Fluorescence Imaging for Visualization of the Ion Cloud in a Quadrupole Ion Trap Mass Spectrometer
Bibliographic record
Abstract
Laser-induced fluorescence is used to visualize populations of gaseous ions stored in a quadrupole ion trap (QIT) mass spectrometer. Presented images include the first fluorescence image of molecular ions collected under conditions typically used in mass spectrometry experiments. Under these "normal" mass spectrometry conditions, the radial (r) and axial (z) full-width at half maxima (FWHM) of the detected ion cloud are 615 and 214 μm, respectively, corresponding to ~6% of r0 and ~3% of z0 for the QIT used. The effects on the shape and size of the ion cloud caused by varying the pressure of helium bath gas, the number of trapped ions, and the Mathieu parameter q z are visualized and discussed. When a "tickle voltage" is applied to the exit end-cap electrode, as is done in collisionally activated dissociation, a significant elongation in the axial, but not the radial, dimension of the ion cloud is apparent. Finally, using spectroscopically distinguishable fluorophores of two different m/z values, images are presented that illustrate stratification of the ion cloud; ions of lower m/z (higher qz) are located in the center of the trapping region, effectively excluding higher m/z (lower qz) ions, which form a surrounding layer. Fluorescence images such as those presented here provide a useful reference for better understanding the collective behavior of ions in radio frequency (rf) trapping devices and how phenomena such as collisions and space-charge affect ion distribution.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".