This study explored the process-structure-property (PSP) relationships in Ti-6Al-4V alloys fabricated through direct energy deposition (DED) additive manufacturing. A systematic investigation was conducted to clarify how process variables—specifically, manipulating the cooling rate and energy input by adjusting the laser power and scan speed during the DED process—influenced the phase fractions, pore structures, and the resultant mechanical properties of the samples under various processing conditions. Significant links were found between the controlled process parameters and the structural and mechanical characteristics of the produced alloys. The findings of this research provide foundational knowledge that will drive the development of more effective and precise control strategies in additive manufacturing, thereby improving the performance and reliability of produced materials. This, in turn, promises to make significant contributions to both the advancement of additive manufacturing technologies and their applications in critical sectors.

Additive Manufacturing (AM) is a process that fabricates products by manufacturing materials according to a three-dimensional model. It has recently gained attention due to its environmental advantages, including reduced energy consumption and high material utilization rates. However, controlling defects such as melting issues and residual stress, which can occur during metal additive manufacturing, poses a challenge. The trial-and-error verification of these defects is both time-consuming and costly. Consequently, efforts have been made to develop phenomenological models that understand the influence of process variables on defects, and mechanical/ electrical/thermal properties of geometrically complex products. This paper introduces modeling techniques that can simulate the powder additive manufacturing process. The focus is on representative metal additive manufacturing processes such as Powder Bed Fusion (PBF), Direct Energy Deposition (DED), and Binder Jetting (BJ) method. To calculate thermal-stress history and the resulting deformations, modeling techniques based on Finite Element Method (FEM) are generally utilized. For simulating the movements and packing behavior of powders during powder classification, modeling techniques based on Discrete Element Method (DEM) are employed. Additionally, to simulate sintering and microstructural changes, techniques such as Monte Carlo (MC), Molecular Dynamics (MD), and Phase Field Modeling (PFM) are predominantly used.

Aluminum alloys, known for their high strength-to-weight ratios and impressive electrical and thermal conductivities, are extensively used in numerous engineering sectors, such as aerospace, automotive, and construction. Recently, significant efforts have been made to develop novel aluminum alloys specifically tailored for additive manufacturing. These new alloys aim to provide an optimal balance between mechanical properties and thermal/ electrical conductivities. In this study, nine combinatorial samples with various alloy compositions were fabricated using direct energy deposition (DED) additive manufacturing by adjusting the feeding speeds of Al6061 alloy and Al-12Si alloy powders. The effects of the alloying elements on the microstructure, electrical conductivity, and hardness were investigated. Generally, as the Si and Cu contents decreased, electrical conductivity increased and hardness decreased, exhibiting trade-off characteristics. However, electrical conductivity and hardness showed an optimal combination when the Si content was adjusted to below 4.5 wt%, which can sufficiently suppress the grain boundary segregation of the α- Si precipitates, and the Cu content was controlled to induce the formation of Al2Cu precipitates.

Boron carbide (B4C) is highly significant in the production of lightweight protective materials when added to aluminum owing to its exceptional mechanical properties. In this study, a method for fabricating Al-B4C composites using high-energy ball milling and directed energy deposition (DED) is presented. Al-4 wt.% B4C composites were fabricated under 21 different laser conditions to analyze the microstructure and mechanical properties at different values of laser power and scan speeds. The composites fabricated at a laser power of 600 W and the same scan speed exhibited the highest hardness and generated the fewest pores. In contrast, the composites fabricated at a laser power of 1000 W exhibited the lowest hardness and generated a significant number of large pores. This can be explained by the influence of the microstructure on the energy density at different values of laser power.

Aluminum alloys are widely utilized in diverse industries, such as automobiles, aerospace, and architecture, owing to their high specific strength and resistance to oxidation. However, to meet the increasing demands of the industry, it is necessary to design new aluminum alloys with excellent properties. Thus, a new method is required to efficiently test additively manufactured aluminum alloys with various compositions within a short period during the alloy design process. In this study, a combinatory approach using a direct energy deposition system for metal 3D printing process with a dual feeder was employed. Two types of aluminum alloy powders, namely Al6061 and Al-12Cu, were utilized for the combinatory test conducted through 3D printing. Twelve types of Al-Si-Cu-Mg alloys were manufactured during this combinatory test, and the relationship between their microstructures and properties was investigated.

