The remarkable progress in additive manufacturing has promoted the design of architected materials with mechanical properties that go beyond those of conventional solids. Their realization, however, leads to architectures with process-induced defects that can jeopardize mechanical and functional performance. In this work, we investigate experimentally and numerically as-manufactured defects in Ti–6Al–4V octet truss lattice materials fabricated with selective laser melting. Four sets of as-manufactured defects, including surface, microstructural, morphological, and material property imperfections, are characterized experimentally at given locations and orientations. Within the characterized defects, material property and morphological defects are quantified statistically using a combination of atomic force microscopy and micro–computed tomography to generate representative models that incorporate individual defects and their combination. The models are used to assess the sensitivity to as-manufactured defects. Then, the study is expanded by tuning defects amplitude to elucidate the role of the magnitude of as-designed defects on the mechanical properties of the lattice material.

We here design and fabricate a new kind of copper matrix composites, where titanium carbide nanoparticles are in situ incorporated into and embedded within the copper matrix, by virtue of laser powder-bed-fusion (L-PBF) process. We made a multiscale examination on the microstructures of the additively manufactured samples, unraveling that there are many unusual microstructural features, including grain refinement, the existence of high-density dislocations, and supersaturation of titanium solute atoms in the as-printed metal matrix composites. These unique microstructural features are mainly interpreted by the intense thermal history and the rapid solidification nature of the L-PBF process. The resultant composites then integrate the most important four strengthening mechanisms in metals: grain boundary strengthening, dislocation strengthening, solid solution strengthening, and second-phase strengthening, rendering this new kind of copper matrix composites a remarkably high yield strength (~490 MPa) and large uniform elongation (~12%), surpassing many high-performance copper matrix composites and copper alloys.

Titanium and its alloys are probably the most suitable materials for selective laser melting (SLM) additive manufacturing to process. However, the high cost of raw powder materials limits the industrial application of as-printed Ti products. In this study, we have formulated a cost-affordable Ti–TiB composite powder for SLM, to simultaneously achieve excellent mechanical performance and cost effectiveness. The optimization of the processing parameters will be shown to lead to high relative density (99.3%) for the as-printed Ti–TiB composites containing (0.5, 1, and 2 wt%) TiB2. Furthermore, by incorporating TiB2, the as-printed composites exhibit much improved fracture strength (up to 1813 MPa) and microhardness (up to 412 HV), among which the Ti–0.5 wt% TiB2 has demonstrated a great combination of strength (1007 and 1646 MPa as yield and fracture strengths, respectively) and tensile ductility (~8%). The solidification pathway for the Ti–TiB composite during SLM has been investigated, and the underlying mechanism for achieving high yield strength is discussed based on existing models for shear-lag strengthening, grain refinement, and dispersion strengthening.

Metal additive manufacturing (AM) provides a platform for microstructure optimization via process control, but establishing a quantitative processing-microstructure linkage necessitates an efficient scheme for microstructure representation and regeneration. Here, we present a deep learning framework to quantitatively analyze the microstructural variations of metals fabricated by AM under different processing conditions. The principal microstructural descriptors are extracted directly from the electron backscatter diffraction patterns, enabling a quantitative measure of the microstructure differences in a reduced representation domain. We also demonstrate the capability of predicting new microstructures within the representation domain using a regeneration neural network, from which we are able to explore the physical insights into the implicitly expressed microstructure descriptors by mapping the regenerated microstructures as a function of principal component values. We validate the effectiveness of the framework using samples fabricated by a solid-state AM technology, additive friction stir deposition, which typically results in equiaxed microstructures.

In this investigation, the superalloy IN718 has been prepared by additive manufacturing (AM) following a selective laser melting technique, and the post-AM heat treatments have been optimized. The microstructure of additively manufactured (AM) IN718 is characterized by the presence of dendritic and cellular features with large spatial heterogeneity along and across the build plane. Along the build direction, the 〈100〉 fiber texture dominates. Heat treatment involving two-step solution treatment, and subsequently, two-step aging treatment was specifically designed to facilitate the precipitation of δ phase at the grain boundaries to make the material resistant to grain boundary sliding (GBS). The AM IN718 showed dynamic strain aging (DSA) at three different temperatures, while the critical strain for the onset of serration was extended to a higher value after the heat treatment.

