Polymer-Based Virtual Sensor Array Leveraging Fringing Field Capacitance for VOC Detection
Bibliographic record
Abstract
The detection of volatile organic compounds (VOCs) is crucial in various applications, from environmental monitoring to industrial safety. Through this paper we present a comparative analysis of a polymer-based virtual sensor array (VSA) for VOC detection, utilizing fringing field capacitance to enhance sensitivity and potentially reduce the size of sensor arrays required to differentiate VOC analytes. Polymer-based sensors exhibit changes in material permittivity in response to VOCs, and electrochemical impedance spectroscopy (EIS) measures the resultant change in capacitance. Principal component analysis (PCA) is used to extract subtle patterns from the multivariate EIS data for the identification and differentiation of different VOCs. Results demonstrate superior sensitivity and differentiation capability over conventional rectangular IDE reference design. This research demonstrates the potential of a polymer-based virtual sensor array leveraging fringing field capacitance in VOC detection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".