MétaCan
Menu
Back to cohort
Record W4408307151 · doi:10.1002/marc.202400932

Antifouling Coatings Inspired by Biological Templates

2025· review· en· W4408307151 on OpenAlexafffund
Catherine M. Doyle, Marya Ahmed

Bibliographic record

VenueMacromolecular Rapid Communications · 2025
Typereview
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsUniversity of Prince Edward Island
FundersMitacs
KeywordsBiofoulingMaterials scienceFoulingPolymerNanotechnologySurface modificationChemical engineeringComposite materialMembraneChemistry

Abstract

fetched live from OpenAlex

Surface fouling is a major concern in health care, marine industry, and water purification plants. Polymeric coatings are traditionally utilized to reduce the attachment of foulants on a surface, however low density and thickness of polymer brushes formed by surface initiated polymerization methods, surface exhaustion by continuous exposure to the foulants, and mechanical vulnerability in harsh environments, limit the antifouling performance of these traditional coatings. Recent trends in bioinspired polymeric coatings combine antifouling properties of super-hydrophobic, and highly hydrated lubricating polymers with mechanical properties of micro- and nano-particles to yield contact active, foulant releasable and stimuli responsive materials with superior antifouling performance. This review specifically highlights the development of next generation bioactive antifouling coatings using nature as an inspiration and a discussion of their benefits, over traditional polymeric coatings. The bioinspired coatings obtained are further evaluated for their potential applications in the marine environment, as delivery carriers, in implants, biosensors, and in urinary catheters.

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 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 score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.030
GPT teacher head0.279
Teacher spread0.249 · 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

Citations14
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueMacromolecular Rapid CommunicationsSame topicMarine Biology and Environmental ChemistryFrench-language works237,207