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Record W4408493322 · doi:10.2497/jjspm.14e-t16-05

Anisotropic Magnets Fabricated by Cold Spray Additive Manufacturing

2025· article· en· W4408493322 on OpenAlex
Fabrice Bernier, Jean-Michel Lamarre, Yusuke Hirayama, Kenta Takagi

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

VenueJournal of the Japan Society of Powder and Powder Metallurgy · 2025
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties of Alloys
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceMagnetAnisotropyGas dynamic cold sprayComposite materialMechanical engineeringOpticsEngineeringCoating

Abstract

fetched live from OpenAlex

The development of additive manufacturing (AM) of permanent magnets is rapidly growing due to the competitive advantages they offer. AM of complex shape magnets could revolutionize the design of electrical machines potentially allowing for higher performance. Unfortunately, magnetic performance of AM permanent magnets is often limited due to the use of isotropic powders. In this study, Al-NdFeB composite permanent magnets were fabricated by cold spray AM using anisotropic NdFeB powders. Anisotropic powder can improve magnets’ remanence and energy product via particle alignment and subsequent magnetic anisotropy. The effect of gas temperature on deposition rate and magnet performance was evaluated. Magnetic measurements were performed along three orthogonal directions to quantify the level of anisotropy. It is demonstrated that anisotropic powders partially align itself during the cold spray process in the absence of external magnetic field. This could pave the way for a simple and efficient way of fabricating anisotropic magnets.

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 categoriesInsufficient 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 score0.005
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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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