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Record W4310286291 · doi:10.15251/djnb.2022.174.1297

Preparation and properties of a strong and durable composite superhydrophobic coating

2022· article· en· W4310286291 on OpenAlexaff
Fei‐Fei Mao, Changquan Li, Tianyong Mao, Zhongxin Xue, Guangqing Xu, Alidad Amirfazli

Bibliographic record

VenueDigest Journal of Nanomaterials and Biostructures · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsYork University
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceDurabilityCoatingAbrasion (mechanical)Composite materialContact angleSuperhydrophobic coatingComposite numberAqueous solutionChemistry

Abstract

fetched live from OpenAlex

In this paper, from the perspective of improving the durability of superhydrophobic coatings, a strong and durable superhydrophobic coating was prepared by a simple spray method. The coating has good chemical stability and mechanical durability. After soaking in aqueous solution with pH value of 1 and 14 for 30 hours and 24 hours respectively, the contact angle is 139.8 ° and 143.5 °respectively. After 90 times of abrasion, the contact angle is still 148 ° and the coating shows excellent self-cleaning and antifouling properties.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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