Elimination of the helium requirement in high‐field asymmetric waveform ion mobility spectrometry (FAIMS): beneficial effects of decreasing the analyzer gap width on peptide analysis
Bibliographic record
Abstract
Cylindrical geometry high-field asymmetric waveform ion mobility spectrometry (FAIMS) focuses and separates gas-phase ions at atmospheric pressure and room (or elevated) temperature. Addition of helium to a nitrogen-based separation medium offers significant advantages for FAIMS including improved resolution, selectivity and sensitivity. Aside from gas composition, ion transmission through FAIMS is governed by electric field strength (E/N) that is determined by the applied voltage, the analyzer gap width, atmospheric pressure and electrode temperature. In this study, the analyzer width of a cylindrical FAIMS device is varied from 2.5 to 1.25 mm to achieve average electric field strengths as high as 187.5 Townsend (Td). At these electric fields, the performance of FAIMS in an N(2) environment is dramatically improved over a commercial system that uses an analyzer width of 2.5 mm in 1:1 N(2) /He. At fields of 162 Td using electrodes at room temperature, the average effective temperature for the [M+2H](2+) ion of angiotensin II reaches 365 K. This has a dramatic impact on the curtain gas flow rate, resulting in lower optimum flows and reduced turbulence in the ion inlet. The use of narrow analyzer widths in a N(2) carrier gas offers previously unattainable baseline resolution of the [M+2H](2+) and [M+3H](3+) ions of angiotensin II. Comparisons of absolute ion current with FAIMS to conventional electrospray ionization (ESI) are as high as 77% with FAIMS versus standard ESI-MS.
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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 | 0.000 | 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 | 0.001 |
| 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".