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Record W2315663659 · doi:10.1021/ma4017696

Dynamics near Free Surfaces and the Glass Transition in Thin Polymer Films: A View to the Future

2013· article· en· W2315663659 on OpenAlexafffund
M. D. Ediger, James A. Forrest

Bibliographic record

VenueMacromolecules · 2013
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsGlass transitionPolymerThin filmNanometreChemical physicsMaterials scienceFree surfaceMeasure (data warehouse)NanotechnologyChemistryComposite materialThermodynamicsPhysicsComputer science

Abstract

fetched live from OpenAlex

Abstract The past 20 years have seen a substantial effort to understand dynamics and the glass transition in thin polymer films. In this Perspective, we consider developments in this field and offer a consistent interpretation of some major findings. We discuss recent experiments that directly measure mobility at or near the surface of glassy polymers. These experiments indicate that enhanced mobility near the free surface can exceed bulk mobility by several orders of magnitude and extend for several nanometers into the bulk polymer. Enhanced mobility near the free surface allows a qualitative understanding of many of the observations of a reduced glass transition temperature Tg in thin films. For thin films, knowledge of Tg by itself is less useful than for bulk materials. Because of this, new experimental methods that directly measure important material properties are being developed.

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)0.003
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0030.013
Open science0.0010.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.191
Teacher spread0.187 · 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 designSimulation or modeling
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

Citations512
Published2013
Admission routes2
Has abstractyes

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