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Record W2021052195 · doi:10.1021/ac901026t

Microstructured Photonic Fibers as Multichannel Electrospray Emitters

2009· article· en· W2021052195 on OpenAlexafffund
Shuqin Su, Graham T. T. Gibson, Samuel M. Mugo, Dale M. Marecak, Richard D. Oleschuk

Bibliographic record

VenueAnalytical Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsQueen's University
FundersOntario Innovation Trust
KeywordsChemistryElectrosprayReagentAqueous solutionChromatographyElectrospray ionizationFluidicsVolumetric flow rateNanotechnologyAnalytical Chemistry (journal)Mass spectrometryOrganic chemistry

Abstract

fetched live from OpenAlex

Novel multichannel electrospray emitters are presented that use silica-based microstructured fibers (MSFs) to split the flow allowing efficient desolvation during electrospray. The MSFs investigated in this study possess 30-168 individual fluidic channels (each channel being 5 microm in diameter) that form a 2D emitting array. Multiple flow paths afford stable electrospray at flow rates ranging from the microspray (e.g., 1000 nL/min) to the nanoelectrospray (e.g., 10 nL/min) regime with moderate to negligible flow-induced backpressures. The electrospray stability of highly aqueous solutions (up to 99.9% water with 0.1% acetic acid) is enhanced through modification of the emitting surface with a hydrophobic silylation reagent (chlorotrimethylsilane). Furthermore, by successfully spraying highly concentrated salt solutions, this study demonstrates that multichannel MSF emitters provide enhanced robustness to clogging, leading to increased operational throughput.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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.

Opus teacher head0.006
GPT teacher head0.257
Teacher spread0.251 · 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 teacher head, not a consensus.

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

Citations38
Published2009
Admission routes2
Has abstractyes

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