Aluminium nitride/nanodiamond structures for high-frequency surface acoustic wave nanotransducers
Bibliographic record
Abstract
Surface acoustic waves (SAWs) have been used extensively for a variety of applications such as telecommunications, electronic devices and sensors. The emerging need for high-bit data processing at GHz frequencies and the requirement of high-sensitivity sensors demand the development of high-efficiency SAW devices. With the objective of exploiting the high acoustic velocity of diamond, the authors report on an optimally developed nanodiamond (ND) thin film with crystal size of 3–5 nm, embedded in an amorphous carbon matrix with grain boundaries of 1–1.5 nm, that is integrated with aluminium nitride (AlN) to extend the operating frequency of SAW transducers. The authors utilise this attractive property of diamond through facile synthesis of a bi-layer structure consisting of sputtered AlN deposited on ND. Deposition of ND was carried out using microwave plasma-enhanced chemical vapour deposition. AlN/ND-based SAW structures were fabricated using electron beam lithography to produce high acoustic velocity transducers. The fabricated SAW transducers were composed of two spatial periods of 1400 and 3200 nm devices. The fabricated devices exhibit an operating frequency of >2 GHz with an acoustic velocity of 8120 and 9280 m/s, respectively.
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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".