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Record W3216344517 · doi:10.1002/admi.202101402

Metallic Plate Buckling As a Low Adhesion Mechanism for Durable and Scalable Icephobic Surface Design

2021· article· en· W3216344517 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Materials Interfaces · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsNational Research Council CanadaUniversity of TorontoUniversity of New BrunswickOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMaterials scienceIcingBucklingComposite materialDurabilityAdhesionElastomerWind tunnelIcing conditionsAerospace engineeringGeology

Abstract

fetched live from OpenAlex

Abstract Ice accretion is significantly detrimental to a range of different industries worldwide. Current methods for reducing ice adhesion include the use of lubricants, hydrophobic coatings, or soft elastomers, all of which exhibit limited durability. As an alternative, here sparsely confined metallic sheets are suspended and the surface buckling instability is tailored, resulting in ice adhesion strengths on par with these prior strategies but without the use of any coatings. These Buckling Elastomer‐like Anti‐icing Metallic Surfaces, or BEAMS, exhibit ultra‐low ice adhesion (<1 kPa) and the mechanical resilience of metals. Results from an icing wind tunnel confirmed the efficacy of BEAMS toward impact ice accreted in realistic conditions via the high‐speed impingement of ≈20 µm droplets at −20 °C. The BEAMS sheet confinement, boundary conditions, and physical dimensions of both the ice and the metallic plates can be altered to minimize ice adhesion via the mechanics of plate buckling. Additionally, BEAMS that detach ice without directly contacting it are designed, the scalability of BEAMS is demonstrated, and their durability is verified using rain erosion, sandblasting, thermal extremes, and repeated icing/de‐icing, both in an icing wind tunnel and on a benchtop system.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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