Improving weld strength of magnesium to aluminium dissimilar joints via tin interlayer during ultrasonic spot welding
Bibliographic record
Abstract
Welding of magnesium to aluminium alloys is enormously challenging due to the formation of brittle Al 12 Mg 17 intermetallic compounds (IMCs). This study was aimed at improving the strength of dissimilar joints of AZ31B-H24 magnesium alloy to 5754-O aluminium alloy by using a tin interlayer inserted in between the faying surfaces during ultrasonic spot welding. The addition of tin interlayer was observed to successfully eliminate the brittle Al 12 Mg 17 IMCs, which were replaced by a layer of composite-like tin and Mg 2 Sn structure. Failure during the tensile lap shear tests occurred through the interior of the blended interlayer as revealed by X-ray diffraction and SEM observations. As a result, the addition of a tin interlayer resulted in a significant improvement in both joint strength and failure energy of magnesium to aluminium dissimilar joints and also led to an energy saving because the optimal welding energy required to achieve the highest strength decreased from ∼1250 to ∼1000 J.
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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".