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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 OSTI2025

Real-time single-element-detection structured illumination optical metrology for laser powder bed fusion

Laser powder bed fusion (LPBF) is a type of metal additive manufacturing which could benefit from improved process monitoring to improve quality control. We demonstrate, for the first time to our knowledge, the coaxial monitoring of melt track formation in steel powder with spatial frequency modulation imaging (SPIFI), an enhanced-resolution imaging technique which uses a photodiode to record one-dimensional images. Using a custom live-display software and a high-speed SPIFI geometry, we offset the SPIFI field of view from the fusing beam to monitor different regions of the LPBF melt pool and surrounding area. This demonstrates the potential of SPIFI to monitor spatial features within the melt pool in real-time with increased data efficiency.

Hunter, Scott (ORCID:0009000886150312)↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
DOE OSTI2026

Thermodynamics of Bimetallic Joints between Titanium and Tantalum Produced by Laser Powder Bed Fusion

Laser powder bed fusion (LBPF) is currently the most mature metal additive manufacturing (AM) technology. While it does not have the same flexibility as directed energy deposition techniques to produce compositional gradients, LPBF can still be used to generate bimetallic parts by depositing one metal on a build plate made of another. Here, in this study, we print combinations of Ti-6Al-4V with Ta and characterize defects that occur at the interface. We use thermodynamic modeling to explain the formation of keyhole porosity and solidification cracks when Ta is built on a Ti baseplate, and the lack of defects when the materials are reversed. By understanding the mechanisms that lead to defect formation, the methodology demonstrated here can be applied to other material systems to efficiently design bimetallic LPBF processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microstructural evaluation of thin-wall sections of 316L stainless steel produced by laser powder-bed fusion processing

Laser powder bed fusion (LBPF) is a method of additive manufacturing (AM) that offers a means to fabricate complex components with features which rely upon the mechanical integrity of thin-wall (less than 0.4 mm thick) structures. The microstructure of a 316L AM thin wall is investigated as metallographically prepared from a cylindrical shell. Optimization is pursued through mechanical polishing and chemical etching to minimize the effects of surface roughness. Microanalysis measurements of the sectioned component reveal the sample has high microstructural fidelity, uniform composition and phase content across grain as well as powder layer boundaries within the thin wall. The results are attributed to a uniform thermal gradient at the part scale during rapid solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GRCop-42: Comparison between laser powder bed fusion and laser powder direct energy deposition

This study involves a comparative analysis of additively manufactured GRCop-42 specimens produced using two processes: laser-powder bed fusion (L-PBF) and laser powder direct energy deposition (LP-DED). The investigation characterizes a range of material attributes, including surface topography, internal defects, microstructural features, quasi-static mechanical properties, and fractographic characteristics. The findings demonstrate that, despite the specimens being fabricated with the same base material, the resulting material properties vary significantly between the two additive manufacturing processes. As such, material properties cannot be presumed to be uniform across different manufacturing methods. Consequently, material characterization must be conducted for individual manufacturing processes based on specific parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A FeCrAl-Al2O3 Composite Produced via Laser Powder Bed Fusion of a Mixed Powder for Porous Catalyst Scaffolds

This study proposes a novel approach for synthesizing and etching bicontinuous FeCrAl-Al2O3 composites as a means for replacing FeCrAl foams as catalyst scaffolds in bio-driven alcohol reactors for jet-fuel production. Conventional FeCrAl foams suffer from poor availability and consequent high costs. New additive manufacturing techniques provide an opportunity to produce tailored foams in reasonable times and at acceptable costs. This research aimed to generate a porous FeCrAl structure by etching a bicontinuous FeCrAl-Al2O3 composite produced by laser powder bed fusion of amalgamated FeCrAl and Al2O3 powders. The composite powder for laser powder bed fusion is created by ball-milling FeCrAl and Al2O3 powders. This research focuses on achieving a bi-continuous FeCrAl-Al2O3 structure, essential for the selective removal of the ceramic phase. The influence of laser processing parameters on the microstructure was examined across a range of laser powers (60-120 W) and scan speeds (100-400 mm/s), showing that higher powers and speeds produce finer metal struts. A bi-continuous microstructure was consistently obtained, marking a key achievement. The Al2O3 removal process involved a two-step etching method using hydrochloric and phosphoric acids, tested across various etching times. The alumina phase was reduced from 36 vol% to 17 vol% (corresponding to an increase in porosity from 24 vol% to 43 vol%), showing the potential for use as a porous catalyst scaffold. This research demonstrates the potential for using additive manufacturing to produce porous FeCrAl structures capable of replacing hard-to-source FeCrAl foams.

