Effect of Mo Addition on the Susceptibility of Advanced High Strength Steels to Liquid Metal Embrittlement
Bibliographic record
Abstract
Liquid metal embrittlement (LME) in Zn-coated advanced high-strength steels (AHSSs) is an increasing concern, particularly in automotive assembly, where it can cause early failure and reduce ductility during resistance spot welding (RSW). This study explores the impact of adding 0.2 wt% Mo on the LME susceptibility of 0.2C-2Mn-1.5Si AHSS through hot tensile testing, RSW, and advanced microstructural analyses, including atom probe tomography (APT) and transmission electron microscopy (TEM). The results suggest that Mo enhances resistance to LME, as evidenced by the increased tensile stroke from 2 mm in the case of the 0 Mo alloy and to 2.75 mm in the case of the 0.2 Mo sample. Also, the average crack length in the shoulder of the welded samples decreased from 109 ± 7 μm to 28 ± 3 μm by adding 0.2 wt% Mo to the base alloy. APT analysis revealed that, in the presence of Mo, there is increased boron (B) segregation at austenite grain boundaries, improving cohesion, while TEM suggested more diffusion of Zn into the substrate, facilitating the formation of Zn-ferrite. These findings highlight Mo's potential to reduce LME susceptibility of AHSS for automotive applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".