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Record W4417066742 · doi:10.1103/qyqb-9c57

Dynamics from the Surface to the Bulk in Ultrastable and Liquid-Cooled Oligomeric Glasses

2025· article· en· W4417066742 on OpenAlexafffund
Iain McKenzie, Victoria L. Karner, Ruohong Li, W. A. MacFarlane, G. D. Morris, Michael Thees, John O. Ticknor, James A. Forrest

Bibliographic record

VenuePhysical Review Letters · 2025
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityUniversity of WaterlooTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaTRIUMF
KeywordsGlass transitionMolecular dynamicsDynamics (music)NanosecondDispersityThermalSupercoolingAmorphous solidStyrene

Abstract

fetched live from OpenAlex

Ultrastable glasses (USGs) exhibit strikingly different properties from liquid-cooled normal glasses (NGs), yet their molecular dynamics remain poorly understood. Using β-detected NMR of implanted spin-polarized ^{8}Li^{+}, we directly track the depth and temperature dependence of the γ relaxation-phenyl ring twisting-in highly monodisperse atactic styrene oligomers. Near the bulk glass transition temperature T_{g}, USGs show much faster surface dynamics but slower bulk dynamics than an NG. Cooling below T_{g} reveals a sharp crossover at T^{*}, where surface dynamics vitrify on tens to hundreds of nanosecond timescales and become slower than in the bulk. The NG further displays two distinct T^{*} values near the surface, pointing to heterogeneous local structure. Despite these differences, all dynamics obey entropy-enthalpy compensation, suggesting a common molecular mechanism. These results show that preparation and thermal history lock styrene oligomeric glasses into distinct regions of the potential energy landscape, giving rise to fundamentally different glassy dynamics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.256

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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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