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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simultaneous optimization of hatching orientations and lattice density distribution for residual warpage reduction in laser powder bed fusion considering layerwise residual stress stacking

The reduction in the residual warpage generated via fabrication is an emerging issue in metals’ laser powder bed fusion additive manufacturing (AM). One solution from a design for additive manufacturing (DfAM) perspective is to arrange a hatching strategy that utilizes the asymmetry of the residual stress generated from a molten pool. Another approach is to arrange the geometry of the parts, such as forming an inner lattice structure to arrange the effective stiffness. In this study, the simultaneous optimization of the laser hatching orientation and lattice density distribution was conducted to minimize the residual warpage in lattice infill structures and confirm their synergetic effect. The mutual effect of each layer was highlighted when considering the mechanical background of the optimal results because an imbalance in the residual stress caused the warpage of the AM parts between the layers. The proposed methodology was validated via experimental verification using a quasi-2D plate, 3D bracket, and 3D connecting-rod design problems. The residual warpage in the quasi-2D study, measured as the edge’s vertical deformation, was reduced from 23.4% to 39.4% compared with the benchmark design. In the 3D studies, the warpage reductions ranged from 13.1% to 20.7%.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observation of spatter-induced stochastic lack-of-fusion in laser powder bed fusion using in situ process monitoring

Material produced via additive manufacturing (AM) continues to exhibit variable mechanical properties despite apparent optimization of processing parameters, inhibiting qualification efforts and limiting use in critical applications. Stochastic lack-of-fusion flaws may help explain this variability, but the origin of these seemingly random defects has to this point remained unclear. In this work, we show that spatter particles, material ejected from the laser melt pool, are directly responsible for generating stochastic lack-of-fusion in laser-based powder bed fusion components through the application of spatial statistics. Herein a statistically significant, causal relationship between spatter particles and stochastic lack-of-fusion is established, and the spatial and morphological relationships between spatter and internal flaws are investigated. The occurrence of spatter-induced lack-of-fusion in relation to the inert gas flow and laser trajectory direction is also investigated, and recommendations for mitigating the occurrence of spatter are evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An assessment of the utility of multirate time integration for the modeling of laser powder bed fusion

Finite element simulation of the laser powder bed fusion process is made challenging by the inherently multiscale nature of the process. When using the typical global time stepping techniques, slowly-evolving regions of the domain receive the same numerical treatment as the regions with the highest temperature rates. The current work details the implementation and evaluation of an implicit multirate method which is able to advance different regions of the domain with distinct time steps, depending on their current solution rate. Previous work indicates that this representation of the temporal scales of the problem can lead to significant reductions in wall clock run time, and it is shown herein that multirate time integration, when used with a uniform process-scale mesh, can result in speedups of approximately 19, 42, and 87 times, for domains with edge lengths of approximately 1 mm, 2 mm, and 5 mm, respectively. When used in conjunction with $\ h$-refinement (limited to two levels of refinement), the resulting speedups (taken relative to the uniform mesh) are around 28, 85, and 665 times. The method is demonstrated to converge as indicated by the literature, and its use with an AM-Bench domain is demonstrated.

42 ENGINEERING↗
DOE OSTI2023

Microstructure and strengthening of Al-6Ce-3Ni-0.7Fe (wt%) alloy manufactured by laser powder-bed fusion

