Supercritical argon as a mobile phase for the flame photometric detection of sulfur
Bibliographic record
Abstract
The background emission properties of supercritical argon and supercritical carbon dioxide mobile phases in packed column supercritical fluid chromatography (pSFC) with flame photometric detection (FPD) were compared. As column flow rates were increased toward common values used in pSFC, the carbon dioxide background emission grew enormously. The resulting emission spectrum displayed dominant features at wavelengths between 325 and 525 nm, consisting of a complex series of overlapping molecular emission band systems partly attributed to CO* and CH*. By comparison, when using the same flow rates with a supercritical argon mobile phase, the background emission was identical to that of the FPD flame without column effluent. In terms of intensity, when using a column flow rate of 2 mL/min, supercritical carbon dioxide contributes a background emission in the FPD that is about 3 × 105 times larger than that produced by supercritical argon. This difference leads to an improvement of two orders of magnitude in the pSFC-FPD signal-to-noise ratio for sulfur when a supercritical argon mobile phase is used. Results indicate that supercritical argon could also be advantageous for the pSFC-FPD analysis of other elements.Key words: supercritical fluid chromatography, packed column, flame photometric detection, supercritical argon.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".