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Univalent salts as modifiers in micellar capillary electrophoresis

2002· article· en· W2050152113 on OpenAlexaff
David G. McLaren, Olivier Boulat, David D. Y. Chen

Bibliographic record

VenueElectrophoresis · 2002
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryMicelleSalt (chemistry)ChromatographyCounterionCapillary electrophoresisSodium dodecyl sulfateElectrolyteSodiumAnalyteInorganic chemistryIonAnalytical Chemistry (journal)Aqueous solutionOrganic chemistry

Abstract

fetched live from OpenAlex

The influence of three univalent salts (LiCl, NaCl and RbCl) on the separation of amino acids labelled with 3-(4-carboxybenzoyl)-quinoline-2-carboxaldehyde (CBQCA) in micellar capillary electrophoresis has been studied. Capacity factors for a series of eight CBQCA-labelled amino acids in a sodium dodecyl sulfate (SDS) micellar system containing different concentrations of salt were measured and were found to be related to both the hydrodynamic radius of the salt counter-ion (Li(+), Na(+), Rb(+)) and the relative hydrophobicity of the amino acid. Affinities of the analytes for the micelles were generally observed to decrease as the salt concentration in the background electrolyte was increased from 10 to 50 mM. This decrease in affinity was greatest in the presence of the salt counter-ion with the smallest hydrodynamic radius and is primarily due to an increased resistance to mass transfer. Furthermore, interaction of hydrophobic analytes with the micelles is greater than that of hydrophilic analytes at all salt concentrations due to the greater strength of the hydrophobic interactions and this effect is also enhanced in the presence of a smaller counter-ion. No negative effects due to Joule heating or electromigrative dispersion were observed for low to moderate concentrations of salt, which suggests that the use of simple univalent salts to modify analyte/micelle affinities can be a practical method for improving the separation of complex mixtures.

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 categoriesInsufficient payload (model declined to judge)
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 score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.006
GPT teacher head0.177
Teacher spread0.171 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2002
Admission routes1
Has abstractyes

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