Son, Kwangtae↗
DOE OSTI2025

2025 Peregrine in-situ monitoring and training dataset for laser powder bed fusion and binder jet printers

Peregrine, a software tool developed at Oak Ridge National Laboratory (ORNL), was used to collect and analyze in-situ monitoring (ISM) data from a Concept Laser M2 (Colibrium Additive) laser powder bed fusion (L-PBF) printer and an ExOne Innovent (Desktop Metal) binder jet printer. Data for four builds (print jobs) were saved to HDF5 (high performance data) files for release. Additionally, process anomalies were annotated by the authors across 37 image stacks (i.e., print layers) and are also provided as HDF5 files.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chemistry effects on ODS steel consolidated via laser powder bed fusion from GARS powder

Oxide Dispersion Strengthened (ODS) steels are promising candidate alloys for structural and cladding applications in extreme environments. They contain a high density of nanoscale oxides for high temperature mechanical strength and radiation resistance. In this work, gas atomization reaction synthesis (GARS) was used to produce powders that were used for additive manufacturing (AM) Laser Powder Bed Fusion consolidation of ODS steels, in order to skip the traditional mechanical alloying of blended yttria and alloy powders. Powder containing iron, chromium, and tungsten with varying amounts of yttrium, titanium, oxygen and zirconium were used to produce ODS steel samples. AM consolidated specimens and powder samples were characterized with transmission electron microscopy. TEM imaging, diffraction patterns, and energy dispersive X-ray spectroscopy (EDS) was used to identify phases present before and after consolidation across chemistries. The effect of the controlled oxygen input (from GARS) and the oxide-forming additions (Y, Ti, Zr) on precipitate size distribution and composition is substantiated and discussed.

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 OSTI2026

On the formation of swelling and related flaws in laser powder bed fusion

Process monitoring in laser powder bed fusion additive manufacturing can provide insights into stochastic anomalies, melt pool and plume dynamics, and part quality. Swelling, a build anomaly where overbuilt material protrudes through the powder layer after recoating, is readily detectable in post-recoat visible light images of the powder bed. Here, this work identifies several of the underlying mechanisms driving swelling formation by analyzing the influence of processing parameters, laser scan paths, and build plate locations on the presence of swelling detected in situ. Swelling near the edge of the part and swelling in the internal region of the part are shown to correlate with different process conditions. Edge and internal swelling may be driven by different phenomena, with edge swelling predominately occurring on the edge of a part facing the laser module and correlated to clusters of near-surface voids (detected with X-ray computed tomography). A larger spot size, higher laser power, and lower scan velocity also increased the presence of edge swelling. Laser spot size and scan path influenced internal swelling, which occurred preferentially with a larger spot size and in regions with large melt pools, caused by localized heat accumulation due to non-optimal processing parameters or scan path strategies. For coupons processed with a slicer-defined maximum scan vector length, swelling seldom occurred at internal vector-stripe boundaries. These results provide a mechanistic understanding of how swelling can be linked to material flaws, insight into how some instances of swelling can be avoided, and evidence supporting the use of swelling as an in situ indicator for quality assurance and part qualification.

Anomaly↗
DOE OSTI2026

In situ study on radiation response of tungsten manufactured by laser powder bed fusion

Tungsten (W) produced by laser powder bed fusion (LPBF) was examined by in situ Krypton (Kr) ion irradiation at 400 °C up to 2.52 displacements per atom (dpa) to investigate its radiation response. Dislocation loops with identical Burgers vectors form aligned raft structures, inducing significant grain misorientation accumulation. Defect saturation was observed beyond 0.36 dpa, marked by constant loop density and raft spacing. WO 3 nanoparticles are found in the as-printed matrix and served as efficient defect sinks. Dislocation loops were absorbed at the W/WO 3 interface, facilitating defect annihilation and suppressing defect accumulation. In conclusion, these findings highlight the role of LPBF microstructure and oxide interfaces in mediating radiation-induced defect evolution, offering insights for designing radiation tolerant W-based materials.

Defect sink↗
DOE OSTI2026

Establishing an acoustic-property relationship in laser powder bed fusion with machine learning

Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.

Acoustic emission↗
DOE OSTI2024

An experimental process parameter study on the identification of defects in additively fabricated Al6061 with laser powder bed fusion

Additively fabricated metal parts using laser powder bed fusion (L-PBF) possess sophisticated morphology due to the recurrent use of laser-induced metal powder melting and solidification. The surface and 3D morphology of these parts often include defects in the form of protrusions, depressions, pores, voids, keyholes, or cracks that are known to be influenced by laser scanning paths and layer-to-layer processing. Such inconsistent part quality hampers the extensive adoption of L-PBF. Pores and cracks are detrimental to the fatigue life of the parts and components. Quantifying and controlling part defects and optimizing processing and scanning strategy parameters adaptively in real-time through in situ monitoring systems are highly desired. This study investigates the optimization of experimental process parameters (power, scan velocity, and hatch spacing) and their effects on the cracking and porosity of Al6061 alloy using machine learning techniques. Multi-objective optimization is formulated and conducted to determine the L-PBF parameters that minimize both porosity and crack densities.

36 MATERIALS SCIENCE↗