Ultra‐thin ALD CoO <sub> <i>x</i> </sub> ‐ZnO heterogenous films as highly sensitive and environmentally friendly H <sub>2</sub> S sensor
Bibliographic record
Abstract
Abstract To obtain environmentally friendly, integrated and miniaturized gas sensors for the increasing request for the Internet of Things industry and other relative areas, the ultra‐thin CoO x /ZnO heterogeneous film with active interfacial sites was in‐situ deposited on micro‐electro‐mechanical systems (MEMS) as H 2 S sensor. Atomic layer deposition (ALD) was employed to in‐situ fabricate the uniform ZnO thin film. ALD CoO x was deposited on ZnO surface to obtain CoO x /ZnO heterojunction and active interfacial sites. The ultra‐thin film (20 nm) with 50 ALD CoO x decorated on 250 ALD ZnO displays excellent sensing performance, including very high response (4.45@200 × 10 −9 ) and selectivity to H 2 S with a limit of detection (LOD) of 0.38 × 10 −9 , long‐term sensing stability, high response/recovery performance (7.5 s/15.7 s) and mechanical strength at 230 °C. Reasons for the high sensing performance of CoO x /ZnO have been confirmed by series of characterizations and density functional theory (DFT) calculation. Heterojunction film thickness with Debye length, the oxygen vacancies and the synergistic effect of active interfacial sites are main reasons for the high sensing performance. The strategy by fabrication of CoO x /ZnO heterogeneous film within Debye length and employing synergistic effect of active interfacial sites offers a promising route for the design of environmentally friendly gas sensors. Furthermore, the ALD technique offers a facile in‐situ strategy and high‐throughput fabrication of MEMS gas sensors.
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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) | 0.000 | 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".