Piezotransistive transduction of femtoscale displacement for photoacoustic spectroscopy
Bibliographic record
Abstract
Measurement of femtoscale displacements in the ultrasonic frequency range is attractive for advanced material characterization and sensing, yet major challenges remain in their reliable transduction using non-optical modalities, which can dramatically reduce the size and complexity of the transducer assembly. Here we demonstrate femtoscale displacement transduction using an AlGaN/GaN heterojunction field effect transistor-integrated GaN microcantilever that utilizes piezoelectric polarization-induced changes in two-dimensional electron gas to transduce displacement with very high sensitivity. The piezotransistor demonstrated an ultra-high gauge factor of 8,700 while consuming an extremely low power of 1.36 nW, and transduced external excitation with a superior noise-limited resolution of 12.43 fm Hz(-1/2) and an outstanding responsivity of 170 nV fm(-1), which is comparable to the optical transduction limits. These extraordinary characteristics, which enabled unique detection of nanogram quantity of analytes using photoacoustic spectroscopy, can be readily exploited in realizing a multitude of novel sensing paradigms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".