Atmospheric Pressure Ionization in a Miniature Mass Spectrometer
Bibliographic record
Abstract
A miniature cylindrical ion trap mass spectrometer featuring an atmospheric pressure interface allowing atmospheric pressure chemical ionization and electrospray ionization is described together with its analytical performance characteristics. The vacuum system, ion optics, mass analyzer, control electronics system, and detection system have all been designed and built in-house. The design is based upon a three-stage, differentially pumped vacuum system with the instrument capable of being interfaced to many types of atmospheric pressure ionization sources. Ions are transferred through home-built ion optics, and instrument control is achieved through custom-designed electronics and LabView control software. Corona discharge ionization and electrospray ionization sources are implemented and used to allow the analysis of both gaseous- and solution-phase samples during the characterization of the instrument. An upper mass/charge limit of approximately 450 Th with unit resolution was achieved using a 2.5-mm-internal radius cylindrical ion trap as the mass analyzer. The specificity of the instrument can be increased by employing the MS/MS capabilities of the ion trap and has been demonstrated for nitrobenzene. Limits of detection for the trace analysis in air of the chemical warfare agent simulant methyl salicylate (1.24 ppb) and for nitrobenzene (629 pptr) are achieved. The dynamic range of the instrument is currently limited to approximately 2 orders of magnitude by saturation of the detection electronics. Isolation and collision-induced dissociation efficiencies in MS/MS experiments both greater than 50% are reported. Electrospray/nanospray data are presented on solutions including 100 microM (D,L)-arginine, 10 microM (-)-ephedrine, and 10 microM lomefloxacin.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.006 | 0.004 |
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".