Microcrack mitigation during laser scanning of tungsten via preheating and alloying strategies
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The high surface roughness is one of the major challenges encountered in laser metal additive manufacturing (AM) processes, which is closely related to the melt flow behavior. However, how to control the melt flow in laser metal AM processes to improve surface finish is unknown. Here we reveal the effects of nanoparticles on melt flow behavior at every location of melt pool during laser metal AM process for the first time using Al6061 + TiC nanoparticles system and achieve significant improvement of surface finish by using TiC nanoparticles to control the melt flow and damp the surface wave. Based on the in-situ x-ray imaging observation, the surface wave is fully damped after adding TiC nanoparticles, compared with only 56% damping without nanoparticles during LPBF of Al6061. Our in-depth in-situ x-ray imaging analysis and viscosity measurement enable us to identify that nanoparticle-induced increase of viscosity causes the fully damping of the surface wave by (1) increasing the internal fluid friction for more efficient wave amplitude reduction, (2) controlling the melt flow to increase the surface wave number, (3) controlling the melt flow to increase the wave damping time. Furthermore, we also quantified the relative contributions of increasing fluid friction, increasing wave number, and increasing damping time to wave damping, which account for 61%, 25%, and 14%, respectively. Furthermore, our research provides the mechanisms and potential method to address the surface finish challenge in laser metal AM processes.
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Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.
The fatigue strength of additively manufactured metallic parts in their as-built surface condition is mainly dominated by the surface roughness. Post-processing is often inevitable to reduce surface roughness effects even though post-processing diminishes the main advantage of additive manufacturing, which is net-shaped direct-to-service production. This work investigates the underlying mechanisms responsible for fatigue failure of additively manufactured 304L stainless steel parts in as-built and machined/polished surface conditions. Both strain- and force-controlled, fully reversed fatigue tests were conducted to gain a comprehensive understanding of surface roughness effects on fatigue behavior. The sensitivity to surface roughness is shown to be dependent on the control mode, with stress-based fatigue tests showing greater sensitivity than strain-based fatigue tests. Moreover, the fatigue life estimation for as-built specimens was performed based on surface roughness parameters as well as the fatigue properties of the specimens in machined/polished surface condition of the material without using any fatigue data of specimens in as-built surface condition. Accordingly, the effect of surface roughness on the fatigue behavior could be estimated reasonably well in both strain-life and stress-life approaches.
This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.
Additive manufacturing is a state-of-the-art production technology to produce tailor-made and highly complex parts. Among various other alloys, Ti base alloys are frequently used in this manufacturing technique due to their well-balanced properties and their wide range of applications. Allotropic phases and the occurrence of athermal phase transformations are the main reasons why these alloys hold a great development potential and are the basis of extensive use. High cooling rates during manufacturing lead to martensitic phases and the formation of nanometer-sized microstructures resulting in extraordinary strength. Simultaneously, such high cooling rates cause a high amount of lattice defects and the occurrence of residual stresses, which finally may result in delamination effects and cracks. Usually, a common approach to reduce residual stresses during additive manufacturing is to decrease thermal gradients by increasing the heat input or preheating the building platform. Instead of applying the typical approaches to lower thermal gradients, this study deals with the origin of the ‘softer’ orthorhombic martensite by accelerating the solidification process. The implementation of the orthorhombic phase in bulk components was inspired by a new phase transformation herein reported for the first time in the powder material, which also validates the possible occurrence of two martensitic phases in the same alloy. Various sophisticated characterization techniques like high energy and high-temperature X-ray diffraction, high-resolution transmission electron microscopy as well as atom probe tomography were applied to characterize this softer orthorhombic martensitic phase in detail aiming to highlight the opportunities accompanied by this new approach for additive manufacturing of titanium alloys.
Although retained austenite is present in minor amounts in as-built additively manufactured-maraging steels, its evolution during ageing is key to controlling the final microstructure. This study investigates the relationship between austenite reversion and precipitation evolution during ageing, particularly whether these processes compete or cooperate. Using Scanning/Transmission Electron Microscopy, Atom Probe Tomography and Thermo-Calc® PRISMA simulations, the presence and evolution of retained austenite, Ni 3 Ti and Fe 7 Mo 6 intermetallic phases was characterised across different ageing conditions. Experimental results revealed the presence of non-enriched austenite in the as-built condition. Nevertheless, with increasing ageing temperature, Ni and Mo segregation became evident. High-Resolution Transmission Electron Microscopy revealed that Ni 3 Ti precipitation primarily occurred within the martensitic matrix, while Fe 7 Mo 6 nucleated preferentially at the austenite-martensite interface. PRISMA simulations indicated early and rapid precipitation in solute-enriched areas (i.e., intercellular regions), with Ni 3 Ti forming prior to Fe 7 Mo 6 . Both experimental and simulation results suggested Ni diffusion controls retained austenite growth, while Ti and Mo drive Ni 3 Ti and Fe 7 Mo 6 precipitation, respectively. The evidence reported in this work supports a both collaborative and independent phase transformation mechanism, where austenite reversion and precipitation co-evolve.
