A study of the performance of an ion shutter for drift tubes in atmospheric pressure ion mobility spectrometry: Computer models and experimental findings
Bibliographic record
Abstract
Ion mobility spectra are initiated when ions, derived from a sample, are pulsed or injected through ion shutters into a drift region. The effect on signal intensity from electric fields arising from the shutter grids (E(s)) and a superimposed electric field of the drift tube (E(d)) was determined experimentally and simulated computationally for ion motion at ambient pressure. The combination of these two fields influenced shutter performance in three ways: (1) intensity of an ion peak was suppressed by increased current in the baseline due to continuous leakage of ions into the drift region from insufficient E(s) to block ion motion when needed, at a given value of E(d); (2) the ion shutter provided maximum peak intensity with some optimal ratio of E(s)/E(d) when ions were fully blocked except using the injection time; (c) the signal intensity was reduced when the blocking voltage of the ion shutter exceeded this optimal E(s)/E(d) ratio from ion depletion at the shutter grids. The optimal ratio from the computer models was equal to 1.50, whereas a value of 2.50 was obtained from the experimental findings. This difference was attributed to nonideal geometry with the grids of the shutter and the conducting elements in the drift tube establishing both E(s) and E(d). As both the experimental and modeling results demonstrated, a mobility dependence of ion yield from the ionization source was found to cause a mobility dependent ion signal at the collector electrode.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".