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Record W4409009826 · doi:10.1021/acsapm.5c00222

Hydrophosphinated Styrene–Butadiene Rubber: Improving Automotive Tire Performance

2025· article· en· W4409009826 on OpenAlexafffund
Ian C. Watson, Alexander E. R. Watson, Gabrielle A. Tellier, Benjamin Gutschank, Thomas Rünzi, Thomas Groß, Gilles Arsenault, Paul J. Ragogna, Joe B. Gilroy

Bibliographic record

VenueACS Applied Polymer Materials · 2025
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaWestern UniversityCanada Foundation for InnovationSolvay
KeywordsNatural rubberAutomotive industryStyrene-butadieneMaterials scienceComposite materialAutomotive engineeringStyreneEngineeringCopolymerPolymerAerospace engineering

Abstract

fetched live from OpenAlex

Styrene–butadiene rubber (SBR) was functionalized using the phosphane–ene reaction, resulting in the installation of phosphines at the alkene functional groups within and pendant to the polymer backbone. Secondary phosphines, including diphenylphosphine (HPPh 2 ), dicyclohexylphosphine (HPCy 2 ), di- iso -butylphosphine (HP i Bu 2 ), and di- tert -butylphosphine (HP t Bu 2 ) were studied in this context, and the progress of these reactions was monitored by 1 H and 31 P{ 1 H} NMR spectroscopy. The most efficient functionalization was achieved when HP i Bu 2 was employed. The inclusion of phosphines influenced the resulting polymer’s thermal properties, decreasing the temperature required for thermal decomposition and raising the T g of the polymers. Large-scale (>200 g) batches of hydrophosphinated styrene–butadiene rubber (PSBR) rubber were produced using HP i Bu 2 and subsequently subjected to vulcanization conditions and testing standard to the automotive tire industry. The results indicated that the vulcanizate produced from PSBR containing 0.5% phosphorus would yield tire treads with improved wet traction and rolling resistance characteristics compared to vulcanizates prepared from the parent SBR. These results defy traditional limitations associated with the “magic triangle” of automotive tire characteristics, whereby gains in performance in one area (e.g., one of traction, rolling resistance, or resistance to degradation) are traditionally accompanied by losses in performance in the others.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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