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Record W4243961246 · doi:10.26434/chemrxiv.12959885.v1

Polyvinylidene Difluoride: A Universal Binder for Preparation of Solid Phase Microextraction Devices

2020· preprint· en· W4243961246 on OpenAlexafffund
Varoon Singh, Chiranjit Ghosh, Avneet Kaur, Janusz Pawliszyn

Bibliographic record

VenueChemRxiv · 2020
Typepreprint
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolid-phase microextractionSorbentMaterials sciencePolymerExtraction (chemistry)CoatingChemical engineeringChromatographySample preparationMembraneAdsorptionChemistryOrganic chemistryNanotechnologyGas chromatography–mass spectrometryComposite materialMass spectrometry

Abstract

fetched live from OpenAlex

The communication describes the application of a fluorocarbon-based polymer as a high performance binder component for coatings suitable for a variety of solid phase microextraction (SPME) configurations. SPME devices are characterized by their ability to perform physicochemical extraction of chemical compounds from a given sample, rending said chemical compounds suitable for instrumental determinations; fundamentally speaking, physiochemical extraction is accomplished by thermodynamic equilibrium driven by diffusion and partitioning of chemical compounds. A polyvinylidene difluoride (PVDF) polymer was used to immobilize various sorbent particles on different supports to create different formats of SPME, namely fiber, thin-film membrane, and CBS devices. In this report, PVDF-based coatings are introduced as universal SPME coatings that are amenable to both gas chromatography (GC) and liquid chromatography (LC) while also improving the physical stability of the resulting device, in addition to eliminating the need for highly toxic reagents associated with the preparation of fully fluorinated based coatings previously reported in the literature. Additional incorporation of other polymers to increase coating porosity as well as the adhesion of PVDF on metal surfaces is also described.

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)
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 score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.386
Teacher spread0.329 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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