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Record W2142332521 · doi:10.1002/chem.201402877

Silicone Boronates Reversibly Crosslink Using Lewis Acid– Lewis Base Amine Complexes

2014· article· en· W2142332521 on OpenAlexafffund
Laura Dodge, Yunqing Chen, Michael A. Brook

Bibliographic record

VenueChemistry - A European Journal · 2014
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiliconeCovalent bondLewis acids and basesPolymer chemistryAmine gas treatingElastomerSilicone oilMaterials scienceThermoplastic elastomerChemistryOrganic chemistryCopolymerPolymerCatalysis

Abstract

fetched live from OpenAlex

Silicone elastomers are normally thermosets, which are not readily recycled or repurposed. The few examples of thermoplastic silicone elastomers depend on reversible covalent and non-covalent molecular interactions. It is demonstrated that amine-boronate complex formation provides a simple and flexible route to reversible crosslinked silicones. A variety of network structures were prepared by use of terminal and pendantly functionalised silicone boronates and amines. The crosslink density was quantified using a combination of Shore-hardness measurements, swelling, and rheological analyses. Stress induced by compressive force could be relieved through dynamic B-N bond reformation at 60 °C. Materials could be fully disassembled through introduction of n-butylamine and successfully reformed upon removal of the monofunctional amine by evaporation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations52
Published2014
Admission routes2
Has abstractyes

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