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Record W4413478645 · doi:10.1039/d5sm00497g

Shear-induced softening in fumed silica-reinforced silicone

2025· article· en· W4413478645 on OpenAlex

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

VenueSoft Matter · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsDow Chemical (Canada)
Fundersnot available
KeywordsFumed silicaSofteningMaterials scienceSiliconeComposite materialShear (geology)

Abstract

fetched live from OpenAlex

Fumed silica is widely used as a reinforcing filler and rheology modifier for polymer composites. Untreated, hydrophilic fumed silica formulated into silicone polymer typically leads to a stiff, brittle material due to strong association between the silica surface silanol and the siloxane backbone. However, this hydrophilic silica/silicone mixture can be sheared into a flowable material, with comparable rheological behaviour to a mixture of silicone polymer and a hydrophobically modified silica. In this work, we utilize various characterization techniques such as rheology, bound polymer test, and differential scanning calorimetry (DSC) to understand the mechanism by which agitation softens the hydrophilic silica/silicone mixture. The combined observations indicated the role of shear induced rearrangement of bound polymer bridging the silica particles to drive the rheological behaviour of this kinetically arrested system.

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 score0.142
Threshold uncertainty score0.917

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)0.0010.000

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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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