Metal additive manufacturing (AM) has transformed conventional manufacturing processes by offering unprecedented opportunities for design innovation, reduced lead times, and cost-effective production. Aluminum alloy, a material used in metal 3D printing, is a representative lightweight structural material known for its high specific strength and corrosion resistance. Consequently, there is an increasing demand for 3D printed aluminum alloy components across industries, including aerospace, transportation, and consumer goods. To meet this demand, research on alloys and process conditions that satisfy the specific requirement of each industry is necessary. However, 3D printing processes exhibit different behaviors of alloy elements owing to rapid thermal dynamics, making it challenging to predict the microstructure and properties. In this study, we gathered published data on the relationship between alloy composition, processing conditions, and properties. Furthermore, we conducted a sensitivity analysis on the effects of the process variables on the density and hardness of aluminum alloys used in additive manufacturing.

Machine learning-based data analysis approaches have been employed to overcome the limitations in accurately analyzing data and to predict the results of the design of Nb-based superalloys. In this study, a database containing the composition of the alloying elements and their room-temperature tensile strengths was prepared based on a previous study. After computing the correlation between the tensile strength at room temperature and the composition, a material science analysis was conducted on the elements with high correlation coefficients. These alloying elements were found to have a significant effect on the variation in the tensile strength of Nb-based alloys at room temperature. Through this process, a model was derived to predict the properties using four machine learning algorithms. The Bayesian ridge regression algorithm proved to be the optimal model when Y, Sc, W, Cr, Mo, Sn, and Ti were used as input features. This study demonstrates the successful application of machine learning techniques to effectively analyze data and predict outcomes, thereby providing valuable insights into the design of Nb-based superalloys.

Lightweight steel is a crucial material that is being actively studied because of increased carbon emissions, tightening regulations regarding fuel efficiency, and the emergence of UAM, all of which have been recently labeled as global issues. Hence, new strategies concerning the thickness and size reduction of steel are required. In this study, we manufacture lightweight steel of the Fe-Mn-Al-C system, which has been recently studied using the DED process. By using 2.8 wt.% low-Mn lightweight steel, we attempt to solve the challenge of joining steel parts with a large amount of Mn. Among the various process variables, the laser scan power is set at 600 and 800W, and the laser scan speed is fixed at 16.67 mm/s before the experiments. Several pores and cracks are observed under both conditions, and negligibly small pores of approximately 0.5 μm are observed.

Novel Ni- and Fe-based alloys are developed to impart improved mechanical properties and corrosion resistance. The designed alloys are manufactured as a powder and deposited on a steel substrate using a high-velocity oxygen-fuel process. The coating layer demonstrates good corrosion resistance, and the thus-formed passive film is beneficial because of the Cr contained in the alloy system. Furthermore, during low-temperature heat treatment, factors that deteriorate the properties and which may arise during high-temperature heat treatment, are avoided. For the heattreated coating layers, the hardness increases by up to 32% and the corrosion resistance improves. The influence of the heat treatment is investigated through various methods and is considered to enhance the mechanical properties and corrosion resistance of the coating layer.

Aluminum alloys are extensively employed in several industries, such as automobile, aerospace, and architecture, owing to their high specific strength and electrical and thermal conductivities. However, to meet the rising industrial demands, aluminum alloys must be designed with both excellent mechanical and thermal properties. Computer-aided alloy design is emerging as a technique for developing novel alloys to overcome these trade-off properties. Thus, the development of a new experimental method for designing alloys with high-throughput confirmation is gaining focus. A new approach that rapidly manufactures aluminum alloys with different compositions is required in the alloy design process. This study proposes a combined approach to rapidly investigate the relationship between the microstructure and properties of aluminum alloys using a direct energy deposition system with a dual-nozzle metal 3D printing process. Two types of aluminum alloy powders (Al-4.99Si-1.05Cu-0.47Mg and Al-7Mg) are employed for the 3D printing-based combined method. Nine types of Al-Si-Cu-Mg alloys are manufactured using the combined method, and the relationship between their microstructures and properties is examined.

This study investigates the interfacial reaction between powder-metallurgy high-entropy alloys (HEAs) and cast aluminum. HEA pellets are produced by the spark plasma sintering of Al0.5CoCrCu0.5FeNi HEA powder. These sintered pellets are then placed in molten Al, and the phases formed at the interface between the HEA pellets and cast Al are analyzed. First, Kirkendall voids are observed due to the difference in the diffusion rates between the liquid Al and solid HEA phases. In addition, although Co, Fe, and Ni atoms, which have low mixing enthalpies with Al, diffuse toward Al, Cu atoms, which have a high mixing enthalpy with Al, tend to form Al–Cu intermetallic compounds. These results provide guidelines for designing Al matrix composites containing high-entropy phases.

