Hyphenation of Production-Scale Free-Flow Electrophoresis to Electrospray Ionization Mass Spectrometry Using a Highly Conductive Background Electrolyte
Bibliographic record
Abstract
In this technical note, we demonstrate the hyphenation of production-scale free-flow electrophoresis (FFE) and sheathless electrospray ionization mass spectrometry (ESI-MS). In contrast to previous hyphenation approaches, we used a highly conductive background electrolyte (BGE) required for production-scale FFE. We found that this kind of BGE as well as a production-scale setup leads to significant electric interference between FFE and MS. This interference prevents steady-state FFE operation. We examine this interference in detail and discuss possible solutions to this issue. We demonstrate that the straightforward grounding of the transfer line removes the influence of ESI-MS on FFE, but creates a current leak from the ESI interface, which adversely affects the ESI spray. Furthermore, we show that only the electrical disconnection of the ESI probe from the FFE-MS transfer line suppresses this undesirable current. In order to facilitate the electrical disconnection we used a low conductivity, silica-based ESI probe with withdrawn inner capillary. This approach allowed the interference-free hyphenation of production-scale FFE (using a highly conductive BGE) with 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".