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Record W1963655924 · doi:10.1021/ma0014618

Influence of Entanglements on the Time Dependence of Mixing in Nonradiative Energy Transfer Studies of Polymer Diffusion in Latex Films

2001· article· en· W1963655924 on OpenAlexaff
Ewa Odrobina, Mitchell A. Winnik

Bibliographic record

VenueMacromolecules · 2001
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiffusionPolymerScalingFick's laws of diffusionMonomerChemistryAcceptorActivation energyThermodynamicsAnalytical Chemistry (journal)Chemical physicsPolymer chemistryMaterials sciencePhysical chemistryPhysicsCondensed matter physicsOrganic chemistry

Abstract

fetched live from OpenAlex

We report energy transfer experiments on poly(butyl methacrylate) (PBMA) latex films prepared from a 1:1 mixture of donor- and acceptor-labeled latex particles. In one set of samples, the particles contain low molecular weight polymer ( M w = 34 000) comparable to the entanglement molecular weight ( M e ) of PBMA. For this sample, the extent of mixing f m (defined as the fractional increase in the energy transfer quantum yield) increased with time as t 1/2, consistent with diffusion that follows Fick's law. In the second set of experiments, involving polymer with M w = 380 000 ( M w > 10 M e ), we observe a change in the time dependence of f m . At early times, for values of f m < 0.2, f m scales as t 1/2 . There is a sharp crossover to a t 1/4 scaling relationship for values of f m > 0.2. The most likely explanation of the early-time behavior is Fickian diffusion of the lowest molecular weight components of the broadly disperse polymer ( M w / M n = 3). The scaling of f m with t 1/4 does not appear to be consistent with the predictions of the theory of polymer diffusion across interfaces. The parameter f m is a measure of the number of monomers crossing the interface N ( t ). For diffusion across a planar interface, N ( t ) is predicted to increase as t 3/4 if the chain ends are uniform and as t 1/2 if they are segregated to the interface.

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 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 score0.004
Threshold uncertainty score0.284

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 integrity0.0000.000
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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.

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
Published2001
Admission routes1
Has abstractyes

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