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Record W2317664517 · doi:10.1021/cm504784e

Polymer Network Formation Using the Phosphane–ene Reaction: A Thiol–ene Analogue with Diverse Postpolymerization Chemistry

2015· article· en· W2317664517 on OpenAlexafffund
Ryan Guterman, Amir Rabiee Kenaree, Joe B. Gilroy, Elizabeth R. Gillies, Paul J. Ragogna

Bibliographic record

VenueChemistry of Materials · 2015
Typearticle
Languageen
FieldChemistry
TopicOrganoboron and organosilicon chemistry
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsEne reactionChemistryPhosphinePolymerThiolRedoxDerivatizationNuclear magnetic resonance spectroscopyClick chemistryPolymer chemistryOrganic chemistryCombinatorial chemistryCatalysis

Abstract

fetched live from OpenAlex

Air-stable primary phosphines were photopolymerized using phosphane–ene chemistry, the phosphorus analogue of the thiol–ene reaction, to fabricate a completely new class of polymer networks. It was demonstrated that the tunable thermal and physical properties accessible using thiol–ene chemistry could also be achieved using an analogous phosphane–ene reaction. At the same time, the presence of the 31 P nucleus that is easily observed using NMR spectroscopy allowed the chemical structures of the networks to be directly probed using solid state NMR spectroscopy. Following its incorporation into the network, phosphorus offers the distinct difference and advantage of being able to undergo a diverse array of further derivatization to afford functional materials. For example, the networks were demonstrated to serve as effective oxygen scavengers and to bind transition metals (e.g., Pd). By using the air stable ferrocenyl phosphine (FcCH 2 CH 2 )PH 2, redox-active networks were produced and these materials could be pyrolyzed to yield magnetic ceramics. Overall, this demonstrates the promise of phosphane–ene chemistry as an alternative to thiol–ene systems for providing functional materials for a diverse range of 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)0.000
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 score0.003
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations49
Published2015
Admission routes2
Has abstractyes

Explore more

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