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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Quantification of Powder Spreading Process for Metal Additive Manufacturing

In powder bed additive manufacturing (AM), the powder spreading process can lead to inhomogeneity in layer height, porosity level, and particle size distribution. Hence, creating homogeneous layers is the first task for optimal printing. The conventional assessment methods for powder quality are limited to a measurement of powder morphology, flowability, particle size distribution, surface roughness, and packing density. However, those techniques may not be the most appropriate to quantify the powder bed characteristics since it is not able to capture local particle configuration and does not provide any vectoral information (e.g., arrangement of contacts between particles during spreading). In this project, we: 1) developed a powder spreading model using discrete element method (DEM) for multiple-layered process, 2) experimentally measure powder spreading dynamics including static angle of repose (AOR) and dynamic AOR in order to calibrate and subsequently validate the model, and 3) investigated the effect of particle spreading process parameters on spatial powder bed structure and quality using scalar (e.g., porosity, surface roughness, coordination number, and particle size distribution) and tensorial (e.g., directionality of inter-particle contacts) methods for a comprehensive quantification of powder bed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying Trapped Powder in Electron Beam Powder Bed Fusion

Abstract Electron beam powder bed fusion (PBF-EB) shows great potential for manufacturing complex parts including those with internal cavities for heat exchanger, manifold systems, or energy absorption purposes. PBF-EB allows for the manufacture of channel geometries without the need for support structures. Due to the nature of the powder spreading process, powder feedstock is often trapped in intentionally manufactured cavities. This trapped powder can often be difficult to remove and can disturb the intended flow of fluid through the cavity or damage downstream components in its use case. These trapped powder particles present a risk of contamination and component failure if not completely evacuated. Ti6Al4V is a choice material for aerospace applications due to its high strength to weight ratio and its composition as a nonferrous metal; however, in weight sensitive applications excess entrapped powders or powders loosely attached to the surface could cause undesirable weight increases. The inherent spreading process of PBF-EB is different than laser powder bed fusion (PBF-LB) in its operational temperature, sintering. In addition, PBF-EB is less commonly studied in literature compared to its PBF-LB counterpart, and as a result the complexity of the semi-sintered powder and its spreading behavior are not well understood. Prior work has investigated the difficulty in removing trapped powder from PBF-EB, but these studies do not address how to quantify the amount of trapped powder in the cavity. Thus, an accurate method to measure the amount of trapped powder in the cavity must be investigated. In this work, Ti6Al4V coupons were manufactured with horizontal and vertical cavities of three different sizes. Archimedes testing allows for the determination of density differences caused by porosity and trapped powders by measuring mass and volumetric dispersion. Computed tomography (CT) is well suited for segmenting the internal structure and features of a part and has been studied for applications including voids, porosity, and dross. Thus, CT was explored as a method for evaluating trapped powder content in this work. The volumetric representation of the segmentation of the reconstructed CT volume can vary greatly depending on the input filter and thresholding methods. In this study, four different types of segmentation approaches were evaluated to determine the best approach for segmenting the volume as compared to an operator labeled ground truth. The percentage density results from the Archimedes testing were compared to the volumetric percent density from the computed tomography approach. Differences in packing density between two different internal channel features were investigated. Overall, this work sought to validate the use of computed tomography for the detection of trapped powders and present a framework for volumetric segmentation.

Johnstone, Brian↗
DOE OSTI2022

An instrument for in situ characterization of powder spreading dynamics in powder-bed-based additive manufacturing processes

In powder-bed-based metal additive manufacturing (AM), the visualization and analysis of the powder spreading process are critical for understanding the powder spreading dynamics and mechanisms. Unfortunately, the high spreading speeds, the small size of the powder, and the opacity of the materials present a great challenge for directly observing the powder spreading behavior. In this study, we report a compact and flexible powder spreading system for in situ characterization of the dynamics of the powders during the spreading process by high-speed x-ray imaging. The system enables the tracing of individual powder movement within the narrow gap between the recoater and the substrate at variable spreading speeds from 17 to 322 mm/s. The instrument and method reported here provide a powerful tool for studying powder spreading physics in AM processes and for investigating the physics of granular material flow behavior in a confined environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Effects of Particle Size Distribution with Efficient Packing on Powder Flowability and Selective Laser Melting Process