In this study, an Al-6Ce-3Ni-0.7Fe (wt%) alloy was fabricated via laser powder-bed fusion and its microstructure, thermal stability, tensile properties, and creep properties are investigated for two rapid-solidification rates with different eutectic spacings. For both faster- and slower-cooled states, the as-fabricated alloy mostly shows elongated grains with very fine eutectic networks (~40 nm lamellar width) comprising a high-volume fraction (~18 %) of intermetallic phases. Faster-cooled samples, however, display a less continuous eutectic network with finer spacing (~100 nm), leading to higher Orowan strengthening and therefore superior microhardness and yield stress up to ~350 °C. Upon aging (300 - 450 °C), micron-size Al 9 (Ni,Fe) 2 needle-like precipitates form within grains, and the Al 11 Ce 3 eutectic network spheroidizes, while retaining a submicron width and spacing, resulting in 33–37 % drop in microhardness after 144 h aging at 400 °C. Limited tensile ductility (~6 %) and creep ductility (~1-2 %) are measured for both faster- and slower-cooled alloys due to an inhomogeneous microstructure, where cavitation preferentially initiates at melt-pool boundaries, precipitate-free zones, and/or denuded zones, eventually leading to local fracture. Denuded zones, induced by stress, form due to diffusional flow with stress-dependent orientations, and are identified as microstructurally weak regions leading to strain localization. The present alloy does not show a significant difference in 300 °C creep resistance between: (i) tensile and compressive loading, (ii) faster- and slower-cooled samples, and (iii) continuous and spheroidized eutectics. Creep resistance at 300 °C is comparable to that of a Ce-richer Al-10.5Ce-3.1Ni-1.2Mn (wt%) alloy, despite the formation of denuded zones and needle-like Al 9 (Ni,Fe) 2 precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle $θ_s$ is defined based on melt pool overlap geometry, and the range of $θ_s$ over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. Importantly, these results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Harnessing on-machine metrology data for prints with a surrogate model for laser powder directed energy deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. Furthermore, this methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

Digital twins↗
DOE OSTI2025

Ink-based laser powder bed fusion of barium titanate

Barium titanate (BTO) is a lead-free functional ceramic that is widely used in sensors, transducers, and actuators. The increasing demand for complex geometries and quick design iterations motivates the use of additive manufacturing techniques. Laser powder bed fusion (L-PBF) additive manufacturing technique enables the net-shape or near-net-shape fabrication of metals and alloys. Ceramic L-PBF remains challenging due to their high melting temperature. Here, to address this challenge, a nanoparticle ink feedstock was incorporated into the L-PBF process to allow low power melting of BTO. Key print parameters (i.e. laser power, scanning speed, and hatching spacing) were optimized to fabricate millimeter-scale BTO parts. The printed BTO samples possessed an inhomogeneous equiaxed-columnar-cellular microstructure. Semiconducting current-voltage behavior was observed in as-printed samples, which was attributed to the creation of oxygen vacancies. The piezoelectric d 33 coefficient was measured to be 4.6 pC/N.

Dielectrics↗
DOE OSTI2026

Which way does the dendrite grow? Competition among epitaxy, preferred growth direction, and thermal gradients in powder bed fusion additive manufacturing

The as-processed microstructure of metal alloy parts manufactured through laser powder bed fusion (LPBF) is heavily derived from the cellular dendritic solidification. The growth direction of dendrites within the melt pool is determined through competition among epitaxial growth, preferred growth directions, and maximum thermal gradients. However, the dominant factor and the specific role of each in developing melt pool microstructures remain unknown. Here, in this study, we performed single laser track scans on an SS316L single crystal substrate and combined experimental characterization of microstructure and crystal orientations with Computational Fluid Dynamics simulations of thermal gradients to evaluate the role of each factor in determining dendritic growth direction and evolution. Our results reveal that epitaxial growth dominates microstructure development by preferentially growing along a single 〈100〉 variant of the single crystal substrate adjacent to the melt pool boundary. Under LPBF’s highly curved and rapidly evolving thermal field, this preferential dendrite variant selection and its continued growth from the melt pool boundary to the centerline are governed by the local temperature gradient magnitude at the solid-liquid interface, rather than by the instantaneous maximum temperature gradient direction alone. Using these findings, we successfully predict changes in the dendrite growth direction with changing laser scan direction on a single crystal substrate, and show that the geometric melt pool centerline can deviate from the microstructural centerline because asymmetric local temperature gradient magnitudes transiently limit growth, resulting in different dendrite travel distances on each side of the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Oxide dispersion strengthened 304 L stainless steel produced by ink jetting and laser powder bed fusion

