Direct Energy Deposition (DED), as one common type of additive manufacturing, is capable of fabricating metallic components close to net-shape with complex geometry. Surface mechanical attrition treatment (SMAT) is an advanced surface treatment technology which is able to yield a nanostructured surface layer characterized by compressive residual stresses and work hardening, thereby improving the fatigue performances of metallic specimens. In the present study, stainless steel 316L specimens were fabricated by DED and subsequently surface treated by SMAT. Both uniaxial tensile tests and uniaxial tension-compression low-cycle fatigue tests were conducted for as-built and SMAT processed specimens. The microstructure of both conditions was characterized by roughness and hardness measurements, scanning electron microscopy and transmission electron microscopy. After SMAT, nanocrystallites and microtwins were found in the top surface layer. These microstructural features contribute to superior properties of the treated surfaces. Finally, it can be concluded that the mechanical performance of additively manufactured steel under static and fatigue loading can be improved by the SMAT process.

Sub-micro dislocation cellular structures formed during rapid solidification break the strength–ductility trade-off in laser powder bed fusion (LPBF)-processed 316L stainless steel through high-density dislocations and segregated elements or precipitates at the cellular boundaries. The high-density dislocation entangled at the cellular boundary accommodates solidification strains among the cellular structures and cooling stresses through elastoplastic deformation. Columnar grains with cellular structures typically form along the direction of thermal flux. However, the ultra-low misorientations between the adjacent cellular structures and their interactions with the cellular boundary formation remain unclear. In this study, we revealed the ultra-low misorientations between the cellular structures in LPBF-processed 316L stainless steel using conventional electron backscatter diffraction (EBSD), transmission Kikuchi diffraction (TKD), and transmission electron microscopy (TEM). The conventional EBSD and TKD analysis results could provide misorientation angles smaller than 2°, while the resolution mainly depends on the specimen quality and scanning step size, and so on. A TEM technique with higher spatial resolution provides accurate information between adjacent dislocation cells with misorientation angles smaller than 1°. This study presents evidence that the TEM method is the better and more precise analytical method for the misorientation measurement of the cellular structures and provides insights into measuring the small misorientation angles between adjacent dislocation cells and nanograins in nanostructured metals and alloys with ultrafine-grained microstructures.

A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered that maintaining a high resolution while doubling the training image size was crucial in creating a more realistic synthetic 3D image. To meet this requirement, modified 3D image generator and critic architecture was developed within the SliceGAN framework.

The optimized structures, electronic properties and bonding characteristics of the hexagonal C14 Laves phase XCr₂ (X = Ti, Zr, Nb, Hf and Ta) have been investigated using first-principles calculations. Our results reveal that the equilibrium formation enthalpies are not depends entirely on the atomic numbers. The total and the partial density of states and valence charge densities of Laves phases are also calculated and applied to reveal the nature of the bonding character in consideration of the different atomic numbers.

The abnormal grain growth of steel, which is occurs during carburization, adversely affects properties such as heat treatment deformation and fatigue strength. This study aimed to control abnormal grain growth by controlling the materials and processes. Thus, it was necessary to investigate the effects of microstructure, precipitation, and heat treatment conditions on abnormal grain growth. We simulated abnormal grain growth using the cellular automaton (CA) method. The simulations focused on the grain boundary anisotropy and dispersion of precipitates. We considered the effect of grain boundary misorientation on boundary energy and mobility. The dispersion state of the precipitates and its pinning effect were considered, and grain growth simulations were performed. The results showed that the CA simulation reproduced abnormal grain growth by emphasizing the grain boundary mobility and the influence of the dispersion state of the precipitate on the occurrence of abnormal grain growth. The study findings show that the CA method is a potential technique for the prediction of abnormal grain growth.