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Record W1990049255 · doi:10.1039/c4sm02245a

Enhanced high-frequency molecular dynamics in the near-surface region of polystyrene thin films observed with β-NMR

2015· article· en· W1990049255 on OpenAlexaff
Iain McKenzie, Chad Daley, R. F. Kiefl, C. D. P. Levy, W. A. MacFarlane, G. D. Morris, M. R. Pearson, Dong Wang, James A. Forrest

Bibliographic record

VenueSoft Matter · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British ColumbiaSimon Fraser UniversityUniversity of WaterlooTRIUMF
Fundersnot available
KeywordsPolystyreneRelaxation (psychology)Molecular dynamicsPolymerMaterials scienceGlass transitionDeuteriumCondensed matter physicsSpin–lattice relaxationChemical physicsLarmor precessionDynamics (music)Molecular physicsNuclear magnetic resonanceChemistryMagnetic fieldAtomic physicsPhysicsComputational chemistryComposite material

Abstract

fetched live from OpenAlex

β-detected nuclear spin relaxation of (8)Li(+) has been used to probe the depth dependence of molecular dynamics in high- and low-molecular-weight deuterated polystyrene. The average nuclear spin-lattice relaxation rate, 1/T(avg)(1), is a measure of the spectral density of the polymer motion at the Larmor frequency (41 MHz at 6.55 T). In both samples, 1/T(avg)(1) is depth independent below ∼200 K but above this temperature it decreases approximately exponentially with distance from the free surface, returning to bulk behavior for depths greater than ∼10 nm. This is direct evidence for a region near the free surface with enhanced molecular dynamics compared with the bulk. The effective thickness of the surface region increases with increasing temperature and is finite even above the glass transition. These results present challenges for the current understanding of dynamics near the surface of polymer glasses.

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 score0.055
Threshold uncertainty score0.393

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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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

Citations23
Published2015
Admission routes1
Has abstractyes

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