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Record W3000413020 · doi:10.1515/hf-2019-0184

Superhydrophobic wood grafted by poly(2-(perfluorooctyl)ethyl methacrylate) via ATRP with self-cleaning, abrasion resistance and anti-mold properties

2020· article· en· W3000413020 on OpenAlexaff
Yu Wang, Zuwu Tang, Shengchang Lu, Min Zhang, Kai Liu, He Xiao, Liulian Huang, Lihui Chen, Hui Wu, Yonghao Ni

Bibliographic record

VenueHolzforschung · 2020
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of New Brunswick
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceFourier transform infrared spectroscopyComposite materialContact angleMethacrylateAbrasion (mechanical)MoldGraftingX-ray photoelectron spectroscopyScanning electron microscopePolymerizationChemical engineeringPolymer

Abstract

fetched live from OpenAlex

Abstract Wood is a natural, abundant, renewable resource, which is easily processed, has beautiful texture and good mechanical strength, and is widely used for furniture, flooring, decor and building construction. However, wood is vulnerable to moisture and microorganisms, resulting in deformation, cracks, mold and degradation, which causes aesthetic problems and/or shortens the service life of wood products. In this paper, superhydrophobic wood (wood-F) was fabricated by grafting poly(2-(perfluorooctyl)ethyl methacrylate) (PFOEMA) onto wood by atom transfer radical polymerization (ATRP). Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) with an energy-dispersive X-ray spectroscopy (EDS) showed that PFOEMA was successfully grafted onto wood. The resultant wood-F exhibited excellent water resistance with a contact angle (CA) of 156° and hysteresis of 4°. The modified wood also showed abrasion resistance, self-cleaning ability and anti-mold properties, all of which are desirable for various wood products.

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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.198
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

Citations30
Published2020
Admission routes1
Has abstractyes

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