Nanoelectrospray emitters: Trends and perspective
Bibliographic record
Abstract
The benefits of electrospray ionization are many, including sensitivity, robustness, simplicity and the ability to couple continuous flow methods with mass spectrometry. The technique has seen further improvement by lowering flow rates to the nanoelectrospray regime (<1,000 nL/min), where sample consumption is minimized and sensitivity increases. The move to nanoelectrospray has required a shift in the design of the electrospray source which has mostly involved the emitter itself. The emitter has seen an evolution in architecture as the shape and geometry of the device have proved pivotal in the formation of sufficiently small droplets for sensitive MS detection at these flow rates. There is a clear movement toward the development of emitters that produce multiple Taylor cones. Such multielectrospray emitters have been shown to provide enhanced sensitivity and sample utilization. This article reviews the development of nanoelectrospray emitters, including factors such as geometry and the manner of applying voltage. Designs for emitters that take advantage of multielectrospray are emphasized.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".