A new Fe-Cr-Mo-B-C amorphous alloy is designed, which offers high mechanical strength, corrosion resistance as well as high glass-forming ability and its gas-atomized amorphous powder is deposited on an ASTM A213-T91 steel substrate using the high-velocity oxygen fuel (HVOF) process. The hybrid coating layer, consisting of nanocrystalline and amorphous phases, exhibits strong bonding features with the substrate, without revealing significant pore formation. By the coating process, it is possible to obtain a dense structure in which pores are hardly observed not only inside the coating layer but also at the interface between the coating layer and the substrate. The coating layer exhibits good adhesive strength as well as good wear resistance, making it suitable for coating layers for biomass applications.

There is increasing demand for the development of a new material with high strength, high stiffness, and good electrical conductivity that can be used for high-voltage direct current cables. In this study, we develop aluminumbased composites containing C60 fullerenes, carbon nanotubes, or graphene using a powder metallurgical route and evaluate their strength, stiffness, coefficient of thermal expansion, and electrical conductivity. By optimizing the process conditions, a material with a tensile strength of 800 MPa, an elastic modulus of 90 GPa, and an electrical conductivity of 40% IACS is obtained, which may replace iron-core cables. Furthermore, by designing the type and volume fraction of the reinforcement, a material with a tensile strength of 380 MPa, elastic modulus of 80 GPa, and electrical conductivity of 54% IACS is obtained, which may compete with AA 6201 aluminum alloys for use in all-aluminum conductor cables.

Iron-based amorphous powder attracts increasing attention because of its excellent soft magnetic properties and low iron loss at high frequencies. The development of an insulating layer on the surface of the amorphous soft magnetic powder is important for minimizing the eddy current loss and enhancing the energy efficiency of highfrequency devices by further increasing the electrical resistivity of the cores. In this study, a hybrid insulating coating layer is investigated to compensate for the limitations of monolithic organic or inorganic coating layers. Fe2O3 nanoparticles are added to the flexible silicon-based epoxy layer to prevent magnetic dilution; in addition TiO2 nanoparticles are added to enhance the mechanical durability of the coating layer. In the hybrid coating layer with optimal composition, the decrease in magnetic permeability and saturation magnetization is suppressed.

The automotive industry has focused on the development of metallic materials with high specific strength, which can meet both fuel economy and safety goals. Here, a new class of ultrafine-grained high-Mn steels containing nano-scale oxides is developed using powder metallurgy. First, high-energy mechanical milling is performed to dissolve alloying elements in Fe and reduce the grain size to the nanometer regime. Second, the ball-milled powder is consolidated using spark plasma sintering. During spark plasma sintering, nanoscale manganese oxides are generated in Fe-15Mn steels, while other nanoscale oxides (e.g., aluminum, silicon, titanium) are produced in Fe-15Mn-3Al-3Si and Fe-15Mn-3Ti steels. Finally, the phases and resulting hardness of a variety of high-Mn steels are compared. As a result, the sintered pallets exhibit superior hardness when elements with higher oxygen affinity are added; these elements attract oxygen from Mn and form nanoscale oxides that can greatly improve the strength of high-Mn steels.

In the present study, we develop a conductive copper/carbon nanomaterial additive and investigate the effects of the morphologies of the carbon nanomaterials on the conductivities of composites containing the additive. The conductive additive is prepared by mechanically milling copper powder with carbon nanomaterials, namely, multi-walled carbon nanotubes (MWCNTs) and/or few-layer graphene (FLG). During the milling process, the carbon nanomaterials are partially embedded in the surfaces of the copper powder, such that electrically conductive pathways are formed when the powder is used in an epoxy-based composite. The conductivities of the composites increase with the volume of the carbon nanomaterial. For a constant volume of carbon nanomaterial, the FLG is observed to provide more conducting pathways than the MWCNTs, although the optimum conductivity is obtained when a mixture of FLG and MWCNTs is used.

A conductive additive is prepared by dispersing multi-walled carbon nanotubes (MWCNTs) on Cu powder by mechanical milling and is distributed in epoxy to enhance its electrical conductivity. During milling, the MWCNTs are dispersed and partially embedded on the surface of the Cu powder to provide electrically conductive pathways within the epoxy-based composite. The degree of dispersion of the MWCNTs is controlled by varying the milling medium and the milling time. The MWCNTs are found to be more homogeneously dispersed when solvents (particularly, non-polar solvent, i.e., NMP) are used. MWCNTs gradually disperse on the surface of Cu powder because of the plastic deformation of the ductile Cu powder. However, long-time milling is found to destroy the molecular structure of MWCNTs, instead of effectively dispersing the MWCNTs more uniformly. Thus, the epoxy composite film fabricated in this study exhibits a higher electrical conductivity than 1.1 S/cm.