Bibliographic record
Abstract
Mechanical fastening or adhesive bonding methods are generally used to join a NdFeB permanent magnet to a steel component, while no research has been reported on the welding process to join magnet to steel. In this paper, laser spot welding was used to join a NdFeB permanent magnet to an SPCC (steel plate cold commercial) steel in an effort to achieve joining of magnet/steel dissimilar materials with high speed and quality, with the joint formation mechanism, hardness, strength, and fracture behavior analyzed. The results show that during the welding process, the two base metals quickly melt, mix and then solidify to form the weld that joins the two specimens together, but that the hardness in the joint is not uniform with the heat affected zone having lower hardness than the NdFeB base metal. Within the nugget, the region adjacent to the fusion line has the highest hardness while the middle part of the nugget has the lowest in the joint. The maximum fracture stress of the joint is about 75% the strength of the magnet. Hot cracks tend to occur at the interface between the nugget and the magnet base metal, whereat the cracks propagate and lead to joint failure during shear tests. The fracture is intergrannular which is a typical brittle fracture.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".