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Record W3085566412 · doi:10.1103/physreve.102.032802

Universal dynamics of coarsening during polymer-polymer thin-film spinodal dewetting kinetics

2020· article· en· W3085566412 on OpenAlexaff
Jyotsana Lal, Laurence Lurio, D. Liang, Suresh Narayanan, Seth B. Darling, Mark Sutton

Bibliographic record

VenuePhysical review. E · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsMcGill University
FundersArgonne National LaboratoryOffice of ScienceU.S. Department of Energy
KeywordsDewettingSpinodalMaterials scienceSpinodal decompositionChemical physicsScatteringTime evolutionPolymerDynamic light scatteringStatistical physicsCondensed matter physicsThin filmPhysicsOpticsNanotechnologyPhase (matter)

Abstract

fetched live from OpenAlex

The dewetting dynamics of a supported bilayer polymer thin film on a solid substrate is investigated using grazing incidence x-ray photon correlation spectroscopy. We find that the top layer dewets via the spinodal mechanism. The kinetics of the dewetting is studied by monitoring the time evolution of the surface diffuse x-ray scattering intensity. We study the time evolution of fluctuations about the average surface structure by measuring the two-time x-ray intensity fluctuation correlation functions. Using these two-time correlation functions we quantify the crossover from early-time diffusive dynamics to hydrodynamics. The early diffusive regime satisfies dynamic universality. The two-time correlation functions also quantify the onset of hydrodynamic effects. The hydrodynamic regime is observed during the spinodal dewetting process as these interactions are not screened.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 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

Citations8
Published2020
Admission routes1
Has abstractyes

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