This paper discusses the fundamentals of a novel hybrid method to synthesize oxide dispersion strengthened (ODS) 304 L stainless steel (SS) alloy using a modified laser powder bed fusion (LPBF) machine. Previously, ODS metal matrix composites have been produced by LPBF via ball-milling, which is expensive to scale. Here, we selectively dope yttria nanoparticles into a SS matrix by jetting a precursor chemistry onto the SS substrate prior to laser conversion and consolidation. Here, the new alloy shows good room temperature mechanical properties. Microstructures are studied using electron microscopy, energy dispersive spectroscopy and electron backscatter diffraction.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Signatures of rare earth element distributions in fly ash derived from the combustion of Central Appalachian, Illinois, and Powder River basin coals

We report the distribution of Rare Earth elements (REE) in coal-derived fly ashes can have distinctive patterns when fly ashes are produced from different coals within or between basins, such as the Pennsylvanian Class F fly ashes from the Illinois and Central Appalachian basins. Both the Fire Clay coal and a blend of a number of eastern Kentucky coals show strong Gd peaks and an H-type distribution in the Upper Continental Crust-corrected plots. The Fire Clay coal-derived ash has a higher heavy REE concentration than the blended coal-derived ash. The Illinois Basin-derived fly as has an overall lower REE concentration than the latter ashes. Class C fly ash derived from Powder River Basin coals has, with the exception of an Eu peak, a flatter distribution of REE and an overall L-type or indistinct H- versus L-type distribution. The signatures of the REE in fly ashes may be useful in predicting their behavior in the extraction of the REE; simple extrapolations from the basic concentrations and the predicted extraction percentages for ashes from different basins are not necessarily indicative of the actual distribution of the extracted REE.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Brazing characteristics, microstructure, and wettability of laser powder bed fusion additive manufactured GRCop-84 compared to CuCrZr and OFC, and brazing to titanium-zirconium-molybdenum alloy limiters

Laser Powder Bed Fusion (L-PBF) of Glenn Research Copper 84 (GRCop-84), a Cr 2 Nb (8 at. % Cr, 4 at. % Nb) precipitation hardened alloy, produces a fully dense, high conductivity alloy with a yield strength of 500 MPa and ultimate tensile strength (UTS) of 740 MPa with 20% elongation; superior to other competing copper alloys. Braze wetting characteristics of GRCop-84 with Ag-Cu-X, and Au-Cu brazes were similar to CuCrZr, but less than oxygen free copper. No difference in wetting was observed between infill and surface contour areas in L-PBF GRCop-84. Wet sanding to 240 grit (R a =0.24 µm) was considered the optimal surface condition. Silver diffusing through GRCop-84 depleted Cr 2 Nb precipitates from the copper grain and deposited agglomerations of coarsened precipitates within silver-rich regions of intergranular diffusion once a density threshold was reached. Microstructure modification was minimized with 50Au-50Cu braze implying that silver caused precipitate coarsening and agglomeration, and not high temperature exposure. Coarsened precipitates were observed on the surface within braze pools implying a contribution to braze wetting. Palcusil-25, Ticusil, CuSil-ABA, and 50Au-50Cu brazes were suitable for brazing to unplated Titanium-Zirconium-Molybdenum (TZM), while sulfamate nickel plating to allows wetting with CuSil or other non-active brazes. Additionally, vacuum brazing techniques were developed to join a 1 mm thick layer of TZM to the front of additive manufactured GRCop-84 waveguides considering the brazing characteristics of both GRCop-84, TZM, and internal stress from the difference in coefficient in thermal expansion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Size effect characteristics and influences on fatigue behavior of laser powder bed fusion of thin wall GRCop-42 copper alloy

Size effects, influencing a material's strength, elongation, fatigue limit, and longevity, depend on the operative and dominant deformation and failure mechanisms. This study explores the size effects in additive manufactured (AM) GRCop-42 (Cu-4at%Cr-2at%Nb) thin wall structures fabricated via laser-powder bed fusion (L-PBF) and their impact on fatigue life. The influence of internal defects and surface topography on the fatigue life of specimens in both as-built and hot isostatic pressed (HIP) conditions across different thicknesses is investigated. Where micro-computed tomography (μCT) was used to quantify the internal porosity of as-built, pristine HIP'd, and fatigued HIP'd specimens, and laser microscopy was employed to quantify the surface topography of specimens prior to fatigue. Additionally, quasi-static tests were used to establish baseline mechanical properties (i.e. yield strength (YS), ultimate tensile strength (UTS), and elongation) to frame fatigue testing conditions. Results indicate a significant enhancement in fatigue life for HIP'd specimens for both thicknesses, with internal defects depicting a greater impact than surface topography. Furthermore, fractographic analysis suggests that thicker specimens exhibit higher resistance to crack propagation during fatigue testing in the absence of substantial porosity. Thus, the size effects observed on the fatigue life of L-PBF GRCop-42 appears to be dominated by internal defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Revealing melt flow instabilities in laser powder bed fusion additive manufacturing of aluminum alloy via in-situ high-speed X-ray imaging

