Laser Melting Additive Manufacturing Research Articles

PRODUCTION OF OXIDE DISPERSION STRENGTHENED INCONEL 718 ALLOYS USING CONVENTIONAL POWDER METALLURGY AND ADDITIVE MANUFACTURING METHODS

Oxide dispersion strengthened (ODS) Ni-based alloys having a high density of nano-oxides (NOs) (<10 nm) are considered to be good candidates for extreme environments, such as high temperature, radiation, and corrosion. In this study, ODS IN718 alloys have been produced using conventional powder metallurgy (PM) and novel selective laser melting (SLM) additive manufacturing. The effect of processing routes on the microstructure, in particular on the nano-oxide formation and structure has been investigated. It has been found that the powder metallurgy method that consists of compressing followed by sintering at 1250 and 1500 °C results in a nano-granular structure with homogenously distributed fine nano-oxides having a high number density. Similarly, SLM results in a high number density of fine nano-oxides; however, the particles exist in groups with the grains/cells. The nano-oxides are determined to be Y2Ti2O7, Y2TiO5 or YTiO3 and Y-Al-O. The deviation in the lattice parameters of Y2Ti2O7 infers the existence of some Al in the structure. This study sheds light on producing ODS IN718 alloys with high-density nano-oxides using powder metallurgy and additive manufacturing methods.

Selective Laser Melting Additive Manufactured Tantalum: Effect of Microstructure and Impurities on the Strengthening-Toughing Mechanism.

The balance between the strength and the toughness of pure tantalum (Ta) fabricated with selective laser melting (SLM) additive manufacturing is a major challenge due to the defect generation and affinity for oxygen and nitrogen. This study investigated the effects of energy density and post-vacuum annealing on the relative density and microstructure of SLMed tantalum. The influences of microstructure and impurities on strength and toughness were mainly analyzed. The results indicated that the toughness of SLMed tantalum significantly increased due to a reduction in pore defects and oxygen-nitrogen impurities, with energy density decreasing from 342 J/mm3 to 190 J/mm3. The oxygen impurities mainly stemmed from the gas inclusions of tantalum powders, while nitrogen impurities were mainly from the chemical reaction between the molten liquid tantalum and nitrogen in the atmosphere. The proportion of <110> texture decreased after vacuum-annealing at 1200 °C, while that of the <100> texture increased. Concurrently, the density of dislocations and small-angle grain boundaries significantly decreased while the resistance of the deformation dislocation slip was significantly reduced, enhancing the fractured elongation up to 28% at the expense of 14% tensile strength.

Tensile behavior of large size Zr−based bulk metallic glass composites prepared by selective laser melting

A Zr55Cu30Al10Ni5 (Zr55) bulk metallic glass composite (BMGC) with a size of 37 × 37 × 10 mm3 was fabricated by using selective laser melting (SLM) additive manufacturing technology with argon gas atomized (GAed) powder. The microstructure and tensile deformation behavior of SLMed Zr55 BMGCs are investigated. The microstructure evolution perpendicular to the laser scan direction exhibits a periodic microstructure with three different zones (amorphous, nanocrystal + amorphous and dendritic eutectic + nanocrystal zones). The stepwise tensile fracture behavior, mixing ductility with a sharp stress drop after the failure of amorphous layers is shown for the Zr55 BMGC. The nanocrystal + amorphous crystalline zone has a lower hardness and elastic modulus than the amorphous zone via the nanoindentation test, therefore, the stress drops obviously when the hard amorphous layers fail and then stress recovery follows as the soft crystalline layers pick up the load, resulting in a final failure strain of 9%. The results further verified the feasibility of SLM technology for the development of high−performance BMGCs for industrial applications.

Scanning strategy optimization for the selective laser melting additive manufacturing of Ti6Al4V

Minimizing the residual stress and deformation of the manufactured product consequent to the selective laser melting (SLM) process is always a primary focus in the realm of additive manufacturing. This paper studied the influence of different scanning strategies on the thermal-mecha nical characteristics of SLM of Ti6Al4V. Numerical simulation and experimental tests were employed concerning three scanning strategies of the SLM process: Z-shaped, outer spiral, and inner spiral. Allowing for the latent heat of phase change, thermal radiation, and convection effect, the temperature history, and distribution of the specimen were analyzed, based on which the indirect thermal-mechanical coupling method was engaged for the residual stress and deformation analysis. The result shows good consistency in deformation characteristics between the numerical prediction and experimental observation. A reasonable scanning strategy is beneficial to mitigating the non-uniform distribution of the residual stress, and compared with the outer spiral and inner spiral strategies, the z-shaped scanning strategy may have a better effect in forming accuracy and mechanical properties.

