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Record W2977219151

Synthesis and Property Optimization of Ordered, Aryl Dense Polysiloxanes Using Boron Catalysis

2019· dissertation· en· W2977219151 on OpenAlexfundno aff
Alyssa F. Schneider

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldChemistry
TopicOrganoboron and organosilicon chemistry
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArylBoronProperty (philosophy)CatalysisMaterials scienceOrganic chemistryChemistryCombinatorial chemistry
DOInot available

Abstract

fetched live from OpenAlex

Silicones are widely used polymeric materials due to their unique properties. The material properties of silicones may be altered by incorporating various organic groups. Traditional methods for linear silicone synthesis involve ring-opening polymerization, which leaves the growing chain susceptible to acid or base mediated chain redistribution and the formation of cyclic monomer byproducts. The Piers-Rubinsztajn (PR) reaction is an alternative siloxane synthetic route that avoids the use of tin- or platinum- based, or of Brønsted acid/base catalysts. Siloxane bond formation is catalyzed by tris(pentafluorophenyl)borane (B(C6F5)3) (R’3Si-H + RO-SiR”3 → R’3Si-O-SiR”3 + RH); alkoxysilanes can be replaced with silanols or alkoxybenzenes. The catalytic activity of B(C6F5)3 was shown to be hindered by trace water in solution; water acts as a Lewis base coordinating to B(C6F5)3. Since the hydrate-free form of B(C6F5)3 is required to initiate a PR reaction, water can act as an inhibitor. In a somewhat contradictory fashion, water was also shown to react with hydrosilanes via a B(C6F5)3 catalyzed hydrolysis reaction to give silanols, that themselves are reagents for the process. The reactivity of alkoxysilanes (or aryl ethers) in the PR reaction was found to be much quicker than water. This was exploited in the synthesis of Ax(AB)yAx triblock copolymers. The aryl rich AB core was first synthesized using the PR reaction. Excess silicone condensed via hydrolysis forming the A blocks. This method of exploiting relative reactivity to tune structure was applied to elastomers made using a single linker (eugenol) with multiple functional groups – elastomer morphology was controlled by changing order of addition. The development of aryl dense silicones is of interest for use in electronic devices. Phenylmethyl homopolymers and highly ordered phenyl pendant copolymers (Ph/Si ratio of 0.5-1.5) were synthesized from monomers to give polymers with high refractive indices (1.51-1.59) and Mw up to 170 kDa. Statistically relevant libraries of aryl functional silicones were developed using combinatorial chemistry in order to analyze their structure-property relationship. Incorporating aromatic groups into silicones worked to elevate thermal stability, refractive index and improve the mechanical strength of silicone rubbers.

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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