The powder bed-based additive manufacturing (AM) process contains uncertainties in the powder spreading process and powder bed quality, leading to problems in repeatability and quality of the additively manufactured parts. This work focuses on identifying the uncertainty induced by particle size distribution (PSD) on powder flowability and the laser melting process, using Ti6Al4V as a model material. The flowability test results show that the effect of PSDs on flowability is not linear, rather the PSDs near dense packing ratios cause significant reductions in flowability (indicated by the increase in the avalanche angle and break energy of the powders measured by a revolution powder analyzer). The effects of PSDs on the selective laser melting (SLM) process are identified by using in-situ high-speed X-ray imaging to observe the melt pool dynamics during the melting process. The results show that the powder beds made of powders with dense packing ratios exhibit larger build height during laser melting. The effects of PSD with efficient packing on powder flowability and selective laser melting process revealed in this work are important for understanding process uncertainties induced by feedstock powders and for designing mitigation approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Revealing particle-scale powder spreading dynamics in powder-bed-based additive manufacturing process by high-speed x-ray imaging

Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. Here, the particle scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.

42 ENGINEERING↗
DOE OSTI2020

Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing

Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to a single layer and/or small number of particles. Therefore, results from such model configurations may not be generalized to multiple layer processes. In this study, a computationally efficient multi-layer powder spreading DEM simulation model is proposed. The model is calibrated experimentally using static Angle of Repose measurements. The adhesion model parameter, cohesive energy density is related to adhesive surface energy and strain energy release rate parameters. The model results show that interaction between particle and the powder spreading rake leads to noticeable variation in packing density, surface roughness, dynamic angle of repose (AOR), particle size distribution, and particle segregation. Finally, the powder model is experimentally validated using a recoater spreading rig to measure the dynamic AOR at spreading speeds consistent with recoating speeds and layer heights used in AM processes.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Investigating Powder Spreading Dynamics in Additive Manufacturing Processes by In-situ High-speed X-ray Imaging

The quality of the powder bed is known to be one of the main factors that influence the quality of the part being manufactured by powderbed- based additive manufacturing processes. For example, in the laser powder bed fusion process, it has been demonstrated that improving the powder bed density and homogeneity improves the final quality of the part. Understanding powder spreading dynamics in the powder-bed-based additive manufacturing processes is critical for designing spreading structures and spreading parameters, identifying defect formation mechanisms in the powder bed, and guiding the design of optimized feedstock powders. Extensive efforts have been devoted to understand the fundamental mechanism of the powder flow and spreading process. Various powder flow testers were used to study the flow behavior of powders used in additive manufacturing. However, the powder flow conditions in flow meters are different from those in real additive manufacturing conditions. Models have also been developed to simulate and study the spreading process. The discrete element method (DEM) is currently the main tool for computationally simulating the spreading process. However, these models are based on many physical assumptions. Visible light cameras have been used recently to conduct in-situ study of powder spreading in additive manufacturing. Due to the limited resolution and penetration depth of visible light, it is extremely difficulty to study the particle-scale powder spreading dynamics. Here, to overcome the challenges of studying powder spreading dynamics under real additive manufacturing conditions, we developed an experimental approach to study the particle-scale powder spreading process with high spatial and temporal resolution using the high-speed high-energy X-ray imaging facility at beamline 32-ID-B of the APS. Figure 1 shows an overview of the research setup. It is composed of a vacuum chamber (building environment), an automatic powder spreading system, a laser system, an X-ray source (X-ray outlet), and an X-ray detection/imaging system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Electrostatic powder spreading for metal powder bed fusion applications

