Additive manufacturing letters最新文献

The oxidation behavior of copper-silver (Cu–Ag) alloy with the structure of triply periodic minimal surfaces (TPMS) processed by laser powder bed fusion (LPBF) was investigated at 300 °C and 600 °C. The lightweight TPMSs increase surface area, boosting measurement sensitivity in oxidation studies. The presence of silver enhances oxidation resistance of Cu–Ag alloy compared to that of pure copper by slowing down the oxidation process and thinning the oxide layer. This suggests that silver in the alloy potentially suppresses the outward diffusion of copper from the substrate to the oxide layer. This effect is evident in the oxidation rate curves, where the introduction of silver changes the oxidation kinetics from a linear rate in Cu to a parabolic rate in Cu–2 wt.% Ag at 300 °C. Moreover, at 600 °C, silver induces a slower parabolic rate in Cu–2 wt.% Ag compared to Cu.

Electron beam powder bed fusion offers the unique opportunity to observe the process by measuring scattered electrons on a metal detector. This technique is the state of the art in generating electron optical images of the build area after melting using single- or multi-detector setups. The images enable the detection of surface defects like porosity or material transport by reconstructing the surface topography. Internal defects such as layer-bonding defects cannot be identified. Many of these defects, particularly layer-bonding defects, often originate from an irregular distribution of the powder bed.

This work introduces an additional process step by recording an electron optical image after the distribution of the powder bed. Combining this with an electron optical image after melting the previous layer enables extraction of powder bed features such as the current powder bed height. The underlying method bases on the correlation of experimental measurements and numerical simulations of the intensity of the electron optical signal for different powder bed heights. With this approach, it is possible to identify irregular powder distributions, such as uncovered areas of previously molten material or locally varying powder bed heights. This information is crucial for online monitoring and real time process control. Exemplary, this opens the opportunity of healing the powder bed by an additional raking step.

Multi-Material Additive Manufacturing (MMAM) enables the grading of material properties and the integration of functions within printed parts. While most MMAM methods are limited to process single-component or pre-mixed multi-component materials, the in-process mixing and extrusion of multi-component materials enables innovative material properties and use cases. When processing liquid multi-component materials, the individual component streams need to be homogenized in-process, but the required volume in conventional passive mixing hinders rapid transitions in material composition. In this paper, a two component printhead is presented which combines an active mixing approach with a continuous composition adjustment for a third additive. The approach to control the mixing composition is to influence the hydrodynamic equilibrium of individual material streams before merging them near the point of extrusion. The printhead’s functionality is verified in terms of mixing homogeneity and transition speed between material compositions.

This study investigates the impact of atmospheres (Ar and N₂) on Fe-12Cr-6Al alloy fabricated using laser powder bed fusion (L-PBF) in terms of melt pool shape/size, microstructure, precipitate characteristics, and mechanical properties. The sample built in the N₂ atmosphere exhibited lower porosity, wider melt pools, and no Al₂O₃ agglomeration. Oxygen content decreased from 0.012 to 0.0045 (wt.%), and nitrogen content increased from 0.013 to 0.02 (wt.%). The Ar-printed sample had a yield strength (YS) of 232 ± 15 MPa, ultimate tensile strength (UTS) of 286 ± 10 MPa, and total elongation (TE) of 6.4 ± 1.3 %, while the N₂-printed sample showed significant improvements of the mechanical properties: YS of 315 ± 11 MPa, UTS of 401 ± 11 MPa, and TE of 7.8 ± 1.1 %. Therefore, N₂ might be considered to replace Ar as a cost-effective shielding gas for FeCrAl alloys, with improved properties.

Using theory and simulations, the challenge of gravity-induced distortions during sintering is addressed and a mitigation strategy is proposed. Based on the continuum theory of sintering, the finite element simulation demonstrates the advantages of a rotating furnace to counteract gravity forces during sintering. Its application for stainless steel hollow parts produced by additive manufacturing (binder jetting) is demonstrated, numerically, for reliable industrial production of complex shapes. Sintering a tube in a very slow rotating motion exhibits an improvement in the final deformation ratio compared to a conventional sintering process.

The same concept has been adapted for higher furnace revolution speeds and the centrifugal force is now surpassing the effects of gravity. An extended study of sintering under microgravity for space-borne applications is also widely depicted with the same model. Indeed, it shows the possibility of reproducing Earth's sintering conditions at places where gravity is insufficient to provide acceptable densification and shape conservation during sintering.

