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Record W2132291511 · doi:10.1103/physrevlett.95.268301

Tailoring the Flow of Soft Glasses by Soft Additives

2005· article· en· W2132291511 on OpenAlex
Emanuela Zaccarelli, Christian Mayer, Anthi Asteriadi, Christos N. Likos, Francesco Sciortino, Jacques Roovers, Hermis Iatrou, Nikos Hadjichristidis, P. Tartaglia, Hartmut Löwen, D. Vlassopoulos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Review Letters · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsMaterials scienceSoft materialsFlow (mathematics)Soft drinkFlow propertiesSoft tissueSoft matterNanotechnologyMechanicsPhysicsChemistryPhysical chemistryMedicine

Abstract

fetched live from OpenAlex

We examine the vitrification and melting of asymmetric star polymer mixtures by combining rheological measurements with mode coupling theory. We identify two types of glassy states, a single glass, in which the small component is fluid in the glassy matrix of the big one, and a double glass, in which both components are vitrified. Addition of small-star polymers leads to melting of both glasses, and the melting curve has a nonmonotonic dependence on the star-star size ratio. The phenomenon opens new ways for externally steering the rheological behavior of soft matter systems.

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.

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 score0.424
Threshold uncertainty score0.221

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 head0.286
Teacher spread0.268 · 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