The disruptive potential of additive manufacturing (AM) relies on its ability to make customized products with considerable weight savings through geometries that are difficult or impossible to produce by conventional methods. Despite its versatility, applications of AM have been restricted due to the formation of columnar grains, resulting in solidification defects and anisotropy in properties. To achieve fine equiaxed grains in AM, alloy design and solidification conditions have been optimized in various alloy systems. In this review paper, the microstructure of high-entropy alloy (HEA) parts produced by selective laser melting and powder-based directed energy deposition is investigated. Solidification maps based on laser process parameters (as opposed to most commonly used solidification velocity and temperature gradient) are constructed by compiling available literature for single-phase face-centered cubic, body-centered cubic, and multiphase HEAs. These maps could guide printing of HEAs and provide an insight into the design of novel HEAs for AM.

A novel approach is utilized to investigate the deformation mechanisms at the microstructural level in 3D-printed alloys. The complex formation methods leave a unique and complicated microstructure in the as-built 3D-printed alloys. The microstructure is three leveled, composed of meltpools, grains, and cells. Deformation mechanisms in this microstructure are still highly unexplored due to the complexities of analysis at this scale. To understand these, we establish an image processing framework that converts scanning electron microscope (SEM) images directly into models that are scaled up and 3D printed with representative stiff and soft materials for the proposed material types within the body. These bodies are loaded in uniaxial tension with digital image correlation to study the strain gradient and stress delocalization as a result of the microstructure. The same models were tested through Finite Element Analysis (FEA) with materials similar to reality. Our testing shows the hierarchical material distribution leads to an increased damage tolerance.

Severe cracking and unsatisfied mechanical performance are the major challenges of manufacturing titanium aluminide (TiAl) components by selective laser melting (SLM). In this work, graphene oxide (GO) sheets were introduced onto the metal powder surface to improve the manufacturability of SLM of a Ti–48Al–2Cr–2Nb (at.%) alloy and enhance the mechanical strength of the laser-fabricated parts. The effect of laser power and GO content on the macromorphology of single-track processing was investigated, showing that the crack-free track could be obtained with the addition of 0.1–0.5 wt.% GO under a laser power of 110 W. In addition, the characterization of multilayer buildups via electron backscatter diffraction and backscatter electron imaging reveals the grain refinement during SLM of GO/TiAl nanocomposites. Finally, the strength of the as-built samples was examined using micro-hardness test, showing a maximal increase of 21.9% by adding 0.3 wt.% GO into the TiAl powders from laser-fabricated samples without GO.

The study investigated novel wear and corrosion resistance of stainless steel and 316 stainless steel samples which were successfully prepared by laser melting deposition. Phase composition, microstructure, microhardness, wear resistance, and electrochemical corrosion resistance were studied. The experimental results showed that novel stainless steel was mainly composed of α-Fe and a few carbide phase (Cr, Fe)7C3. The microhardness of novel stainless steel was about 2.7 times greater than 316 stainless steel. Meanwhile, the specific wear rate of novel stainless steel and 316 stainless steel was 2.63 × 10−5 mm3/N m and 1.63 × 10−4 mm3/N m, respectively. The wear volume of 316 stainless steel was 6.19 times greater than novel stainless steel. The corrosion current and the corrosion potential of novel stainless steel and 316 stainless steel were 1.02 × 10−7 A/cm2 and 1.5 × 10−7 A/cm2, and −138.8 mV, −135.9 mV, respectively, in 3.5 wt% NaCl solution. Therefore, both microhardness and wear resistance of novel stainless steel were greatly improved, with high corrosion resistance.

Tungsten (W) alloy is of difficulty in processing for conventional way because of its high melting point. Here, W alloy sample with the addition of 3 wt% Ta was prepared by selective laser melting. The influence of volumetric energy density (VED) on the surface morphology and the relative density was discussed, and microstructure, phase composition, and microhardness were investigated. The results show that a smooth surface and high relative density (95.79%) can be obtained under optimal VED. The W–Ta substitutional solid solution formed because of the replacement of Ta atom. There are strip and block fine grains in the W–3Ta sample with no significant texture. In addition, subgrain structure with a size of around 1 μm formed inside the strip grain, owing to the large thermal gradient and extremely fast cooling rate. Finally, the W–3Ta alloy shows higher microhardness than that obtained by traditional methods.

