Unexpected Selectivity of UV Light Activated Metal-Oxide-Semiconductor Gas Sensors by Two Different Redox Processes
Bibliographic record
Abstract
The conflict between the two existing models was resolved, to provide a clear explanation for the unexpected “selectivity” found in UV light activated metal-oxide-semiconductor (MOS) gas sensors during the detection of reducing agents. A new model based on the dynamic equilibrium of adsorbed oxygen concentration was constructed by two types of responses: ( 1 ) when the MOS surface is adsorbed with oxygen, the conductance of the sensor increases upon injection of reducing agents (RA) (α-type) and ( 2 ) when the MOS surface is not covered by oxygen, the conductance decreases upon injection of RA (β-type). The proposed model was verified by the experiments of ZnO based MOS gas sensors, to reveal the origin of the unexpected “selectivity” found by the optimum intensity, where the current drop, due to the reaction between RA and MOS, which increases with UV power and levels with the reciprocal background current, which decreases with the UV power.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".