sputtered populations.
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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".