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Metal additive manufacturing (AM) has evolved from scientific curiosity to a potential paradigm shift in materials manufacturing owing to its ability to control microstructure and fabricate complex geometries. However, geometry, often ignored as a variable, can have a significant impact on microstructure evolution, thereby indirectly limiting the design flexibility offered by AM. Currently, the process of retaining microstructure with changing geometry relies on trial and error-based processing followed by microstructural evaluation that places significant demands on time and costs associated with experimentation and characterization. We demonstrate herein that lightweight thermal models can be effectively used to predict microstructural changes with geometry. These models can in turn be used as precursors to developing geometry independent scan strategies and achieve microstructure control in various alloy systems. Even if the thermal signatures predicted by the model are not accurate, scan strategies can be developed to mimic the thermal conditions during initial process development. We present a case study on one of the most studied AM alloys: Ti-6Al-4V.
The microstructure and mechanical properties of laser powder bed fused (LPBF) AlSi10Mg alloys can be controlled by many processing parameters. This study focuses on the scan rotation angle, α, between adjacent layers, and establishes the relationship between α and tensile behavior of the as-built LPBF-processed AlSi10Mg alloy. Near-full density cubic coupons were manufactured using the same processing parameters but with systematic variation of α from 0° to 90°. Microscopic observations and X-ray diffraction analysis showed that differences among various coupons mainly include orientations of the melt pools with respect to the build direction and development of the crystallographic texture. The α=0° coupon and α=30° coupon showed the highest and lowest texture index, although the overall crystallographic texture was mild. Tensile specimens were manufactured horizontally and vertically using either α=0° or α=30°, but with various first layer laser direction with respect to the build plate. Notably, the α=0° specimen that was tested along the laser scan direction showed the largest yield strength (283 MPa) and highest tensile ductility (10.1 %). Quantitative image analysis and fractography were performed on all specimens. Results showed that the melt pool orientation with respect to the tensile direction affected the tensile behavior across the different specimens. This was closely related to the localized strain distribution within the melt pool and along the melt pool boundary for the different melt pool orientations observed. Further, these results demonstrate that the laser scan rotation angle between layers can be used to fine tune the mechanical properties of LPBF AlSi10Mg alloy.
Hybrid additive manufacturing (AM) involves secondary processes or energy sources to alter specified locations within the build volume. Each hybrid step can refine the grain size, increase dislocation density, or modify residual stresses. Typically, the changes in mechanical properties are not confined within a single layer but have a compounding effect on preceding layers. Existing methods of measuring AM residual stress are limited in terms of their sensitivity, or they are destructive measurements. We propose using resonant ultrasound spectroscopy (RUS) to measure the residual stress in hybrid-AM components noninvasively, based on changes to the resonances, compared to a stress-free component. In this paper, we use finite element models to simulate residual stress in hybrid-AM components and to examine the sensitivity of RUS measurements in terms of frequency shifts and mode shapes with respect to single hybrid layers. Then, the RUS results are used to predict stress for a layer at a known location with unknown stress. Here, the approach highlights the capabilities of RUS to address an AM characterization challenge.
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Design of an additively manufactured molten salt (MS) to supercritical carbon dioxide (sCO 2 ) primary heat exchanger (PHE) for solar thermal power generation is presented. The PHE is designed to handle temperatures up to 720 °C on the MS side and an internal pressure of 200 bar on the sCO 2 side. In the core, MS flows through a three-dimensional periodic lattice network, while sCO 2 flows within pin arrays. The design includes integrated sCO 2 headers located within the MS flow, allowing for a counterflow design of the PHE. The sCO 2 headers are configured to enable uniform flow distribution into each sCO 2 plate while withstanding an internal pressure of 200 bar and minimizing obstruction to the flow of MS around it. The structural integrity of the design is verified on additively manufactured (AM) 316 stainless steel sub-scale specimens. An experimentally validated, correlation-based sectional PHE core thermofluidic model is developed to study the impact of flow and geometrical parameters on the PHE performance, with varied parameters including the mass flowrate, surface roughness, and PHE dimensions. A process-based cost model is used to determine the impact of parameter variation on build cost. The model results show that a heat exchanger with a power density of 18.6 MW/m 3 (including sCO 2 header volume) and effectiveness of 0.88 can be achieved at a heat capacity rate ratio of 0.8. As a result, the impact of design and AM machine parameters on the cost of the PHE are assessed.
X-ray Computed Tomography (X-ray CT) is an analytical technique used in materials science to non–destructively characterize features in variety of materials like polymers, metals, composites, and explosives. It also has the capability of imaging additively manufactured, machined and assembled parts and processes. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations as a result of different stimuli, and assess accuracy of material production. This study will focus on parts manufactured via metal additive manufacturing (AM). Although, AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties. The analysis of 3D printed objects has a strength in analysis in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e. foams) due to stochastic structures. For this study, the print accuracy of several 3D printed cylinders will be assessed via X-ray CT to determine optimal printing parameters for parts with less defects and stronger mechanical properties. This will be accomplished by having the original STL file serve as the baseline surface to compute difference in the CT rendering to calculate surface roughness for each cylinders.