Typical powder bed fusion processes spread each layer of powder by pushing it across the build area with a spreader bar or roller. While simple, these methods require good flowing powder and do not have the ability to place more than one powder type per layer. This naturally limits the ability to incorporate more than one material onto each powder layer in powder bed additive manufacturing processes. Here we demonstrate electrostatic powder spreading, a method to deposit a powder layer without mechanical contact with the previous layers. Electrostatic powder spreading (ESPS) uses an electric field formed between a powder container and a counter electrode to move powder particles from the container to the powder bed. We show that the rate at which powder is deposited can be controlled by adjusting the strength of the electric field. Correspondingly, the deposited layer thickness is controlled by the strength of the electric field and the recoating speed. To demonstrate the feasibility of ESPS for laser powder bed fusion powder spreading, nearly fully dense (> 99.8%) coupons were built in a commercial L-PBF machine using the ESPS setup. Finally, we achieve 2D patterning of a single layer by using an array of electrodes and switching the applied electric field on and off. ESPS represents a method to produce an arbitrary patterned multi-material powder bed without complicated powder removal steps and easy implementation into existing L-PBF machines. Furthermore, ESPS presents an opportunity to build parts with 3D gradients in material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Experimental approach for development of a powder spreading metric in additive manufacturing

The powder spreading is a vital step of powder-based additive manufacturing (AM) processes. The quality of spread powder can considerably influence the properties of fabricated parts. Poorly packed powder beds with high surface roughness result in printed part layers with large porosity and low dimensional accuracy, leading to poor mechanical properties. Therefore, the powder spreadability and its dependence on process parameters and powder characteristics should be quantified to improve the efficiency of powder-based AM methods. This study proposes a novel dimensionless powder spreadability metric that can be commonly used in different powder-based AM processes. The quality of spread powder in terms of powder bed density and surface roughness was evaluated by adjusting the process parameters including recoating velocity and layer thickness, and powder characteristics including particle size distribution. In addition, the dynamic repose angle was proposed and examined as another powder spreadability metric. Furthermore, the results showed that these two proposed metrics were strongly correlated and lower recoating velocity and larger layer thickness led to higher spreadability and lower dynamic repose angle.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Instrumentation for Metal Additive Manufacturing

Laser powder bed fusion (LPBF) is the most widely used process for metal additive manufacturing (AM), particularly where complex geometries provide performance advantages unattainable with traditional manufacturing techniques. However, LPBF is highly sensitive to innate variability in both the powder spreading and fusion steps, often leading to defects such as pores that are difficult to detect yet significantly impair component mechanical properties and fatigue life. This thesis presents a range of novel instruments enabling both precise assessment of powder layer characteristics and in-situ thermal metrology of metal AM to advance the quality control of LPBF. First, leveraging a custom X-ray microscope and a radiation-transport model developed through this work, transmission X-ray imaging is used to study spreading of thin metal powder layers. Effective layer depth is directly mapped at a process-relevant size scale, surpassing optical techniques that can only estimate local deposition from layer surface topography. Layer packing density and quality are shown to be influenced by powder flowability and particle size relative to nominal powder layer thickness. Layer quality is additionally connected to the geometry of the spreading implement and its velocity. This technique and its presented findings enable pairing feedstocks with spreading strategies that create layers with consistent packing density and uniformity. Second, a twofold approach is employed to optically interrogate the laser fusion step of LPBF for observing signatures of defect formation. Aperture division multiplexing is conceptualized, providing for simultaneous laser delivery and high-fidelity infrared (IR) process monitoring through a common optic. In-situ microscopy at 50 μm spatial resolution and at mid-wave IR wavelengths is proven readily achievable with the first purpose-built optic of this type. Next, a bespoke imaging spectrometer, along with a temperature-emissivity separation technique, is used to retrieve accurate process temperatures over a 1000 K range. Data from these instruments are correlated to porosity as fine as 4.3 μm in two LPBF test artifacts, as verified using computed tomography (CT), establishing the viability of robust optically-based component qualification.

