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Record W4401340046 · doi:10.3762/bjnano.15.79

Beyond biomimicry – next generation applications of bioinspired adhesives from microfluidics to composites

2024· article· en· W4401340046 on OpenAlex
Dan Sameoto

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

VenueBeilstein Journal of Nanotechnology · 2024
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiomimeticsMicrofluidicsNanotechnologyMaterials scienceAdhesiveBiomimetic materialsComposite material

Abstract

fetched live from OpenAlex

In this perspective article, Professor Dan Sameoto outlines his opinion on future opportunities in the field of biomimetic adhesives. Despite over twenty years of excellent academic work by groups all around the world in this subfield, the economic value and impact of these materials is somewhat underwhelming. The question for the field is whether it should have a scientific and engineering focus to create every greater performance and understanding of the materials and hope that "if we build it, they will come". Perhaps we should expand our concept on what could be the desirable end applications for such materials and focus efforts on finding better end applications in which these materials can truly shine; a few of those applications like microfluidics and composites are highlighted in this article. It is time for a next generation of research to look beyond biomimicry and look towards re-engineering applications to make use of these materials' unique properties in economically viable ways.

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)0.000
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 score0.174
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.016
GPT teacher head0.239
Teacher spread0.222 · 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