Microstructures and Hardening Mechanisms of a 316L Stainless Steel/Inconel 718 Interface Additively Manufactured by Multi-Material Selective Laser Melting

For the first time, the interfacial microstructures and hardening mechanisms of a multi-material (MM) 316L stainless steel/Inconel 718 (316L SS/IN 718) interface fabricated by a novel multi-material selective laser melting (MM SLM) additive manufacturing (AM) system have been investigated in this study. MM 316L SS/IN 718 parts were successfully built with high densification levels (&gt;99%) and low porosity content (average: ~0.81%). Microscopy analysis indicates that the interfacial microstructures are characterised by dense dislocation tangling networks, NbC and TiC, and very small amounts of Laves phase (&lt;2 wt. %). In addition, equiaxed grains (average: 45 ± 3 μm) are attained in the interfacial region, whereas both individual IN 718 and 316L SS regions exhibit show columnar grains with average sizes of 55 ± 5 μm and 85 ± 3 μm, respectively. Vickers microhardness (HV) and nanoindentation measurements exhibit that the hardness values of the interfacial region are between those of the individual material regions. A strengthening model is built to assess the contribution of intrinsic strength, solid solution, precipitations, dislocations, and grain boundaries to the overall interfacial hardness of the as-built MM alloy.

Influence of Structural Parameters on Mechanical Properties of Triply Periodic Minimal Surface Structure

Titanium alloy is widely used in aerospace and other fields due to its low density, high specific strength, corrosion resistance, and other advantages. With the development of selective laser melting additive manufacturing technology, it is possible to manufacture triply periodic minimal surface porous structures. The effects of structural parameters on the mechanical properties of a Ti-6Al-4V Diamond (D)-type triply periodic minimal surface structure are studied. According to the characteristics of porous structures, the Gibson Ashby fitting formulas of D structures are modified using the concept of equivalent cross-sectional areas. The influence of cell size and surface thickness on the compressive modulus and strength of a D structure is discussed. Prediction formulas of the mechanical properties based on cell size and surface thickness are established by combining the relative density with the structural parameters. On this basis, the density optimization method is applied to the lightweight design of a rocket-related assembly based on D structure filling. The design results verify the feasibility of a lightweight design based on triply periodic minimal surface structure filling.

Strategies to reduce pores and cracks of molybdenum fabricated by selective laser melting

Selective laser melting (SLM) additive manufacturing process has been attractive to the fabrications of Mo and Mo alloys due to the advantage of fast near net shaping of complex shaped components. In order to reduce pores and cracks, by using high purity Mo powder, process parameter optimization, as well as La2O3 particle addition and post hot isostatic pressing (HIP) were applied. The results show that when the applied linear energy density is larger than 0.48 J/mm, the SLM samples can have continuous molten tracks. When the applied volumetric energy density is in the range of 250–280 J/mm3, small cubic SLM samples can have high relative densities larger than 99.7%. For large bulk SLM samples prepared with a volumetric energy density of 259 J/mm3, the addition of 0.9 wt% La2O3 can reduce the porosity from 0.76% to 0.63%. After HIP treatment, the highest relative density of 99.6% can be obtained for large bulk sample with La2O3 addition. Cracks are observed only at the surfaces of all samples, while no cracks can be seen in the inner parts. Moreover, after adding La2O3, the cracks at the surfaces are narrowed, and the crack number density is significantly reduced by >2 times.

Selective Laser Melting (SLM) Additively Manufactured CoCrFeNiMn High-Entropy Alloy: Process Optimization, Microscale Mechanical Mechanism, and High-Cycle Fatigue Behavior.

