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Record W3113956943 · doi:10.1021/acs.macromol.0c02082

High Molar Mass Poly(alkylphosphinoboranes) <i>via</i> Iron-Catalyzed Dehydropolymerization

2020· article· en· W3113956943 on OpenAlexafffund
Diego A. Resendiz‐Lara, Vincent T. Annibale, Alastair W. Knights, Saurabh S. Chitnis, Ian Manners

Bibliographic record

VenueMacromolecules · 2020
Typearticle
Languageen
FieldChemistry
TopicOrganoboron and organosilicon chemistry
Canadian institutionsUniversity of Victoria
FundersH2020 Marie Skłodowska-Curie ActionsEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y TecnologíaCanada Research ChairsUniversity of Bristol
KeywordsMolar massChemistryPhosphineDifferential scanning calorimetryBoraneThermogravimetric analysisMonomerPolymerizationPolymer chemistryGel permeation chromatographyElectrospray ionizationCatalysisMass spectrometryNuclear chemistryOrganic chemistryPolymerChromatography

Abstract

fetched live from OpenAlex

High molar mass polyphosphinoboranes substituted with an alkyl group at phosphorus [RPH–BH 2 ] n (R = t Bu, 1-Ad, i Pr, Cy, n Hex, and Me) have been successfully prepared via dehydropolymerization of the phosphine–boranes RPH 2 ·BH 3 using an iron precatalyst, [CpFe(CO) 2 (OTf)] (100 °C, toluene, 2.0 M, 10–100 h). Substrate purity and the reaction conditions were found to be crucial in obtaining a high molar mass material as the major product ( M n = 18,200–57,200 g mol –1 and D̵ = 1.24–3.40). For example, the addition of small quantities of primary phosphines, a potential monomer contaminant, was found to lead to a lower molar mass oligomeric material [RPH–BH 2 ] x . Our experiments indicated that the added Lewis basic primary phosphine does not induce main-chain scission post-polymerization. In contrast, a phosphine-mediated termination process during the catalytic cycle appears to compete with the polymerization of the phosphine–borane monomer. The resulting poly(alkylphosphinoboranes) were characterized by multinuclear NMR spectroscopy, gel permeation chromatography, and electrospray ionization mass spectrometry. The thermal properties were also investigated by thermogravimetric analysis, which showed the materials to be stable to weight loss up to 100–120 °C, and differential scanning calorimetry, which revealed strongly side group-dependent T g values that ranged from −76 to 87 °C.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.001

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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