Laser metal additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the certification and qualification of additively manufactured parts are greatly hindered by the stochastic melt flow instabilities intrinsic to the process, which has not been explicitly revealed by direct observation. Here, we report the mechanisms of the melt flow instabilities in laser powder bed fusion additive manufacturing process revealed by in-situ high-speed high-resolution synchrotron X-ray imaging. Here we identified powder/droplet impact, significant keyhole oscillation, and melting-mode switching as three major mechanisms for causing melt flow instabilities. We demonstrated the detrimental consequences of these instabilities brought to the process, and presented new understanding on the melt flow evolution and keyhole oscillation. This work provides critical insights into process instabilities during laser metal additive manufacturing, which may guide the development of instability mitigation approaches. The results reported here are also important for the development and validation of high-fidelity computational models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase evolution during reactive flash sintering of Li 6.25 Al 0.25 La 3 Zr 2 O 12 starting from a chemically prepared powder

Here, reactive flash sintering (RFS) of a chemically prepared multiphase precursor powder was performed to fabricate Li 6.25 Al 0.25 La 3 Zr 2 O 12 (Al-LLZO) ceramics. This approach allowed for obtaining single-phase dense samples in a remarkably short processing time of 30 s, at a furnace temperature of 600 °C, with an electric field of 50 V cm -1 and a current limit of 150 mA mm -2 . The ceramics display high bulk conductivity of 0.18 mS cm -1 at room temperature. Furthermore, phase evolution is studied by in-situ X-ray diffraction during: i) conventional heating and ii) RFS under current rate mode. As expected, the intermediate phases progressively dissolved into the Al-LLZO matrix by conventional heating. On the other hand, RFS promoted the growth of the intermediate La 2 Zr 2 O 7 , an effect that was overcome by the thermally driven formation of Al-LLZO at higher temperatures. The observed different reaction pathway suggests that RFS can be used for stabilizing phases that are not thermodynamically favored upon conventional heating.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Additively manufactured β-Ti5553 with laser powder bed fusion: Microstructures and mechanical properties of bulk and lattice parts

Ti5553 (Ti-5Al-5Mo-5V-3Cr wt%) is a titanium alloy widely used for its high strength-to-weight ratio and good formability at elevated temperatures. Unlike Ti-6Al-4V, Ti5553 does not undergo martensitic transformation, preventing cracking of brittle martensite upon rapid cooling. This makes it a strong candidate for additive manufacturing (AM), particularly laser powder bed fusion (L-PBF). L-PBF offers the unique opportunity to make fine lattice structures to reduce component weight. Despite the growing field of AM, there have been limited studies on L-PBF Ti5553 lattices and how their properties differ from the bulk. Here the present work addresses this knowledge gap by investigating microstructures and properties of L-PBF bulk and lattice parts and the effect of post L-PBF heat treatments. Electron microscopy and mechanical testing show that the high dislocation density formed during L-PBF increases bulk part’s yield strength by approximately 100 MPa compared to the conventional alloy. Digital image correlation during compression testing of octet truss lattices reveals a layer-by-layer failure mode. Compared to the bulk, the lattice contains copious ω nanoprecipitation, weaker <001> texture, smaller average grain sizes, and larger content of high-angle grain boundaries. These features elicit differences in Taylor factor distributions for the lattice depending on load direction, underlining challenges in predicting lattice mechanical response based on bulk properties. By examining the processing-structure-property relationships in the bulk and lattice, the present results delineate their microstructural and mechanical differences and establish a benchmark for the future design applications of L-PBF Ti5553.

36 MATERIALS SCIENCE↗