A Radio Frequency Ion Guide for Transporting Cooled Ions Through Differential Vacuum Stages: Design and Simulation
Bibliographic record
Abstract
In order to transport ions from an intermediate-pressure collisional cooling device to a planar electrostatic ion trap (PEIT) mass analyzer in an ultrahigh-vacuum chamber, a segmented radio frequency (RF) quadrupole system was designed and investigated by using an ion optical simulation. Two gas-flow-limiting units were employed in the system, allowing the differential pumping to establish a pressure difference of 7 orders of magnitude. Flow-limiting units including a plain aperture lens and 3 small quadrupoles in different shapes were investigated, and the transmission efficiency and energy distribution of the transported ions were evaluated. The small quadrupoles with conical front-ends inserted between the multiple segments gave the best transmission efficiency, and the collisional cooled ions can maintain their low energy distribution after being transported to the ultrahigh-vacuum stage. With an RF voltage amplitude of 200 V, the maximum transmission efficiency reached above 90%. After ions are cooled in the high-pressure quadrupole segment, the extraction voltage difference in high-pressure region needs to be low enough to avoid reheating the ions during the transport. It was found that an extraction voltage difference below 1.2 V can restrict the half width of the energy spread within 0.5 eV, which is required by PEIT to get ultrahigh mass resolution.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".