High-Yield UV-Photochemical Vapor Generation of Iron for Sample Introduction with Inductively Coupled Plasma Optical Emission Spectrometry
Bibliographic record
Abstract
A novel approach to the generation of volatile iron compounds (likely the pentacarbonyl) with high efficiency is described, wherein solutions containing either Fe(2+) or Fe(3+) and low molecular weight organic acids such as formic, acetic or propionic are exposed to a UV source. An optimum generation efficiency of 60 +/- 2% was achieved in 50% formic acid at pH 2.5 with an irradiation time of 250 s by use of a 17 W low-pressure mercury grid lamp. Compared to conventional solution nebulization, sensitivity and limit of detection were improved 80- and 100-fold, respectively, at the 238.204 nm Fe II emission line. A precision of 0.75% RSD was achieved at a concentration of 100 ng/mL. Photochemical vapor generation sample introduction was used for the determination of trace iron in several environmental Certified Reference Materials, including National Research Council Canada DORM-3 fish muscle tissue, DOLT-3 and DOLT-4 fish liver tissues, and SLRS-5 river water, providing analytical results in excellent agreement with certified values based on a simple external calibration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".