Low temperature aluminum nitride deposition on aluminum by rf reactive sputtering
Bibliographic record
Abstract
Thin film bulk acoustic resonators formed by sputter deposition of piezoelectric films of aluminum nitride on silicon substrates offer an attractive approach to monolithic integration of high Q passive circuit elements with active devices. Such resonators could provide low cost, high performance filters for the steadily growing number of consumer wireless communication devices. Fabrication of these resonators requires a well-characterized low temperature deposition process for aluminum nitride. This material has been studied for use in sensors and actuators, as well as acoustic wave devices. Radio frequency reactive magnetron sputtering produces high quality films, and provides reasonable deposition rates for fabricating high frequency resonators. This work describes aluminum nitride films deposited by radio frequency reactive magnetron sputtering with power varied from 2 to 6 W/cm2, pressure from 0.5 to 1.5 Pa, and N2 flow from 50% to 100% of the total flow. Measured results include x-ray diffraction spectra and measurements of piezoelectric coefficients. X-ray diffraction measurements indicate highly (002) c-axis oriented films. Piezoelectric coefficients e31 were measured by depositing aluminum nitride capacitors on silicon beams and measuring charge generation as each beam was deflected a known distance. Film quality was found to depend strongly on deposition power, with a smaller dependence on pressure and gas mixture. Deposition at higher pressures is preferred for resonator fabrication due to reduction in stress when compared with low pressure deposition.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".