Quadrupole mass filter operation with dipole direct current and quadrupole radiofrequency excitation
Bibliographic record
Abstract
RATIONALE: For mass analysis, a quadrupole mass filter (QMF) usually operates at the upper tip of the first stability region. We introduce a new mode of QMF operation with dipole direct current (dc) and with auxiliary quadrupole excitation. Before experimental investigation of this mode, we have carried out numerical simulations of this process. METHODS: Based on the analytical description of the equations of ion motion and mapping of stability islands, ion trajectory calculations are used to calculate peak shapes or mass filter transmission contours. Ions are given Gaussian distributions of initial positions in x and y, and thermal initial velocity distributions. The effects of the dipole dc in the y direction and auxiliary quadrupole excitation in the x and y directions are modeled. RESULTS: line. This allows control of the resolution with the removal of the low-mass tail of a peak thereby improving the isotopic abundance sensitivity by about two orders of magnitude. The operation of a QMF with high resolution (about 5000) and high transmission (20-25%) and with a relatively short sorting time of ions n = 150 radiofrequency (rf) cycles based on the use of dipole dc and quadrupole excitation is shown. CONCLUSIONS: A new mode of QMF operation with dipole direct current (dc) and with an auxiliary quadrupole is discussed. Using dc excitation allows control of the resolution with the removal of the low-mass tail of a peak. The method of operation of a quadrupole mass filter with high resolution (about 5000) and high transmission (20-25%) and a relatively short sorting time (150 rf cycles) based on the use of dipole dc and on quadrupole excitation is shown.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".