Dielectric powder characterization by radio frequency measurements technique for hydrogen sensor applications: Application to iron oxide
Bibliographic record
Abstract
This work presents a characterization technique developed to study the gas sensitivity of dielectric powder in Radio Frequency (RF) domain for hydrogen sensing application at room temperature. The method is based on the measurement of S parameters of sample holder loaded with dielectric powder. The sample holder used is designed and adapted to fit in a gas test bench for materials characterization under gas environment. The non-ideal cylindrical sample holder is modeled to extract dielectric permittivity of the filled powder in the frequency range of 25 MHz to 350 MHz. Then, the measurement technique with the designed setup is applied to iron (II, III) oxide dielectric powder to extract dielectric permittivity variation under hydrogen atmosphere. The results show a significant dielectric constant variation in presence of hydrogen. In addition, the presented model has advantages of a high accuracy in wide permittivity range validity from 1 to 25. This technique allows characterizing dielectric material for sensing application and to be used for other gas sensing application.
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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 | 0.001 | 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".