∝-Ferrite Suppression during Fiber Laser Welding of Al-Si Coated 22MnB5 Press-Hardened Steel
Bibliographic record
Abstract
During laser welding of an Al-Si coated 22MnB5 steel to produce tailor-welded blanks, the Al-Si coating mixes into the weld and causes the formation of the lower strength ferrite phase dispersed in an otherwise martensitic matrix. It has been shown that the presence of the ferrite phase is the principal reason for premature failure of hot-stamped laser-welded joints. Currently, the Al-Si coating is removed prior to welding, which can be time consuming. This work showed that adding Ni to the fusion zone of laser welded Al-Si coated 22MnB5 steel by welding through a pure Ni coating of a specified thickness, ferrite formation can be suppressed, whereby improving the weld strength and successfully shifting failure from the fusion zone, where it normally occurs, to the base material to achieve 100%joint strength. This work also showed that laser welding Al-Si coated 22MnB5 steel through a Ni coating eliminated the need to mechanically or chemically remove the Al-Si coating prior to welding.
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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) | 0.001 | 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".