The equiatomic CoCrFeNiMn high-entropy alloy (HEA) possesses excellent properties including exceptional strength-ductility synergy, high corrosion resistance, and good thermal stability. Selective laser melting (SLM) additive manufacturing facilitates the convenient fabrication of the CoCrFeNiMn HEA parts with complex geometries. Here, the SLM process optimization was conducted to achieve a high relative density of as-built CoCrFeNiMn HEA bulks. The mechanisms of process-induced defects and process control were elucidated. The microscale mechanical behaviors were analyzed through in situ scanning electron microscopy observation during the compression tests on micro-pillars of the as-built HEA. The stress-strain characteristics by repeated slip and mechanism of "dislocation avalanche" during the compression of micro-pillars were discussed. The high-cycle fatigue tests of the as-built HEA were performed. It was found that a large number of nano-twins were induced by the fatigue, causing a non-negligible cycle softening phenomenon. The effects of promoted ductility due to the fatigue-induced nano-twins were illustrated. This work has some significance for the engineering application of the SLM additively manufactured CoCrFeNiMn HEA parts.

Micro-laminated CoCrFeMnNi−TiNp/CoCrFeMnNi high-entropy alloy matrix composite with bimodal grain structure via multi-material selective laser melting (MM-SLM) additive manufacturing

Deviating from most studies on selective laser melting (SLM) additively manufactured single metals or homogeneous metal matrix composites (MMCs), this work engaged in a multi-material SLM (MM-SLM) route for micro-laminated MMCs with bimodal grain structures. Structurally hierarchical micro-laminate of CoCrFeMnNi high-entropy alloy (HEA)-based HEA−TiNp/HEA MMC was built by the MM-SLM to overcome the strength-ductility trade-off and improve the anti-impact performance under high strain-rate compression deformation. The dynamic impacts were performed on the SLM-built HEA and MM-SLM-built HEA−TiNp/HEA using a split Hopkinson pressure bar (SHPB) system, with the strain rates of 1000 s−1, 2000 s−1, and 3000 s−1. The structurally hierarchical HEA−TiNp/HEA exhibited higher strength and deformability than the HEA. The strain-rate-dependent work hardening capacity and macroscopic plasticity of the HEA−TiNp/HEA indicated a better resistance to dynamic shocks. The promising results pave a road for achieving high-performance HEA-based MMCs of the MM-SLM-built hierarchical structures with a relatively low proportion of nano-ceramic reinforcements and bimodal-grained HEA matrix.

A dimensionally augmented and physics-informed machine learning for quality prediction of additively manufactured high-entropy alloy

Selective laser melting (SLM) additive manufacturing (AM) is widely used due to its significant advantages in designing and manufacturing special-shaped complex components. The process parameters of SLM determine the quality of as-built parts, but it is difficult to establish an accurate and reliable mathematical model to connect process parameters with the quality of as-built parts. However, data-driven machine learning can effectively solve the analysis and prediction problem of complex process. Therefore, a machine learning (ML) prediction method based on dimensionality augmentation and physical information is proposed, which connects the process parameters (laser power, hatching space, scanning speed, and layer thickness) of SLM with the quality characteristics (top layer surface roughness and relative density) of as-built parts. The four process parameter features (4-dimensional features) are expanded to high-dimensional features through feature engineering to characterize the quality of as-built parts. In addition, the physical information of powder melting forming in SLM process is fused with ML algorithm, the theory-guided ML is used to improve the prediction accuracy of the model. In this paper, the CoCrFeNiMn high-entropy alloy as-built samples dataset is used for network training of four ML algorithms, and three assessment indexes are used to evaluate the prediction model. The results show that dimensionally augmented and physics-informed ML model has better prediction accuracy and generalization ability. The proposed method can also provide guidance for optimizing process parameters.

Ultrafast Laser Ablation of Inconel 718 for Surface Improvement

Inconel 718 is considered difficult to machine because of its ability to maintain its properties at high temperatures. The low thermal conductivity of the alloy causes accelerated tool deterioration when machining. Selective laser melting (SLM) additive manufacturing introduces a possibility of eliminating these difficulties, and producing complex shapes with this difficult-to-machine material. However, high surface roughness and porosity usually occur at the surface of components produced through additive manufacturing. In this study, the surfaces of Inconel 718 samples produced through selective laser melting were treated using laser ablation. The process parameters for the laser ablation process were analyzed in order to achieve a minimum surface roughness. The surfaces of the samples were observed after printing and after the laser ablation process using a microscope and the roughness average was measured using a profilometer. Optimized process parameters were achieved, and have the capability to reduce the surface roughness to a minimum Ra of 3.024 µm.

