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Abstract Materials properties depend not only on their compositions but also their microstructures under various processing conditions. So far, the analyses of complex microstructure images rely mostly on human experience, lack of automatic quantitative characterization methods. Machine learning provides an emerging vital tool to identify various complex materials phases in an intelligent manner. In this work, we propose a “center-environment segmentation” (CES) feature model for image segmentation based on machine learning method with environment features and the annotation input of domain knowledge. The CES model introduces the information of neighbourhood as the features of a given pixel, reflecting the relationships between the studied pixel and its surrounding environment. Then, an iterative integrated machine learning method is adopted to train and correct the image segmentation model. The CES model was successfully applied to segment seven different material images with complex texture ranging from steels to woods. The overall performance of the CES method in determining boundary contours is better than many conventional methods in the case study of the segmentation of steel image. This work shows that the iterative introduction of domain knowledge and environment features improve the accuracy of machine learning based image segmentation for various complex materials microstructures.

Electroplated Cu has been extensively applied in advanced electronic packaging, and its mechanical properties are critical for reliability. In this study, Cu foils fabricated through electroplating with various bis-(3-sulfopropyl) disulfide (SPS) concentrations are examined using tensile tests. The SPS concentration affects the grain size of the electroplated Cu foils, resulting in different mechanical properties. A significant Hall-Petch effect, [Formula: see text], is demonstrated for the electroplated Cu foils. The different concentrations of impurities identified through time-of-flight secondary ion mass spectrometry correspond to the different grain sizes, determining the transgranular and intergranular fracture during the tensile test. The results demonstrate that the SPS concentration controlling the microstructures of the electroplated Cu results in a Hall-Petch effect on the mechanical properties of the electroplated Cu foils., (© 2023. The Author(s).)

With the ever-reducing sizes of electronic devices, the problem of electromigration (EM) has become relevant and requires attention. However, only the EM behavior of Sn-Ag solders within the solder joint structure has been focused on thus far. Therefore, in this study, a thin metallic film composed of Sn-3.5Ag (wt.%) was subjected to a current density of 7.77 × 10 4 A/cm 2 at a temperature of 15 °C to test the ability of existing EM models to predict the nucleation and evolution of voids generated by the resulting atomic migration. A computer simulation was then used to compute the coupled current distribution, thermal distribution, and atomic migration problems. It relied on an original random walk (RW) method, not previously applied to this problem, that is particularly well suited for modelling domains that undergo changes owing to the formation of voids. A comparison of the experimental results and computer simulations proves that the RW method can be applied successfully to this class of problems, but it also shows that imperfections in the film can lead to deviations from predicted patterns.

High-entropy alloys (HEAs) are promising materials for next-generation applications because of their mechanical properties, excellent high-temperature stability, and resistance against oxidation and corrosion. Although many researchers have investigated high-temperature HEA applications, few have considered low-temperature applications. Here we demonstrate an unprecedented intermetallic compound of (Fe, Cr, Co, Ni, Cu)Sn 2 at the interface between Sn-3.0Ag-0.5Cu (SAC) solder and FeCoNiCrCu 0.5 HEA substrate after reflow at 400 °C. Significantly suppressed growth of intermetallic compound without detachment from the substrate was observed during thermal aging at 150 °C for 150 h. Sn grains with an average grain size of at least 380 μm are observed. The results reveal a completely new application for the fields of Sn-Ag-Cu solder and HEA materials.

High-entropy alloys (HEAs) are well known for their excellent high-temperature stability, mechanical properties, and promising resistance against oxidation and corrosion. However, their low-temperature applications are rarely studied, particularly in electronic packaging. In this study, the interfacial reaction between a Sn-3.0Ag-0.5Cu solder and FeCoNiCrCu 0.5 HEA substrate was investigated. (Cu 0.76 , Ni 0.24 ) 6 Sn 5 intermetallic compound was formed the substrate at the interface between the solder and the FeCoNiCrCu 0.5 HEA substrate. The average Sn grain size on the HEA substrate was 246 μm, which was considerably larger than that on a pure Cu substrate. The effect of the substrate on Sn grain size is due to the free energy required for the heterogeneous nucleation of Sn on the FeCoNiCrCu 0.5 substrate.