Humidity Sensing of Ordered Macroporous Silicon With ${\rm HfO} _{2}$ Thin-Film Surface Coating
Bibliographic record
Abstract
Porous silicon (PS), as a gas/chemical sensing material, has been widely investigated. In this paper, the humidity sensing characteristics of n-type macroporous silicon with ordered structure and metal oxide thin-film coating is studied. The ordered PS has uniform pore size, pore shape and distribution. All pores are aligned vertically and open to the environment. The PS heterostructure (PS/Si substrate) and self-supporting membrane are fabricated and their resistance responses are measured under room temperature. A resistance variation of 23.5% and 28.3% for each structure are obtained, respectively. Surface modification for sensing enhancement is also investigated. The resistance and capacitance responses of ordered PS heterostructure with HfO2thin-film coating are characterized. The HfO2modified PS show high sensing variation and near-linear response to a wide range of relative humidity (RH). It is also demonstrated that PS with HfO2thin-film coating is able to sense the RH change faster than a commercial humidity sensor. To the best of our knowledge, this is the first time that humidity sensing with ordered porous silicon and HfO2thin-film is reported. Possible sensing mechanisms and future work are also discussed.
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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".