Characteristics of a novel alkali flame ionization detector as an air sensor for volatile organo-nitrogen compounds
Bibliographic record
Abstract
A novel alkali flame ionization detector (AFID) is introduced and characterized for use as an air sensor (i.e., without chromatographic separation) for organo-nitrogen compounds. Using a planar channeled quartz design, a simple, lightweight architecture for the portable device is presented, which yields sensitive and selective response toward nitrogen-containing analytes. For instance, the AFID sensor offers a detection limit of 30 pg N/s and a selectivity for nitrogen response over carbon of nearly two orders of magnitude. Further, nitrogen response is linear over the 1000-fold range of concentrations investigated. Relative to a flame photometric detector (FPD) device also used in a sensor mode, the AFID is observed to provide 100 times greater S/N values for nitrogen analytes with a nitrogen-to-carbon selectivity that is about 15 times larger. When using the AFID and FPD sensors in tandem, it is found that the response ratio of the simultaneous signals generated by each produces characteristic values that more clearly identify the presence or absence of nitrogen in unknown analytes. The AFID sensor was used to detect organo-nitrogen analytes in several samples, and results indicate that it could be a useful approach for portable air sensing of nitrogen compounds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".