Humidity sensing characteristics of laterally aligned ZnO nanowires by dielectrophoresis method
Bibliographic record
Abstract
In this study, the humidity sensing characteristics of zinc oxide (ZnO) nanowires are investigated experimentally. ZnO nanowires are grown by hydrothermal method at low temperature (95°C) for 3-24 hours. Dielectrophoresis (DEP) force is then applied to assemble ZnO nanowires on interdigitated electrode (IDE) patterns to make connection between two electrodes. Prior to the assembling, thermal annealing is used and pure alcohol is dropped on the IDE pattern so that the adhesion of IDE patterns and substrate is improved effectively. The hydrogen sites of water molecules are thought to be positively charged due to the high electronegativity of oxygen compared to hydrogen. These charged hydrogen sites will capture the electrons of ZnO nanowires electrostatically. Thus, the electrical resistance of our sensor increases with increasing relative humidity (RH) level in the tests. Our sensors show extremely fast response time and they can reach 90% of the total change in 16 seconds when increasing RH level from 0% to 100%. These laterally aligned ZnO nanowires are expected to be promising for applications in commercial humidity 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) | 0.001 | 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".