Acoustic emission for in situ process monitoring of selective laser melting additive manufacturing based on machine learning and improved variational modal decomposition

Acoustic emission for in situ process monitoring of selective laser melting additive manufacturing based on machine learning and improved variational modal decomposition

Fabrication and Actuation Performance of Selective Laser Melting Additive-Manufactured Active Shape-Memory Alloy Honeycomb Arrays

Shape-memory alloy (SMA) honeycomb arrays have drawn worldwide attention for their potential active applications in smart morphing wings. However, the manufacturing of complex active SMA honeycomb arrays via conventional processes is a difficult task, and the actuation performance of the honeycomb arrays has not yet been well–investigated. In this work, the active SMA honeycomb arrays were fabricated by selective laser melting (SLM) additive manufacturing, and their actuation performance was investigated. The results show that the SLM–fabricated active SMA honeycomb arrays can generate obvious actuation performance during the transformation and exhibit a higher maximum actuation stress of 2.53 MPa at a R/t ratio of 4 and a tensile pre–strain of 35%. This research will contribute to the design and further improvement of active SMA honeycomb arrays based on SLM additive manufacturing, promoting the engineering applications for smart morphing wings.

Optimization of Selective Laser Melting (SLM) Additive Manufacturing Process Parameters of 316L Austenitic Stainless Steel

Optimization of Selective Laser Melting (SLM) Additive Manufacturing Process Parameters of 316L Austenitic Stainless Steel

Design and 3D printing of waveguide-based ultrasonic longitudinal-torsional transducers for medical needle insertion

This paper presents a new waveguide-based longitudinal-torsional (L&T) ultrasonic transducer. For synchronization of both the longitudinal and the torsional vibrations, a new circular array of helical structures was designed and developed. The array of helical structures is used as an effective waveguide to constrain the wave propagations to achieve harmonic longitudinal-torsional vibration. Analytical modeling of the new design is presented for synchronous L&T vibration conversion. A finite element (FE) analysis was used to optimize the geometric design of the new L&T transducer. The new design was fabricated using a selective laser melting (SLM) additive manufacturing (AM) process. Lab experiments were conducted to measure the impedance and vibration performance of the novel fabricated transducers and validate the L&T transducer design. The results show that the new waveguide-based transducer is promising to deliver synchronized L&T vibration with high vibrational power efficiency. The new L&T ultrasonic transducer can be developed for a vibratory needle insertion device, effectively reducing insertion force and bending.

Formability, surface quality and compressive fracture behavior of AlMgScZr alloy lattice structure fabricated by selective laser melting

Due to the comprehensive advantages of lightweight and integration of structure and function, aluminum alloy lattice structures are widely applied in aerospace, automotive industry and biomedical fields. Selective laser melting (SLM) additive manufacturing technology can significantly improve the overall performance of the structure, reduce the production cycle and manufacturing cost by integrated manufacturing. In this paper, five lattice structures (BCC, BCCZ, FCC, FCCZ, Cubic) of AlMgScZr alloy were fabricated by SLM, and the formability, surface quality and compressive properties were systematically studied. It shows that printing defects are easily formed at high power and fast scanning speed. Comparatively, the lattice structures fabricated at low power and slow scanning speed (100 W-250 mm/s) have better overall forming performance at the same energy density. The Cubic type structure has the highest compressive strength of the five lattice structures, which has a compressive strength of 95.2 MPa under the 200 W-500 mm/s condition.

