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Record W1964521963 · doi:10.1063/1.2766844

Tracking polymer diffusion in a wet latex film with fluorescence resonance energy transfer

2007· article· en· W1964521963 on OpenAlexaff
Jeffrey C. Haley, Yuanqin Liu, Mitchell A. Winnik, David Demmer, T. L. Haslett, Willie Lau

Bibliographic record

VenueReview of Scientific Instruments · 2007
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFörster resonance energy transferPolymerMaterials scienceDiffusionAcceptorCopolymerTracking (education)FluorescenceComposite materialOpticsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

We describe an instrument to measure the polymer interdiffusion between donor-labeled and acceptor-labeled latex polymers in a partially wet latex film with fluorescence resonance energy transfer (FRET). It is possible to temporarily arrest the drying process of a wet latex film by sealing the film in an airtight chamber. In our approach, we measure donor fluorescence decays from 0.5 mm diameter spots at various positions across an arrested latex film with time-correlated single photon counting. We interpret the resulting decays with a Monte Carlo simulation of the FRET process and extract information about the extent of polymer diffusion as a function of position on the film. These results enable us to determine the extent of polymer interdiffusion as a function of distance from the wet-dry edge in the latex film. To highlight this device's ability to capture the rapid early stages of latex interdiffusion, we report results from an acrylate copolymer latex.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

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