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Record W1993910293 · doi:10.1063/1.2799940

Temperature scanning small angle x-ray scattering measurements of structural relaxation in type-III vitreous silica

2007· article· en· W1993910293 on OpenAlexafffund
Ralf Brüning, Claire Levelut, Rozenn Le Parc, Annelise Faivre, Lynne Semple, Michel Vallée, J. P. Simon, Jean‐Louis Hazemann

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsMount Allison University
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Synchrotron Radiation Facility
KeywordsAnnealing (glass)Decoupling (probability)Relaxation (psychology)ScatteringGlass transitionAnalytical Chemistry (journal)Atmospheric temperature rangeMaterials scienceChemistryThermodynamicsOpticsComposite materialChromatographyPolymer

Abstract

fetched live from OpenAlex

The fictive temperature of vitreous silica containing approximately 900wtppm of hydroxyl groups was monitored with small angle x-ray scattering. The measurements were carried out during annealing and while scanning the temperature, with annealing temperatures ranging between 930 and 1330K. Fitting the data to the Adam-Gibbs-Fulcher equation by using the Tool-Narayanaswamy method yields a particularly simple thermorheological behavior for type-III vitreous silica. Unlike the general case for glass kinetics, including vitreous silica with low hydroxyl content, the relaxation time constant is nearly decoupled from the fictive temperature. This high degree of decoupling of the state of the glass and the relaxation rate agrees with the results of viscosity measurements. By improving the data analysis procedure, we have significantly increased the precision of the results, and it was possible to resolve changes of the activation energy of the relaxation processes to within 0.5%. This has made sample aging effects that had previously been undetectable visible.

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 score0.015
Threshold uncertainty score0.325

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 head0.028
GPT teacher head0.250
Teacher spread0.222 · 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

Citations9
Published2007
Admission routes2
Has abstractyes

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