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Record W4417212529 · doi:10.1016/j.apmt.2025.103037

Coating-free metallic de-icing composites based on magnetic actuation

2025· article· en· W4417212529 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

VenueApplied Materials Today · 2025
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMagnetorheological fluidDeformation (meteorology)Magnetic fieldMagnetCurvaturePiezoelectricityFerrofluidFerromagnetism

Abstract

fetched live from OpenAlex

• Magnetorheological-elastomer (MRE)/steel composites generate strong negative-curvature deformation under an external field, producing pure Mode-I opening stresses that detach large ice blocks with low adhesion (∼0.8 kPa). • Encapsulated ferrofluid layers create positive-curvature deformation that propagates a smooth interfacial crack, with optimized fluid volumes achieving adhesion values as low as ∼1.5 kPa. • Embedded magnet arrays provide spatially programmable, localized deformation through rotational actuation of individual magnets, enabling complete de-icing on both flat plates and curved airfoil leading edges. • Magnetic actuation enables a thin, lightweight, coating-free architecture. • Magnetic actuation delivers instantaneous, low-power de-icing (0.1–0.35 kW/m 2 ), achieving complete ice removal with lower power demand than electrothermal or piezoelectric systems. Ice accretion on aircraft, wind turbines, and other exposed structures in cold climates poses significant safety and performance risks. Conventional de-icing technologies, such as electrothermal heating, hot-air circulation, and piezoelectric actuators, can be effective but are often hindered by high energy demand, complex system integration, and slow response times. These limitations highlight the need for simpler, more energy-efficient solutions. In this study, we introduce magnetically actuated buckling elastomer-like anti-icing metallic surfaces (BEAMS) as a novel active de-icing strategy. Three distinct mechanisms based on magneto-responsive BEAMS are demonstrated: (i) suspended magnetorheological elastomer (MRE)/steel composites, which deform under applied magnetic fields to induce negative curvature and initiate interfacial cracks; (ii) encapsulated ferrofluid/steel composites, which redistribute within an applied field to generate localized upward deformation and delaminate ice from the steel surface; and (iii) embedded magnet arrays, which rotate in place under a magnetic field, producing spatially programmable and localized surface deformation. Across repeated icing and de-icing cycles, all three systems achieved complete ice removal within a second under electromagnet-driven actuation, while consuming as little as 0.1 kW/m 2 , substantially lower than electrothermal (∼3.7 kW/m 2 ) and piezoelectric (∼0.74 kW/m 2 ) methods. These results demonstrate that magnetic actuation can enable instantaneous, low-power, and scalable de-icing through tunable deformation modes adaptable to both flat and curved geometries. This approach offers a promising pathway toward next-generation ice protection systems for aerospace and other cold-climate applications.

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 score0.047
Threshold uncertainty score0.766

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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