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Record W4319811926 · doi:10.1002/cjce.24857

Polyhedral oligomeric silsesquioxane‐based functional coatings: A review

2023· review· en· W4319811926 on OpenAlexvenueno aff
Kaka Zhang, Shuaishuai Huang, Qi Zhang, He Zhu, Shiping Zhu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typereview
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsnot available
FundersDivision of Materials ResearchChinese University of Hong KongNational Natural Science Foundation of China
KeywordsSilsesquioxaneMaterials scienceCoatingCovalent bondPolymerFire retardantWettingNanotechnologyMoleculePolymer sciencePolymer chemistryComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Polyhedral oligomeric silsesquioxane (POSS)‐based coatings have attracted significant attention from academia and industry over the past decades. The three‐dimensional nano‐sized cage with alternating SiO bonds forms the inorganic core of POSS molecules, while organic functional groups are covalently attached to the Si vertices. With this unique structure, they can be integrated with polymers via different approaches, including physical blending, covalent grafting, and chemical cross‐linking. And the inorganic/organic hybrid nature of POSS offers the coating materials with desirable mechanical, anti‐wetting, anti‐corrosive, icephobic, and fire‐retardant properties. This review focuses on the state‐of‐the‐art developments of POSS‐based functional coatings, while their challenges and future research directions are also discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.270
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2023
Admission routes1
Has abstractyes

Explore more

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