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Record W1993426721 · doi:10.1088/0960-1317/14/8/008

Joule heating effects on peak broadening in capillary zone electrophoresis

2004· article· en· W1993426721 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2004
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsJoule heatingCapillary electrophoresisChemistryDiffusionElectro-osmosisElectrophoresisCapillary actionDispersion (optics)Analytical Chemistry (journal)ViscosityJoule–Thomson effectZeta potentialThermodynamicsFlow (mathematics)MechanicsMaterials scienceChromatographyOpticsPhysicsNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Based on Taylor–Aris dispersion theory, a general analytical formula was derived for the theoretical plate height in capillary zone electrophoresis with the consideration of Joule heating effects. During the electrophoresis, the Joule heating causes a temperature rise and temperature gradients in the buffer solution. The temperature variations can affect the molecular diffusion, electroosmotic flow and electrophoretic flow via the temperature-dependent diffusion coefficient, dynamic viscosity and electrical conductivity. All these factors contribute to the peak broadening and are considered simultaneously in the present general model. The general formula derived in this paper is employed to discuss quantitatively the peak broadening in the presence of Joule heating effects. This formula can be easily extended to capillary zone electrophoresis with higher zeta potentials, if an approximate solution to Poisson–Boltzmann equation is employed.

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.

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)
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 score0.023
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)0.0000.000

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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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