Fluorinated Graphene Oxide Based Chemiresistive Gas Sensor Targeting NH3 and Other Analytes Under Atmospheric Conditions
Bibliographic record
Abstract
Emergence of graphene-derived highly functional materials has transformed chemical and biological sensing. Several novel approaches utilizing chemical modification of graphene oxide (GO) were investigated and implemented using these materials in sensor fabrication for the detection of chemical analytes such as volatile organic compounds (VOC). The detection methods rely on using functionalization of modified graphene derivatives to target select analytes and produce a quantifiable, distinguishable electrical response. In this work, an in-house hydrothermal fluorination technique to synthesize fluorinated-GO (FGO) suspension was developed. The FGO material was drop coated in its solution phase onto interdigitated electrodes to create a chemiresistive gas sensor. An ultra-low-level detection of NH3 (~>2.26 ppm) was observed by the chemiresistive sensor which was extended to detect acetone and distinguish between their individual transient responses. The sensor system is fully integrated and miniaturized making it suitable for point-of-care, continuous health monitoring applications in exhaled breath testing.
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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".