Effects of TiC nanoparticle inoculation on the hot-tearing cracks and grain refinement of additively-manufactured AA2024 Al alloys

The hot-tearing cracks and porosities of Al alloys usually developed in the selective laser melting (SLM) additive manufacturing, impairing the corresponding mechanical properties and machining performance. Thus, it is necessary to eliminate these defects via grain refinement of microstructures. In the present work, the SLMed TiC/AA2024 Al alloy was obtained by adding different contents of TiC nanoparticles into the AA2024 Al alloy powder at different laser scanning speeds. Experimental results show that the addition of TiC nanoparticles significantly refined the microstructures of SLMed AA2024 Al alloy matrix. Coarsening columnar grains were gradually transitioned to small equiaxed grains, which suppresses the formation and propagation of cracking and porosities. Such phenomenon was mainly attributed to the significant grain refinement during SLM solidification. The externally added TiC nanoparticles and the in-situ formed Al3Ti particles have certain orientation relationship (ORs) with their surrounding metal matrix. These ORs are related to the nucleating interface with low lattice mismatch, which promotes grain refinement via heterogeneous nucleation.

Evaluate the effect of melt pool convection on grain structure of IN625 in laser melting process using experimentally validated process-structure modeling

During the laser based manufacturing process such as metal additive manufacturing (AM) and laser cladding, enhancing or inhibiting liquid metal flow within the laser-induced melt pool provides a promising approach to tune material microstructure and the resulting mechanical properties. However, the effect of convection flow, specifically the dominant Marangoni convection flow in the melt pool, on the as-solidified material microstructure is still vague. This study aims to reveal convection-modified grain evolution in the laser melting process, e.g., the selective laser melting AM. We use a process-microstructure model and systematically design comparative simulation cases (with and without convection flow) to identify the effects of convection flow on melt pool geometry, solidification conditions, and as-solidified grain structure formation. The model is validated by secondary electron images and electron backscatter diffraction of the laser melted IN625 alloy provided by NIST Additive Manufacturing Benchmark Test Series. It is found that the strong Marangoni convection flow can widen the melt pool and notably affect the solidified microstructure in terms of grain growth directions and bulk nucleation events. This study provides a quantitative basis for controlling the as-solidified microstructure by manipulating the convection flow in the laser-induced melt pool.

Research on shape memory alloy honeycomb structures fabricated by selective laser melting additive manufacturing

Active honeycomb structures made of shape memory alloys (SMAs) have drawn worldwide attention for their potential applications in smart morphing wings. However, the manufacturing of SMA honeycomb structures via conventional processes is somewhat limited, especially when complex designs are needed. In this paper, selective laser melting (SLM) additive manufacturing was used to create NiTi-based SMA honeycomb structures that could be used for smart morphing wings. The influence of process parameters on structure precision, relative density, transformation temperatures, in-plane tensile deformability capacity and active deformation response were investigated systemically. The results show that high quality honeycombs with a relative density of 99.5% can be fabricated by the optimum process parameter with an energy density of 139 J·mm−3. Most importantly, the honeycombs fabricated with the optimum process parameter exhibit good in-plane tensile deformability capacity with a maximum strain of 62.3%, and show excellent active deformation response with an actuation strain of approximately 13% with functional stability. This research will contribute to the design and fabrication of SMA honeycomb structures based on SLM additive manufacturing, providing novel ideas for the future development of smart morphing wings.

ELUCIDATING THE FRACTAL NATURE OF POWDER BED IN SELECTIVE LASER MELTING OF METALLIC COMPONENTS

In this work, the fractal nature of Selective Laser Melting (SLM) additive manufacturing process (AM) is elucidated. Fractal dimension and lacunarity of metallic powders are calculated from Scanning Electron Microscopy (SEM) images adapted from literature. The complexity and homogeneity of the textures of the powder beds are also studied through the comparison of fractal dimension and lacunarity. It is found that better densification results are obtained when the powder bed’s fractal dimension is closer to the golden mean number of 1.618. Furthermore, this finding is extended to expressions for predicting the component’s bulk density produced via SLM by setting the [Formula: see text] exponent equal to the golden mean value and finding the proportionality constant, [Formula: see text], using a nonlinear least squares method. The proposed approach works well since theoretical prediction and experimental data compare well with root-mean-square-error (RMSE) values that do not exceed [Formula: see text]. This work sheds new light on enhancing additive manufacturing technologies considering the fractal nature of SLM since its process mathematical models are constructed around Euclidian space-time with continuous smooth assumptions that should be adapted to include the fractal nature of the manufacturing process aiming to improve their precision. The underlying interweaving of SLM, as a fractal process, and the golden mean number is revealed.