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Record W2152582231 · doi:10.1002/marc.201500123

Dual Sulfide–Disulfide Crosslinked Networks with Rapid and Room Temperature Self‐Healability

2015· article· en· W2152582231 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

VenueMacromolecular Rapid Communications · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsConcordia University
Fundersnot available
KeywordsPolysulfideSelf-healingSulfideMaterials sciencePolymerDisulfide bondViscoelasticityPolymer chemistryThiolChemical engineeringChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Polymer-based crosslinked networks with intrinsic self-repairing ability have emerged due to their built-in ability to repair physical damages. Here, novel dual sulfide-disulfide crosslinked networks (s-ssPxNs) are reported exhibiting rapid and room temperature self-healability within seconds to minutes, with no extra healing agents and no change under any environmental conditions. The method to synthesize these self-healable networks utilizes a combination of well-known crosslinking chemistry: photoinduced thiol-ene click-type radical addition, generating lightly sulfide-crosslinked polysulfide-based networks with excess thiols, and their oxidation, creating dynamic disulfide crosslinkages to yield the dual s-ssPxNs. The resulting s-ssPxN networks show rapid self-healing within 30 s to 30 min at room temperature, as well as self-healing elasticity with reversible viscoelastic properties. These results, combined with tunable self-healing kinetics, demonstrate the versatility of the method as a new means to synthesize smart multifunctional polymeric materials.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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