Powder metallurgy, the process of compacting powders and then heating and sintering them, has recently been attracting new attention in the field of practical materials such as metals and ceramics. This paper introduces examples of research on MD, MC, FEM, and DEM, which are expected to be applied in the future, as simulation methods for powder metallurgy compacting and sintering processes, and describes future developments in simulation. Simulation-based support technology will become more important in the future when the development of new powder metallurgical components requires complex control of many factors related to the manufacturing process, or when experimental inspection methods are difficult to apply.

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  The recent development of metal additive manufacturing makes it possible to manufacture lattice structures with complex topology. The lattice structures can be applied to biomaterials, shock energy-absorbing parts, and thermal management components. In this article, two studies related to strut-based lattice structures are introduced. One is the improvement in energy absorption properties of lattice structures based on experiments and finite element analyses. A strategy for suppressing shear band deformation, which has a detrimental effect on the energy absorption properties, is introduced. The other is an analysis for heat transfer properties of lattice-structured heat sinks based on computational fluid dynamics simulation and machine learning. A methodology to understand important structural features for heat sink properties is explained.

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  Persistent homology, an algebraic tool characterizing the topology of point clouds, was applied for the pores in sintered metals. This method is useful for understanding the role of pore-configurations in the elementary processes of deformation and fracture of porous metallic materials.

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  The effects of tool stiffness on powder die compaction process of multi-step parts have been investigated by performing FEM analysis using Drucker-Prager CAP model as constitutive equation for granular materials. The material parameters of atomized iron and ferrite powders were validated by comparing the results of uniaxial compaction tests with measurement die system. The influence of punch spring back during unloading and ejection was focused to discuss occurrence of shear failure on powder compact. FEM analysis for inner flange shape with different tool rigidity has been carried out. DPC model with measured materials parameters simulates proper densification behavior but some deviation at residual stress especially for ferrite powder. Results of analysis during and after unloading stage shows that inhomogeneous elastic recovery from tools leads to principal strain distribution occurrence and shear stress concentration at ejection stage. Moreover, it was found that elastic recovery of lower punch promotes inhomogeneity of residual stress especially for thinner rim shape.

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  In this paper, we will discuss the technology of prediction in AM processes, which is considered to be increasingly important for controlling microstructures, maximizing component performance, and ensuring reliability. An attempt to correlate part-scale and microscale temperature field analysis with actual microstructures is presented as well as an example of predicting solidification segregation by combining part-scale temperature field analysis with the phase field method. In addition, an example from the literature is presented, where machine learning was used to predict tensile strength distributions from temperature field data obtained by monitoring during the AM process.

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  First-principles calculation i s one of the methods to calculate electronic states, providing insights into various physical properties derived from these states. This study focuses on the utilization of first-principles calculations for Titanium （Ti） alloys. Specifically, it explores the analysis of interstitial element diffusion mechanisms within α-Ti and material design strategies aimed at enhancing the strength while minimizing the elastic modulus in β-Ti alloys.

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  Copper has bactericidal and virus inactivating properties against bacteria, and the use of copper-coated products on the surface of components such as stainless steel can reduce the risk of bacterial and viral. Among the coating techniques, the multi-beam laser cladding uses lasers to heat both the powder in flight and the substrate to form a fusion bonded layer. This method requires less heat input to the substrate than the conventional method of melting powder in a molten pool. In addition, by using a blue diode laser, which has a high absorption rate for copper, it is possible to form a coating with less energy than a near-infrared laser. In the model equation for the temperature rise of powder in the multi-beam laser cladding syste m, the temperature of flying powder depends on the particle size of the powder, so the powder with a particle size distribution will have a temperature distribution when reaching the substrate. Therefore, it is necessary to select a powder with a particle size below a certain level in order to melt the powder in flight. In this study, multi-laser beam cladding was performed using pure copper powder with a particle size distribution in which all particles are above melting when they reach the substrate. The dependence of the yield and dilution of layers formed by this method on heat input was determined.

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