MétaCan
Menu
Back to cohort
Record W2047407157 · doi:10.1002/jssc.200900177

Dynamic control of split flow in packed column supercritical fluid chromatography using dual resistively heated restrictors

2009· article· en· W2047407157 on OpenAlexafffund
Jian Jun Li, Kevin B. Thurbide

Bibliographic record

VenueJournal of Separation Science · 2009
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistrySupercritical fluid chromatographyChromatographyPacked bedAnalytical Chemistry (journal)Isobaric processVolumetric flow rateFlame ionization detectorSupercritical fluidDetectorInjection portGas chromatographyFlow (mathematics)MechanicsMaterials scienceThermodynamicsComposite materialOptics

Abstract

fetched live from OpenAlex

Remote control of the vent/detector split flow ratio in packed column supercritical fluid chromatography (pSFC) with flame ionization detector (FID) is demonstrated using a dual heated restrictor method. Restrictors stemming from a Tee at the separation column outlet were, respectively, fixed into an FID and a vent port, and their individual temperatures were controlled using resistively heated wires. Subsequently, both system pressure and split flow could be manipulated. For example, for applied restrictor temperatures examined up to 600 degrees C, corresponding vent/FID split flow ratios between 2 and 7 were observed depending on the port heated. As well, column pressures around 16-23 MPa were also achievable over the same range. Conversely, isobaric altering of the split flow ratio was possible when opposing positive and negative temperature gradients were applied at the two restrictors. Under these conditions, the system pressure varied less than 1% RSD over a 10 min period. As an application, the method was used to establish stable detector operation in the analysis of n-alkanes under pSFC-FID conditions that initiated flame instability. Results indicate that this technique could be a relatively simple and inexpensive means of controlling system pressure and detector split flow ratios in pSFC-FID.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.014
GPT teacher head0.307
Teacher spread0.294 · 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

Citations2
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Separation ScienceSame topicAnalytical Chemistry and ChromatographyFrench-language works237,207