MétaCan
Menu
Back to cohort
Record W2019708458 · doi:10.1038/srep02951

Self-healing of the superhydrophobicity by ironing for the abrasion durable superhydrophobic cotton fabrics

2013· article· en· W2019708458 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.

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of British Columbia
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsAbrasion (mechanical)Materials scienceMethacrylateComposite materialContact angleSelf-healingPolymerizationPolymer

Abstract

fetched live from OpenAlex

Self-healing of the superhydrophobic cotton fabric (SCF) obtained by the radiation-induced graft polymerization of lauryl methacrylate (LMA) and n-hexyl methacrylate (HMA), can be achieved by ironing. Through the steam ironing process, the superhydrophobicity of the SCFs will be regenerated even after the yarns are ruptured during the abrasion test under a load pressure of 44.8 kPa. SCFs made from LMA grafted cotton fabric can ultimately withstand at least 24,000 cycles of abrasion with periodic steam ironing. The FT-IR microscope results show that the migration of the polymethacrylates graft chains from the interior to the surface is responsible for the self-healing effect.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.027
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.013
GPT teacher head0.225
Teacher spread0.213 · 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