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Record W2329262645 · doi:10.1021/acs.iecr.5b00421

Carboxylic Acid-Functionalized Butyl Rubber: Synthesis, Characterization, and Physical Properties

2015· article· en· W2329262645 on OpenAlexafffund
Matthew J. McEachran, John F. Trant, Inderpreet Sran, John R. de Bruyn, Elizabeth R. Gillies

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNatural rubberPolymer chemistryMaterials scienceUltimate tensile strengthMethacrylateCarboxylic acidAtom-transfer radical-polymerizationChemical modificationPolymerizationDerivative (finance)Butyl rubberPolymerChemistryComposite material

Abstract

fetched live from OpenAlex

Polyisobutylene (PIB) and other PIB-based materials are of significant interest for a vast array of applications, but chemical modification is often required to obtain the desired properties. Described here are two new approaches for the preparation of carboxylic acid-functionalized PIB. The ring opening of cyclic anhydrides from an allylic alcohol derivative of butyl rubber and the atom transfer radical polymerization of tert -butyl methacrylate from a rubber derivative both ultimately afford carboxylated materials. These materials displayed significantly enhanced adhesion to stainless steel, as well as increased ultimate tensile strength and Young’s modulus in comparison to unmodified rubbers. Rheological studies suggested that they exhibit a greater degree of cross-linking-type behavior than the parent butyl rubber. Combined, these studies suggest that the properties of PIB can be readily tuned through synthetic modifications of the backbone, even at low mole percent, and that carboxylic acid moieties can impart desirable properties for various applications.

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 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)0.001
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 score0.018
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.117
GPT teacher head0.290
Teacher spread0.174 · 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 teacher head, 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

Citations23
Published2015
Admission routes2
Has abstractyes

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