High-temperature gas sensor using perovskite thin films on a suspended microheater
Bibliographic record
Abstract
Suspended microstructures consisting of a thin oxide/nitride diaphragm with embedded polysilicon heaters were designed and fabricated using a standard complementary metal–oxide–semiconductor process and simple postprocessing. Thin films of gas sensitive materials based on the SrFeO2.5+x nonstoichiometric perovskite family were deposited onto the diaphragms by room-temperature pulsed excimer laser deposition. Successful chemical sensor functionality was demonstrated. With applied power up to 30 mW, estimated temperatures of the gas sensor film up to 900 °C were reached. When the device was exposed to volatile organic compounds (VOCs) such as acetone and methanol, a reversible ten to 100-fold increase in sensor film resistance was observed, with response times from less than 1 s to a few minutes. Sensor response sensitivity depended on applied power and on the nature of the VOC analyte. This sensor device has the potential for use in multiarray configurations such as in an electronic nose.
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 | 0.001 | 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".