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Record W2009409443 · doi:10.1021/jp0476951

Dielectric Polarization and the Stages of a Macromolecule's Growth

2004· article· en· W2009409443 on OpenAlexaff
K. Venkateshan, G. P. Johari

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2004
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMacromoleculeDielectricDipoleDiglycidyl etherConductivityMaterials scienceRelaxation (psychology)Dielectric spectroscopyPermittivityChemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

To investigate the change in the orientation polarization, particularly during the growth of a macromolecule by addition reactions in a liquid, dielectric relaxation spectra of diglycidyl ether of bisphenol A have been studied in real time. It is found that in the plot of the dielectric permittivity, ε ‘, measured at a fixed frequency against the polymerization time, the first step of the (inverted) sigmoid-shape part of the spectrum resembling a relaxational decrease is a dc conduction effect. After this effect vanishes, the equilibrium permittivity, ε s, of the liquid increases with time as covalently bonded molecular clusters form at random sites in the bulk liquid, and the dipole orientational correlation increases as a result of hydrogen bonding between the newly formed OH groups. Thereafter, the macromolecule's continuous growth in the liquid decreases the net dipole moment of the covalently bonded network, which decrease ε s . Thus, after the conductance effect has become negligible, a plot of ε s against the polymerization time shows a maximum. Both the dc conductivity, σ 0, and the distribution parameter for dielectric relaxation decrease with time, and σ 0 follows a scaling equation for gelation. The irreversible increase in relaxation time during a macromolecule's growth is explained in terms of a decrease in the configurational entropy, and a relation between the two is provided.

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 score0.009
Threshold uncertainty score0.097

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 head0.004
GPT teacher head0.199
Teacher spread0.195 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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