Penny, Ryan↗
DOE OSTI2024

On the Nature of Recoater Damage Powder Spreading Mechanics

Laser powder bed fusion (PBF-LB) additive manufacturing gained popularity for the creation of high mix, low volume parts for defense and commercial applications. Parts made via PBF-LB can be difficult to qualify due to their variation in performance, even within the same build. During the build process, regions of the PBF-LB recoater blade could be subject to damage by spatter or superelevation in the powder bed. As a result, the worn recoater can potentially cause spreading defects in the localized topography profile, which could in turn cause porosity or form deviations. These process concerns are not well understood for their criticality and subsequent impact on part quality. This study will investigate the mechanics of recoater damage through two experimental builds. Post-mortem inspection of the failure region will be conducted with laser line profilometry and will help propose a better understanding of the criticality of extreme recoater damage.

In-Situ Monitoring↗
DOE OSTI2019

Binder Jet Additive Multi-Material Manufacturing for the Transformational Challenge Reactor

Additive manufacturing (AM) is a process in which material is deposited in a layer-by-layer fashion, thereby building up a geometry. This contrasts with subtractive manufacturing in which material is removed from bulk feedstock to create a final geometry. Binder jet AM (BJAM) is a specific process in the AM field in which a binder, or glue, is selectively deposited on a bed of spread powder feedstock and cured. Binder is deposited with an inkjet printhead, which allows for high-resolution shaping of the powder layers. Compared with other AM processes, BJAM is fast, efficient, and scalable. Further, BJAM has one of the largest material selections of the powder AM processes as it can process ceramics, plastics, metals, and virtually any powdered material. Thus, the opportunity exists to leverage the versatility and productivity of BJAM to enable multi-material printing, the next generation of AM technology. The aim of this research is the design and manufacture of a purpose-built BJAM machine that can process multiple materials in its normal operation. This binder jet additive multi-material manufacturing (BJAM 3 ) machine will be able to produce parts that have multiple materials intra- and inter-layer. An example of this would be encapsulating metal spheres inside of a ceramic cube or vice versa. This BJAM 3 process adds another step of freedom to designing and manufacturing complex parts. The milestone for this work is to provide details on the technical progress made to date on the development of multi-material binder jetting and to facilitate simultaneous additive manufacturing of at least two different powder feedstocks.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring Carbide Dispersed Steels: A Path to Increased Strength and Hydrogen Tolerance

The use of transition metal carbides is reported for use as a hydrogen trapping mechanism for ferritic and austenitic steel materials. The program combined computational modeling and simulations to guide experiments towards candidate metal carbide traps, both for interfacial and interior trapping. It was found that interfacial trapping is less effective than interior trapping, with the group IVB transition metal carbides being the most effect internal traps with a loss of carbon. The sub-stoichiometric rocksalt structure accommodate the hydrogen atoms in its octahedral interstices. Using percolation theory, carbon loss of approximately 25% or more was sufficient to ensure an interconnected network of vacancies for such trapping from the surface to the internal sites within the carbide. Using this as a guide, the program developed a means to provide a uniform dispersion of ZrC nanoparticles with either Fe or 304L micron-scale powders which was then consolidated by direct current sintering. Electrolytic hydrogen diffusivity studies confirmed the reduction of hydrogen diffusion in the matrix with increasing ZrC content, which was a linear response over the sample range studied (0.01 to 1.0 wt.%). The consolidated material was micro-tensile tested in either a non-hydrogen or hydrogen charge condition and compared to a control with no carbides. Additions up to 0.05 wt.% ZrC increased the yield strength with no loss in ductility in either the non-hydrogen or hydrogen tested condition. ZrC concentrations above this amount further increased the yield strength at the expense of ductility. While these samples had a lower absolute ductility value prior to failure, the relative change in ductility between the non-hydrogen and hydrogen charge states was less for the carbides than that of the control. Metal-rich ZrC nanoparticles were fabricated through a conformal coating process yielding ZrC0.66 particles that were then incorporated into a metal matrix. Notch fatigue testing in a hydrogen environment was conducted where the number of cycles to failure was found to be less in the control than that of the carbide addition. However, the spread in experimental data and the number of samples tested limits a conclusive outcome based on defects noticed in the gauge section of all the powder processed samples. The collective outcomes of this report provide further insight into the mechanisms by which carbides act as hydrogen traps; a means to process such carbides through powder metallurgy; and their associated mechanical performance in either a non-hydrogen or hydrogen-charged condition.

