Highly Efficient Photochemical Vapor Generation for Sensitive Determination of Iridium by Inductively Coupled Plasma Mass Spectrometry
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Herein, we describe the highly efficient photochemical vapor generation (PVG) of a volatile species of Ir (presumably iridium tetracarbonyl hydride) for subsequent detection by inductively coupled plasma mass spectrometry (ICPMS). A thin-film flow-through photoreactor, operated in flow injection mode, provided high efficiency following optimization of identified key PVG parameters, notably, irradiation time, pH of the reaction medium, and the presence of metal sensitizers. For routine use and analytical application, PVG conditions comprising 4 M formic acid as the reaction medium, the presence of 10 mg L –1 Co 2+ and 25 mg L –1 Cd 2+ as added sensitizers, and an irradiation time of 29 s were chosen. An almost 90% overall PVG efficiency for both Ir 3+ and Ir 4+ oxidation states was accompanied by excellent repeatability of 1.0% ( n = 15) of the peak area response from a 50 ng L –1 Ir standard. Limits of detection ranged from 3 to 6 pg L –1 (1.5–3 fg absolute), dependent on use of the ICPMS reaction/collision cell. Interferences from several transition metals and metalloids as well as inorganic acids and their anions were investigated, and outstanding tolerance toward chloride was found. Accuracy of the developed methodology was verified by analysis of NIST SRM 2556 (Used Auto Catalyst) following peroxide fusion for sample preparation. Practical application was further demonstrated by the direct analysis of spring water, river water, lake water, and two seawater samples with around 100% spike recovery and no sample preparation except the addition of formic acid and the sensitizers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".