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Record W4387366101 · doi:10.1039/d3cc03531j

Functional silicone oils and elastomers: new routes lead to new properties

2023· review· en· W4387366101 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Communications · 2023
Typereview
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiliconeElastomerOrganic chemistryMaterials scienceSilicone ElastomersPolymer scienceChemistry

Abstract

fetched live from OpenAlex

, aminosilicones, softening of fabrics; silicone polyethers, superwetting agricultural adjuvants). However, relatively little organic chemistry is practiced in commercial silicones, limiting the types of desirable functionality that can be attained. We report the utilization of a series of simple-to-practice organic reactions that take place efficiently on silicone oils to allow the preparation of a wide variety of functional silicones. The silicone oil starting materials typically act as both solvent and educt to allow many of the newer reactions, such as Click processes, to be used to tune the properties of both silicone oil and elastomer products. The review considers the concept of 'functionality' to include: the reactive groups used to enable synthesis of more complicated structures; and separately, the functional properties of the product silicones. One such property that is considered throughout is degradability at end-of-life, which is related to the sustainability of silicones.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.230
GPT teacher head0.350
Teacher spread0.120 · 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