Melt pool geometry is a deterministic factor affecting the characteristics of metal Additive Manufacturing (AM) components. The wide array of physical and thermal phenomena involved during the formation of the AM melt pool, along with the great variety of alloy compositions and AM methods, coupled with the clear influence of multiple process parameters, make it difficult to predict the melt pool geometry under a given set of conditions. Therefore, using Artificial Intelligence (AI) approaches such as Machine Learning (ML) is necessary for accurate predictions. Using a physics-informed feature selection strategy along with the application of atomic features for the first time, this work aims to offer accurately trained models relying on existing high-fidelity data for most common alloys in AM academia and industry, i.e., 316 L stainless steel, Ti6Al4V, and AlSi10Mg. Multiple ML algorithms were trained, and the results revealed that the average R² and RMSE obtained by the K-fold cross-validation (K = 5) were significantly enhanced when laser and material properties, inspired by the analytical models for AM melt pool geometry, were used as the model features. Removing the excess features and applying atomic features further enhanced the accuracy of the models. As a result, R² for the XGBoost, CatBoost, and GPR models were 0.907, 0.889, and 0.882, respectively, while the hold-out cross-validation led to 0.978, 0.976, and 0.945, respectively. Furthermore, the results showed that the XGBoost model outperforms the Rosenthal equation. This approach provides a pathway to more accurately predict the properties of metal AM components.

Additive manufacturing of Al alloys has garnered attention in the aerospace and automobile industries. This is the first study on the formation of nanoscale Al precipitates in the Si phase of an AlSi10Mg alloy during electron beam powder bed fusion (EB-PBF). Spherical Si particles were homogeneously dispersed in the Al matrix, highlighting the difference from the laser beam PBF (LB-PBF) microstructures. Nanoscale Al phase was formed with a crystallographic orientation relationship with the surrounding Si phase: (111)_Si//(111)_Al and [1$\overline{1}$0]_Si//[1$\overline{1}$0]_Al. The formation of Al nanoprecipitates was attributed to an interplay between non-equilibrium solidification, wherein excess Al was dissolved in the Si particles, and the subsequent decomposition of the supersaturated Si phase during high-temperature exposure owing to the preheating procedure. To the best of our knowledge, such formation of Al nanoparticles has not been reported in AlSi10Mg produced through conventional processing or LB-PBF. Thus, the unique thermal history of EB-PBF provides novel opportunities for microstructural evolution, which may be beneficial for the development of novel Al-based alloys.

Visible light-based volumetric additive manufacturing (VAM) technology has recently enabled rapid 3D printing of optically transparent resins in a single step. There is now strong interest in extending the design space of VAM to include opaque, scattering and composite materials. Microwave energy can penetrate more deeply than visible light into a broader family of materials. For microwaves to be useful for VAM, however it is necessary to have a fundamental understanding of material dielectric properties, microwave field propagation and localization. Here we present a multi-physics microwave beam formed-thermal diffusion model that addresses these needs. The model demonstrates its ability to optimize power delivery and curing time to obtain better thermal control. We validate the model with a proof-of-concept single-antenna experimental system operating at 10 GHz that is able to cure a wide variety of materials, including both optically translucent and opaque epoxy resins loaded with conductive additives with a minimum curing spot of 5 mm. While available microwave hardware operating at 40 Watt power cures the resins in 2.5 min, the model estimates the ability to cure in as less as 6 s at 1 Kilowatt power levels. This computational model and experiments lay the foundation for a future multi-waveguide microwave-based VAM system.

Additive manufacturing has revolutionized the creation of complex and intrinsic structures, offering tailored designs for enhanced product performance across various applications. Architected cellular or lattice structures exemplify this innovation, customizable for specific mechanical or functional requirements, boasting advantages such as reduced mass, heightened load-bearing capabilities, and superior energy absorption. Nonetheless, their single-use limitation arises from plastic deformation resulting from localized yield damage or plastic buckling. Incorporating NiTi shape memory alloys (SMAs) presents a solution, enabling structures to recover their original shape post-unloading. In this study, an NiTi architected metastructure, featuring auxetic behavior and a negative Poisson's ratio, was designed and fabricated via laser powder bed fusion (LPBF). The samples exhibit promising superelastic performance with recoverable deformation strains at room temperature. Comprehensive characterization processes evaluated the functional performance of the fabricated metastructures. The metastructure geometry promoted microstructure formation primarily along the wall thickness. Cycling compression tests, conducted at three applied force levels, demonstrated stable cyclic behavior with up to 3.8 % reversible deformation strain, devoid of plastic buckling or yielding damage. Furthermore, the NiTi metastructures displayed robust energy absorption capacity and damping behavior, underscoring their potential for reusable energy dissipators in various industries including aerospace, automotive, construction, and etc.

Boron has almost null solubility in iron, and its addition to stainless steels leads to the formation of hard borides, beneficial for increasing the wear resistance. However, these boron-containing steels have poor printability, with the occurrence of pronounced cracking, high porosity and risk of delamination. In this work, Box-Behnken design coupled with analysis of variance (ANOVA) was used to optimize the LPBF (Laser Powder Bed Fusion) processing parameters of a highly boron-alloyed stainless steel reinforced with a boride network. The proposed models demonstrated to be accurate in determine the porosity percentage for the studied alloys, in which the laser power and scanning speed play the main role in the alloys’ densification, and absence of extensive defects. These results indicate that the use of design of experiments tools is essential to produce defect-free boron-modified stainless steel specimens with a relatively low number of experiments, identifying a narrow optimized processing window to build bulk composite materials.