A membrane introduction mass spectrometer utilizing ion‐molecule reactions for the on‐line speciation and quantitation of volatile organic molecules
Bibliographic record
Abstract
RATIONALE: The ability of membrane introduction mass spectrometry to quantitatively resolve low molecular weight volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene and xylene (BTEX) using electron ionization (EI) can be compromised by isobaric interferences. This work focuses on reducing isobaric interferences with ion-molecule reactions in a portable quadrupole ion trap mass spectrometer for the analysis of VOCs. METHODS: EI was used to produce reagent ions from precursors (chloroform, methyl iodide, trichloroethylene or chlorobenzene) that were continually infused into the helium acceptor phase upstream of the membrane introduction mass spectrometry (MIMS) sampling interface. The reagent ions were selectively stored in the ion trap, and then allowed to react with target VOC analytes in air samples via ion-molecule reactions within the trap storage volume. A variety of reaction times were examined (50-5000 ms), and the resulting product ions were analyzed in positive ion mode. RESULTS: The detection limits achieved were comparable with those obtained using EI (low ppbv), and in some cases better than for EI coupled with tandem mass spectrometry (MS/MS). For the VOCs studied, isobaric interferences were greatly reduced or eliminated using chloroform as a reagent gas. The predominant ionization mechanism was via adduct formation, although charge transfer and hydride abstractions were also observed. An internal standard was shown to be effective at correcting for signal changes due to consumption of reagent ions when complex mixtures were sampled. CONCLUSIONS: Ion-molecule reactions were exploited to eliminate isobaric interferences that are often encountered in direct, real-time analysis strategies for atmospheric VOC mixtures. The use of a continuously infused internal standard will improve quantitative results in field applications where analyte concentration and sample complexity may be wide ranging.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".