The review paper starts with the applications of liquid metals and then concentrates on lead and lead–bismuth eutectic used in Gen IV nuclear reactors and accelerator-driven systems. Key points of degradation modes of austenitic stainless steels and ferritic-martensitic steels, candidates for the structural components, are briefly summarized. Corrosion and liquid metal embrittlement are critical issues that must be overcome. Next, the paper focuses on the strong efforts paid to the mitigation of corrosion and reviews the different solutions proposed for the protection of steels in lead and lead–bismuth eutectic. There exist promising solutions based on protection by deposition of protective coatings or protection by “natural” oxidation resulting from optimized chemical composition of the steels. However, the solutions have to be confirmed especially by longer-term experiments and by additional mechanical testing.

To limit corrosion of the steels in contact with liquid metal (Pb or Pb-Bi), both different solutions based on the presence of alumina at the surface of the steels were selected: 2 Alumina-Forming Austenitic (AFA) steels and the 15-15 Ti steel coated by alumina layer. These technical options to mitigate corrosion by lead or Pb-Bi were investigated in terms of mechanical performances in liquid lead or liquid Pb-Bi. So the liquid metal embrittlement (LME) sensitivity of the different materials selected for their good corrosion resistance was evaluated by tensile tests or small punch tests carried out in presence of liquid metal, and by post-mortem analysis of the cracking and of the fracture surfaces. No LME sensitivity for the tested conditions has been observed for the Al2O3 coated 15-15Ti steel and for the two AFA steels (16Ni-14Cr-2.5Al-2.5Mn-1Nb), one without and one with 2% wt.% W and 0.02% wt.% Y in their as received state. But a 650 °C thermal aging promotes modifications of the microstructure specially precipitations and then LME sensitivity of the AFA steels, according the nature of the precipitation.

Liquid metal embrittlement (LME) occurs when a normally ductile alloy undergoes brittle fracture in contact with a liquid metal. The mechanisms behind LME remain unclear, and most of the models rely on post mortem analyses. In this work, we overcome this limitation by performing in situ scanning electron microscopy (SEM) notched micro-bending tests on α-brasses exposed to the gallium–indium eutectic (EGaIn) at room temperature, enabling real-time correlation between load–displacement curves and crack evolution during LME. In the Cu-30%Zn alloy, LME was observed only after prior plastic deformation and ductile crack growth, confirming that liquid metal did not influence early plasticity. A two-step experiment further showed that a pre-existing crack in contact with EGaIn, under continued loading, was sufficient to trigger brittle fracture. The Cu-20%Zn alloy displayed alternating ductile and brittle events, with brittle cracks propagating horizontally before arresting in undeformed zones, leading to stepped load–displacement curves. By contrast, pure Cu and Cu-15%Zn showed only ductile fracture despite continuous contact with EGaIn. These results demonstrate that LME in the Cu-Zn/EGaIn system acts during crack propagation rather than initiation. The present in situ SEM methodology provides direct evidence of fracture mechanisms and a framework for future experimental modeling comparisons.

This study presents a robust methodology for analyzing 3D roughness parameters to characterize sandblasted surfaces, identifying the most relevant descriptors for process optimization. Sandblasting with irregularly shaped corundum particles is performed using five grit sizes (25, 50, 90, 125, and 250 µm) and three pressure levels (2, 3, and 4 bar). The resulting surfaces are characterized through eight 3D roughness parameters: Sa, Spc, Sal, Sfd, Sdq, Sdr, Spd, and Str. A linear model of the form Q = a + b.D + d.D.P, where Q represents the roughness parameter, D is the average grit size, and P is the sandblasting pressure, is employed. For Spd, a nonlinear model, Spd = (a + b.D + d.D.P)², yields a significantly improved determination coefficient, demonstrating the model’s enhanced ability to capture the complexity of the Spd parameter. The double-bootstrap analysis validates the statistical significance of all models, providing confidence intervals for each parameter. This approach emphasizes the importance of advanced 3D roughness descriptors for accurately analyzing surface textures in sandblasting processes, offering a reliable framework for surface characterization and industrial optimization.