08 HYDROGEN↗
DOE OSTI2021

Synthesis of nanograined zirconium diboride microsphere powder feedstock via emulsification of suspensions

Ceramic nanograined materials have desirable characteristics compared to their macroparticle counterparts but are rarely used in industrial applications due to issues with poor handleability and health hazards. Due to interparticle forces that become more dominant as the particle size decreases, it is difficult to use nanomaterials to fill dies, spread on surfaces, or flow through hoppers found in various manufacturing processes. In this work, we report a scalable gelcasting solution and unique emulsification process to create microspheres composed of nanoscale powders to enhance the flowability and handleability of nanomaterials. The gelcasting solution and emulsification process can be used with any nanoparticle composition that can be suspended in a liquid phase. This paper reports the effects of various parameters on zirconium diboride microsphere formation, such as surfactant content and mixing conditions. The microspheres maintain the nano-scale characteristics of the powder but improve its flowability by using cross-linked polyvinyl alcohol to combine irregularly shaped zirconium diboride nanoparticles with a particle diameter of 60 nm into larger spherical particles with a d 50 ~25 μm. This hierarchical feedstock engineering design combine the positive characteristics of materials across both length scales and improve the flowability of the feedstock from a Hausner Ratio of 1.56 to 1.19. The materials produced using this technique can be used in thermal plasma spray, die filling for hot pressing or spark plasma sintering, and binder jet printing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A multi-scale convolutional neural network for autonomous anomaly detection and classification in a laser powder bed fusion additive manufacturing process

In-situ detection of processing defects is a critical challenge for Laser Powder Bed Fusion Additive Manufacturing. Many of these defects are related to interactions between the recoater blade, which spreads the powder, and the powder bed. Here this work leverages Deep Learning, specifically a Convolutional Neural Network (CNN), for autonomous detection and classification of many of these spreading anomalies. Importantly, the input layer of the CNN is modified to enable the algorithm to learn both the appearance of the powder bed anomalies as well as key contextual information at multiple size scales. These modifications to the CNN architecture are shown to improve the flexibility and overall classification accuracy of the algorithm while mitigating many human biases. A case study is used to demonstrate the utility of the presented methodology and the overall performance is shown to be superior to that of methodologies previously reported by the authors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Powder spreading, densification, and part deformation in binder jetting additive manufacturing

Binder jetting additive manufacturing (AM) can print complex structures in economical and scalable manner. Binder jetting AM comprises of deposition and weak binding of particles, known as green part, at room temperature and subsequent binder removal and sintering densification at high temperatures. However, during the densification (i.e., sintering), the part significantly deforms due to volume shrinkage. The deformation during sintering is difficult to predict, which prevents the widespread application of this technology. In this research, powder spreading simulation using discrete element method (DEM) was performed first to capture local variations in powder bed configuration. Second, finite element method (FEM) with a phenomenological continuum constitutive model was used to predict part shrinkage during the sintering process. DEM simulation showed variations in packing density, particle segregation, formation of uneven powder bed surface, and shift in particle size distribution (PSD). The sintering simulation modeled part deformation with a reasonable accuracy of 3% for solid-state sintering and intermediate liquid phase sintering. A demonstration case with non-uniform initial packing density showed that inhomogeneous green part density and PSD should be accounted for prediction of part deformation in binder jetting AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

From casting to 3D printing geopolymers: A proof of concept

The objective of this paper is to define a mix design strategy allowing the implementation of geopolymer in powder bed 3D printing. In a selective binder approach, an aluminosilicate powder bed is activated through the deposit of an alkaline silicate solution. We first show that, in comparison to casting, this technology requires mastering the spreading of the liquid into the powder bed to ensure that the reaction takes place where it is needed. A series of experiments at the drop level, mimicking the 3D printing process, were performed to determine the printing solution composition for a given powder bed packing. We then highlight the relationship between the compressive strength of the printed geopolymer and the powder bed saturation, controlled by the printing parameters. Finally, SEM/EDX analysis confirm the formation of geopolymer with desired Si/Al and Na/Al ratios in the resulting printed material.

36 MATERIALS SCIENCE↗