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Record W2327391466 · doi:10.1021/ac1017953

Asymmetrical Emitter Geometries for Increased Range of Stable Electrospray Flow Rates

2010· article· en· W2327391466 on OpenAlexafffund
E. Jane Maxwell, Xuefei Zhong, David D. Y. Chen

Bibliographic record

VenueAnalytical Chemistry · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryElectrosprayBevelCommon emitterVolumetric flow rateElectrospray ionizationAnalytical Chemistry (journal)Electric fieldIonizationElectrodeMass spectrometryOptoelectronicsMechanicsChromatographyIonMaterials science

Abstract

fetched live from OpenAlex

Because electric field distribution is determined by emitter size and shape, sprayer tip geometry determines the optimum liquid flow rate that can be processed by the electrospray ionization interface. Electric field is the highest at the sharpest edge of an electrode; therefore, for a beveled tip, the field is highest at the very tip, and for a conventional symmetrically tapered tip, the field is the highest around the rim of the electrode. Electrospray performance as a function of flow rate was investigated using both continuous infusion and peak-based analysis. The sharpest symmetrical emitter gave the most stable electrospray ionization (ESI) at flow rates ≤0.10 μL/min, while beveled emitters provided significantly better performance at expanded flow rates up to 1 μL/min. The use of beveled emitters offers the potential for increased versatility in electrospray ionization interfaces.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.004
GPT teacher head0.212
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2010
Admission routes2
Has abstractyes

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