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Record W2781045968 · doi:10.1021/acs.analchem.7b04446

Atmospheric-Pressure Dielectric Barrier Discharge as an Elemental Ion Source for Gas Chromatographic Analysis of Organochlorines

2017· article· en· W2781045968 on OpenAlexaff
Kunyu Zheng, Michael J. Dolan, Peter J. Haferl, Hamid R. Badiei, Kaveh Jorabchi

Bibliographic record

VenueAnalytical Chemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsPerkinElmer Biosignal
FundersDivision of ChemistryNational Science Foundation
KeywordsChemistryDielectric barrier dischargeElemental analysisAnalytical Chemistry (journal)Mass spectrometryAtmospheric pressureIon sourceIonChromatographyGas chromatographyDetection limitIon chromatographyInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Atmospheric-pressure dielectric barrier discharge (AP-DBD) plasma has emerged in recent years as a versatile plasma for molecular ionization and elemental spectroscopy. However, its capabilities as an elemental ion source have been less explored, partly because of difficulties in the detection of positive elemental ions from this low-gas-temperature plasma. In this work, we investigate the detection of negative elemental ions to enable elemental mass spectrometry (MS) using AP-DBD. A gas chromatograph is coupled to a helium AP-DBD apparatus and positioned in front of an atmospheric-pressure-sampling mass spectrometer with no modifications to the ion sampling interface. We demonstrate that Cl – ions are detected with a compound-independent efficiency, enabling elemental quantification of organochlorines. Further, addition of oxygen at low concentration (11 ppm, v/v) to the helium plasma improves the analytical performance by reducing postcolumn peak broadening, whereas high oxygen concentrations (>110 ppm, v/v) lead to loss of the compound-independent response. The optimized GC-AP-DBD-MS setup shows close to 2 orders of magnitude of linearity for its compound-independent Cl response and offers detection limits of 0.5–1 pg of Cl on column (0.6 pg/s), suitable for analysis of organochlorines in food samples. We demonstrate this capability by analyzing orange juice spiked with pesticides at 9 μg/L and a single internal standard. Importantly, we demonstrate that a quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction followed by GC-AP-DBD-MS quantification using the single standard provides acceptable recoveries (80–120%). These results highlight uniform QuEChERS extraction of a range of compounds and the compound-independent response of AP-DBD for Cl, making the combination of the two methods desirable for the rapid quantification of organochlorines. Furthermore, we discuss ionization matrix effects in AP-DBD for chlorine detection and offer strategies to flag matrix-impacted analytes. These results suggest that AP-DBD has the potential to become a unified ion source for both elemental quantification and molecular identification of GC eluents on a single MS platform.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.009
GPT teacher head0.282
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

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