Coating-free metallic de-icing composites based on magnetic actuation
Bibliographic record
Abstract
• 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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".