Microstructure and magnetic properties of additively manufactured NdFeB magnets by cold spray
Bibliographic record
Abstract
Neodymium iron boron (NdFeB) permanent magnets are ubiquitous components in compact electromagnetic devices that demand high energy density for high efficiency. Commercial manufacturing approaches such as sintering and hot deformation yield excellent magnetic performance, while bonding methods offer geometric freedom at reduced thermal exposure. Cold spray, initially a coating technique, is an emerging solid-state additive manufacturing method that deposits metal powder via high-velocity impact without melting. However, cold-sprayed NdFeB magnets show inferior magnetic performance compared to sintered or hot deformed magnets, and the reasons causing such deterioration of magnetic properties are not completely understood. In this study, we use aluminum as the binder to manufacture bonded NdFeB magnets by cold spray and investigate the microstructure features, such as phases, oxidation, and crack formation, affect the magnetic performance. Compared with the raw NdFeB powder, the as-deposited magnet exhibited decreased coercivity (from 780 kA/m to ~658 kA/m) and remanence (from 0.88 T to ~0.45 T). Electron probe microanalysis revealed localized oxidation at cracks, suggesting the decomposition of the Nd 2 Fe 14 B phase which generates non-favorable sites for reverse-domain nucleation. The X-ray diffraction and Williamson - Hall analysis indicated about ~0.8% of average micro-strain in the deposited material, promoting lattice distortion partial phase decomposition in the NdFeB powder during the cold spray process. This study improves our understanding of the high-strain rate deformation of NdFeB powders cold spray processing, opening new pathways for efficient, scalable, and energy-saving magnet manufacturing. • Cold-spray yields near-dense NdFeB-Al magnets that still lose 6–16% coercivity and 40–50% remanence. • XRD analysis shows impact induced microstrain around 0.8%, enabling defect-assisted nucleation in nano scale grains driving coercivity decrease. • Aluminium dilution plus closed porosity lowers remanence in line with a rule-of-mixtures estimate. • Crack-centred oxidation partially decomposes Nd 2 Fe 14 B phase, cutting hard-phase fraction, and further weakening magnetic properties.
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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) | 0.002 | 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".