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Record W2322367262 · doi:10.1021/ac201207t

Thermal Modulation for Multidimensional Liquid Chromatography Separations Using Low-Thermal-Mass Liquid Chromatography (LC)

2011· article· en· W2322367262 on OpenAlexaff
Matthias Verstraeten, Matthias Pursch, Patric Eckerle, Jim Luong, Gert Desmet

Bibliographic record

VenueAnalytical Chemistry · 2011
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsDow Chemical (Canada)
Fundersnot available
KeywordsChemistryThermal desorptionChromatographyAnalytical Chemistry (journal)AnalyteMass spectrometryThermalGas chromatographyTwo-dimensional chromatographyModulation (music)DesorptionAdsorption

Abstract

fetched live from OpenAlex

We report on a proof-of-principle experiment with a novel thermal modulation device with potential use in two-dimensional liquid chromatography (LC × LC) systems. It is based on the thermal desorption concept used in two-dimensional gas chromatography (GC × GC) systems. Preconcentration of neutral analytes eluting from the first dimension column is performed in a capillary "trap" column packed with highly retentive porous graphitic carbon particles, placed in an aluminum low-thermal-mass LC heating sleeve. Remobilization of the trapped analytes is achieved by rapidly heating the trap column, by applying temperature ramps up to +1200 °C/min. Compared to the nonmodulated signal, the presented thermal modulator yielded narrow peaks, and a concentration enhancement factor up to 18 was achieved. With a thermally modulated LC separation of an epoxy resin, it is shown that when the thermal modulation is applied periodically, the trapped and concentrated molecules can be released periodically and that the modulating interface can both serve as a preconcentration device and as an injector for the second dimension column of an LC × LC setup. Because of the thermal modulation, a high-molecular-weight epoxy resin could be adequately separated and the different fractions were identified with a GPC analysis, as well as an offline second dimension LC analysis.

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 score0.071
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.265
Teacher spread0.238 · 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

Citations47
Published2011
Admission routes1
Has abstractyes

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