Dipole Excitation: A New Method for Mass Analysis with a Quadrupole Mass Filter
Bibliographic record
Abstract
Trajectory calculations are used to investigate peak shapes and ion transmission with a proposed new method of mass analysis with a quadrupole mass filter. Dipole excitation is applied to either the x or the y electrodes, or both, to create bands of instability within the first stability region. With excitation between the y electrodes (near β y = 0), ions are removed from the low mass side of a peak, and with ion excitation in x (near β x = 1), ions are removed from the high mass side. The mass resolution can be approximately doubled with comparatively little loss in ion transmission. Ion motion in an ideal quadrupole field and in the field of a quadrupole constructed with round rods has been studied. With an ideal quadrupole field, excitation in y is found to give better peak shape and resolution than excitation in x. With quadrupoles constructed with round rods, excitation in y is found to remove ions from both the low and high mass sides of a peak. The additional higher order multipoles introduced to the quadrupole potential by the use of round rods couple the x motion to the y motion so that exciting the y motion also excites ions in x. Thus, only excitation in y is necessary. Both with an ideal quadrupole field and quadrupoles constructed with round rods, the resolution can be increased ca. ×2 with little loss of transmission. Graphical Abstract ᅟ.
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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 | 0.000 | 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) | 0.009 | 0.003 |
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".