Selective laser melting (SLM) is a state-of-the-art technology in the additive manufacturing field. This study focuses on the influence of scanning speed on the fabrication of Ti6Al4V samples produced by SLM. This article contributes to the effect of SLM scanning speed parameters on micropores, surface morphology, and roughness. The detailed characterizations for the parts produced by the SLM process are evaluated. An SLM scanning speed of 695, 775, or 853 mm/s was selected. The findings show that a high quality of surface morphology and microstructure is obtained at a scanning speed of 775 mm/s. In addition, the maximum surface roughness values for both upper and side surfaces are approximately 0.460 µm and 0.592 µm, respectively. Furthermore, surface defect characteristics regarding the speed mechanism parameter for the SLM system are also discussed, and the challenges to the part quality, and potential for numerous industries (e.g., aerospace, automotive, and biomedical), creating microstructures, are observed.

The oxidation behavior of the selective laser melting (SLM)–fabricated Inconel 718 was investigated through isothermal oxidation testing at 650 °C for 500 h and compared with that of the as-cast and as-forged specimens at the same testing conditions. The effect of microstructure and surface roughness on the oxidation behavior of the SLM-fabricated, as-cast, and as-forged Inconel 718 specimens was examined. The result shows that Inconel 718 fabricated by SLM with the unique layer structure exhibited a better resistance to the 500 h oxidation at 650 °C compared with as-cast and as-forged 718 with coarse dendritic structure and uniform equiaxed grain microstructure, respectively. The influence of the surface roughness on the long-time oxidation resistance of SLM specimens is not pronounced compared with that of as-cast and as-forged specimens. The tiny dendrites instead of grain boundaries are a major influencing factor for the oxidation process of SLM specimens. The surface roughness has more evident influence on the oxidation resistance of as-forged specimens than that of the as-cast ones subjected to the 500 h oxidation at 650 °C.

Additive manufacturing has enabled the development of lightweight lattice structures, which are widely used in orthopedic implant, aerospace and filtration fields. The traditional method of optimizing part build orientation has been unable to meet the demand for lightweight lattice parts. This paper proposes a novel method to obtain an optimum build orientation for lightweight lattice parts based on selective laser melting by considering two factors at a time, namely processability of lattice structures and the surface quality of functional features. First, the overhang structure area model for the evaluation of the processability of lattice structures is established; then, mesh segmentation and feature level classification of the lightweight part frame are carried out. On this basis, the adaptive feature roughness model for the evaluation of the surface quality of functional features is established; finally, a multicriteria genetic algorithm is used to solve the build orientation optimization problem of lightweight lattice parts to obtain a Pareto optimal set.

Additively manufactured parts produced via laser powder bed fusion (LPBF) have limitations in their applications due to post-processing requirements caused by high surface roughness. The characteristics of side-skin surfaces are generally assumed to be dominated by adhered powder particles. This work aims to analyze and interpret the effects of LPBF processing parameters on side-skin surfaces. As such, this work has two sections to investigate the effect of (i) core and (ii) border LPBF parameters on side-skin surface roughness for Ti–6Al–4V. The findings show that there is a robust correlation between both core and border LPBF parameters on side-skin surface morphologies. In terms of core LPBF parameters, an interaction between laser power and beam velocity is shown to influence side-skin surface roughness, resulting in Sa values in the range of 11–26 μm. Additionally, a preliminary investigation into the effect of melting mode phenomena at the border leads to a possibility of obtaining Sa values of <10 μm, with reduced effects of adhered and partially fused powder.

Distinguished by a marked combination of high strength and high fracture toughness, 18Ni-300 maraging steel (MS) is widely used for intricate tool and die applications. MS is also amenable to the powder bed fusion additive manufacturing process, providing unique opportunities to make small features and incorporate cooling channels in molds. In this study, tensile test samples were fabricated using selective laser melting to investigate the effects of built height and orientations on the evolution of the microstructure and the mechanical properties of the samples. The microstructure of the as-fabricated samples consists of the primary α-martensite phase and fine cellular microstructure (~0.66–0.83 μm) with the retained austenite γ-phase aggregated at the boundaries of the cells, resulting in an enhanced mechanical performance compared with traditional counterparts under the same condition (without post-heat treatments). Random grain orientations with weak textures are revealed in all samples. The XY-built samples display better tensile performance when compared to the Z-built samples due to the fine grain sizes and the retained γ phase. The bottom of the Z-built sample exhibits a higher hardness than other parts of the sample, which could be attributed to its finer cellular structure.