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Record W2069781730 · doi:10.1002/marc.201300640

Fast Optical Healing of Crystalline Polymers Enabled by Gold Nanoparticles

2013· article· en· W2069781730 on OpenAlex
Hongji Zhang, Daniel Fortin, Hesheng Xia, Yue Zhao

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

VenueMacromolecular Rapid Communications · 2013
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials sciencePolymerColloidal goldNanoparticleSurface plasmon resonanceCrystalliteRecrystallization (geology)Ethylene oxidePolyethyleneComposite materialNanotechnologyChemical engineeringOpticsCopolymerMetallurgy

Abstract

fetched live from OpenAlex

A general method for very fast and efficient optical healing of crystalline polymers is reported. By loading a very small amount of gold nanoparticles (AuNPs) in either poly(ethylene oxide) (Tm ≈ 63 °C) or low-density polyethylene (Tm ≈ 103 °C), the heat released upon surface plasmon resonance (SPR) absorption of 532 nm light by AuNPs can melt crystallites in the interfacial region of two polymer pieces brought into contact; and the subsequent recrystallization of polymer chains on cooling merges the two pieces into one. The fracture strength of such repaired sample can reach the level of the undamaged polymer after 10 s laser exposure. Moreover, in addition to an ability of long-distance remote and spatially selective healing, the optical method also works for polymer samples immersed in water.

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 score0.022
Threshold uncertainty score0.741

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 science0.0010.001
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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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