MétaCan
Menu
Back to cohort
Record W4413267657 · doi:10.1109/tec.2025.3593451

Electropermanent Magnet Eddy Current Separator to Recycle Non-Ferrous Metals

2025· article· en· W4413267657 on OpenAlexaff
Alireza Abedini-Gourtani, Ahmadreza Tabesh, S. Ali Khajehoddin

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEddy currentMagnetSeparator (oil production)FerrousMaterials scienceCurrent (fluid)Magnetic separationNuclear engineeringWaste managementEnvironmental scienceElectrical engineeringMetallurgyEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

This paper proposes and demonstrates the idea of using electropermanent magnet (EPM)-based actuator in the structure of eddy current separator to recycle non-ferrous metals. It uses a coil excited by a full-bridge inverter to statically switch the direction of magnetic flux in the EPM, inducing eddy current within metal particles. This provides a pulsating magnetic actuator to repel non-ferrous metals mixed with other materials on a recycling conveyor. Conventional eddy current separators typically use a costly and bulky rotating permanent magnet drum or a static electromagnetic coil to generate the required repulsive forces. The static EPM-based separator eliminates the need for the expensive rotating drum structure. Furthermore, it reduces power losses compared to static electromagnetic coils by using narrow-band current pulses instead of continuous sinusoidal current. A quadratic approximation of the magnetic flux density is proposed to improve the accuracy of the repulsive force calculation. The paper also elaborates on a core optimization and electromagnetic heating analysis. A proof-of-concept EPM separator is developed and experimentally tested to calculate the repulsive force based on measured deviations in particle angle and distance. Comparing the test results shows an average error of less than 5%, confirming the improved accuracy of the quadratic approximation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score0.919

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)0.0010.001

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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Energy ConversionSame topicRecycling and Waste Management TechniquesFrench-language works237,207