Comparative study of microstructure and mechanical properties of laser welded–brazed Mg/steel joints with four different coating surfaces
Bibliographic record
Abstract
This paper presents a comparative study of laser welding–brazing Mg to steel with four different coating surfaces, including (Zn+pre-existing Fe–Al phase), pure Zn coating, pre-existing Fe–Al phase and fresh steel without any coating. The presence of Zn coating was found to significantly improve the wettability of liquid filler on steel. However, Mg–Zn products enriching at the seam head tended to cause cracking. The weak bonding of Mg–Zn products and Fe–Al layer was mainly responsible for the decreased tensile strength and interfacial failure that occurred in joints with the first two coatings. For joints with the latter two coatings, the thickness of newly formed Fe–Al layer determined the mechanical properties. The reaction layer formed at the Mg/fresh steel was thin, inducing interfacial failure, whereas the joint with pre-existing Fe–Al phase fractured at the seam, indicating that the pre-existing Fe–Al phase was beneficial to formation and growth of the Fe–Al phase.
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 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".