Highlights The process-formability-microstructure-performance relationship in additively manufactured Mg and its alloys was reviewed. The underlying mechanisms behind defect formation, microstructure evolution and performance improvement were discussed. A full chain development from raw materials to equipment and process was emphasized. 

Additive manufacturing of magnesium and its alloys: process-formability-microstructure-performance relationship and underlying mechanism

To improve the wear resistance of titanium alloy, the WC-reinforced composite coatings were prepared on Ti-6Al-4V substrate by laser cladding. The effect of linear energy density (LED: 73.3 J·mm−1-283.3 J·mm−1) on the microstructure, microhardness and wear resistance of the composite coatings were investigated. The evolution of WC during laser cladding was revealed and discussed. It is found that the WC is dissolved by the forms of releasing W and C with increasing LED, and grows into specific shapes according to the Lifshitz-Slyosov-Wagner model. As the LED increases, the retention index of WC decreases (0.91–0.80) and the grain size increases (1.89 μm–5.81 μm) in the composite coating. The microstructure differences lead to the microhardness and brittleness increasement of composite coating. Compared with the Ti-6Al-4V substrate, the maximum microhardness improvement and wear mass loss reduction are 5 times and 25 times by varying LED. The main wear mechanism of composite coatings is abrasive wear. However, additional forms of wear mass loss such as adhesive wear and WC peeling can occur due to LED variation, and further leads to the difference in wear resistance. It is expected that the evolution of WC, which can regulate the microstructure will provide an effective theoretical foundation for the wear-resistance improvement of the laser cladding coatings. 

Effect of linear energy density on microstructure and wear resistance of WC-Co-Cr composite coating by laser cladding

In the present study, the effective parameters in the Direct Laser Metal Deposition Method (DLMD) of SS316L-Inconel 625 grade material were investigated. A 1000 W continuous-wave fiber laser was used to manufacture a five-layered gradient wall. The weight percentages of Inconel 625 and SS316L were different in each layer. Response Surface Methodology (RSM) was used to study the effects of scanning speed and laser power -each in three levels- on the average width, surface roughness, average microhardness, standard deviation of the width, and standard deviation of the height of the gradient walls. Also, the microstructure of the gradient walls was investigated using SEM images and EDS analysis. The results showed that the average width and surface roughness of the walls would increase by decreasing the scanning speed and increasing the laser power. The increase in the scanning speed and decrease in the laser power decreased the standard deviation of the width and the height of the walls. The lowest surface roughness of 96 µm was obtained at the highest scanning speed of 200 mm/min while the lowest values of the standard deviation of the width and standard deviation of height were 76 and 70 μm, respectively at this speed. It was also found that the microhardness value increased significantly with the increase in the scanning speed due to the higher solidification rate. 

Experimental and response surface study on additive manufacturing of functionally graded steel-inconel wall using direct laser metal deposition

As the lightest metal structural material, magnesium and its alloys have the characteristics of low density, high specific strength and good biocompatibility, which gives magnesium alloys broad application prospects in fields of biomedicine, transportation, and aerospace. Laser selective melting technology has the advantages of manufacturing complex structural parts, high precision and high degree of freedom. However, due to some disadvantages of magnesium alloy, such as low boiling point and high vapor pressure, the application of it in laser selective melting was relatively undeveloped compared with other alloys. In this paper, the fabrication, microstructure, mechanical performance and corrosion resistance property of magnesium alloys were summarized, and the potential applications and the development direction of selective laser melting magnesium alloys in the future are prospected.

/pdf/selective-laser-melted-magnesium-alloys-fabrication-1nxe0dk7.pdf

Selective Laser Melted Magnesium Alloys: Fabrication, Microstructure and Property

Complex structures can now be manufactured easily utilizing AM technologies to meet the pre-requisite objectives such as reduced part numbers, greater functionality, and lightweight, among others. Polymers, metals, and ceramics are the few materials that can be used in AM technology, but metallic materials (Magnesium and Aluminum) are attracting more attention from the research and industrial point of view. Understanding the role processing parameters of laser-based additive manufacturing is critical to maximize the usage of material in forming the product geometry. LPBF (Laser powder-based fusion) method is regarded as a potent and effective additive manufacturing technique for creating intricate 3D forms/parts with high levels of precision and reproducibility together with acceptable metallurgical characteristics. While dealing with LBPF, some degree of porosity is acceptable because it is unavoidable; hot ripping and cracking must be avoided, though. The necessary manufacturing of pre-alloyed powder and ductility remains to be the primary concern while dealing with a laser-based additive manufacturing approach. The presence of the Al-Si eutectic phase in AlSi10Mg and AlSi12 alloy attributing to excellent castability and low shrinkage, attaining the most attention in the laser-based approach. Related studies with these alloys along with precipitation hardening and heat treatment processing were discussed. The Pure Mg, Mg-Al alloy, Mg-RE alloy, and Mg-Zn alloy along with the mechanical characteristics, electrochemical durability, and biocompatibility of Mg-based material have been elaborated in the work-study. The review article also summarizes the processing parameters of the additive manufacturing powder-based approach relating to different Mg-based alloys. For future aspects, the optimization of processing parameters, composition of the alloy, and quality of powder material used will significantly improve the ductility of additively manufactured Mg alloy by the LPBF approach. Other than that, the recycling of Mg-alloy powder hasn’t been investigated yet. Meanwhile, the post-processing approach, including a homogeneous coating on the porous scaffolds, will mark the suitability in terms of future advancements in Mg and Al-based alloys.

/pdf/advancements-in-the-additive-manufacturing-of-magnesium-and-15dylvt0.pdf

Advancements in the Additive Manufacturing of Magnesium and Aluminum Alloys through Laser-Based Approach

In this study, the dataset of as-cast A380 aluminum alloy involving chemical composition, processing parameter and mechanical properties was experimentally established. On this basis, the relationship between four input variables of Fe/Mn ratio, Sr content, cooling rate and porosity content, and two outputs of ultimate tensile strength (UTS) and elongation (El) was linked by two artificial neural network (ANN) models for comparison: (1) back propagation - artificial neural network (BP-ANN) model, and (2) back propagation optimized by particle swarm optimization - artificial neural network (PSO-BP-ANN) model. The results showed that the established PSO-BP-ANN model has better reliability and prediction accuracy than BP-ANN model, for lower root mean square errors (RMSE), 6.19 MPa for UTS and 0.08% for El, and higher determination coefficient (R2), 0.9775 for UTS and 0.9798 for El, respectively. Sensitivity level analysis result by the preferable PSO-BP-ANN prediction model showed that the order of relative importance for UTS is Sr content, cooling rate, Fe/Mn ratio, and porosity content while the importance ranking for El is Sr content, Fe/Mn ratio, cooling rate, and porosity content. The research results and dataset in this work lay a foundation for the control of casting performance in industrial practice and for secondary development of mechanical properties prediction module in commercial casting software. 

Artificial neural network approach for mechanical properties prediction of as-cast A380 aluminum alloy

Limitations of linear energy density for laser powder bed fusion of Mg-15Gd-1Zn-0.4Zr alloy

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Artificial neural network approach for mechanical properties prediction of as-cast A380 aluminum alloy

Limitations of linear energy density for laser powder bed fusion of Mg-15Gd-1Zn-0.4Zr alloy