Classification of the Mechanisms of Liquid Metal Embrittlement Via Machine Learning

Begley, B. A.; Norkett, J. E.; Frampton, C.; Miller, V. M.

doi:10.1007/s11837-023-06326-z

JOM

2023

DOI: 10.1007/s11837-023-06326-z

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Classification of the Mechanisms of Liquid Metal Embrittlement Via Machine Learning

B. A. Begley,

J. E. Norkett,

C. Frampton

et al.

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Cited by 3 publications

References 33 publications

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A comprehensive systematic review of machine learning in the retail industry: classifications, limitations, opportunities, and challenges

Hassan,

Hassan

2024

Neural Comput & Applic

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A comprehensive systematic review of machine learning in the retail industry: classifications, limitations, opportunities, and challenges

Hassan,

Hassan

2024

Neural Comput & Applic

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Crack propagation in BCC Fe and the influence of Zn: An atomistic exploration

Mei,

Cheng,

Chen

et al. 2025

Acta Materialia

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Liquid Metal Embrittlement Susceptibility and Crack Formation of the Zn-Coated Complex Phase Steel

Hu,

Zhou,

Sun

et al. 2024

Materials

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In the resistance spot-welding (RSW) of galvanized complex phase (CP) steel, liquid metal embrittlement (LME) may occur, deteriorating the welded joint’s performance. Based on the Auto/Steel Partnership (A/SP) standard, the joints of galvanized CP steel welded with a welding current from 7.0 kA to 14.5 kA were evaluated. When the welding current increased to 11.0 kA, LME cracks began to appear. The longest type A crack was 336.1 μm, yet the longest type D crack was 108.5 μm, and did not exceed 10% of the plate thickness, which met the limitation of the A/SP standard. In light of the microstructural observation and element distribution, it was found that there existed an internal oxide layer adjacent to the surface of galvanized CP steel matrix, with the depth of about 4.1 μm. In addition, the simulation results show that the CP steel was under tensile stress throughout the RSW process, but the internal oxide layer could successfully lead to the low LME susceptibility of the Zn-coated CP steel.

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Classification of the Mechanisms of Liquid Metal Embrittlement Via Machine Learning

Cited by 3 publications

References 33 publications

A comprehensive systematic review of machine learning in the retail industry: classifications, limitations, opportunities, and challenges

A comprehensive systematic review of machine learning in the retail industry: classifications, limitations, opportunities, and challenges

Crack propagation in BCC Fe and the influence of Zn: An atomistic exploration

Liquid Metal Embrittlement Susceptibility and Crack Formation of the Zn-Coated Complex Phase Steel

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