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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gas pore correlations in laser powder bed fusion of Al6061

Additive manufacturing (AM) of metal materials based on powder bed fusion technology is widely used now in many industries. A known limitation of this type of manufacturing is the formation of gas pores in the bulk material. Here we present a combined X-ray imaging and mid-infrared pyrometry study of pore formation in side-by-side tracks of Al6061 for different processing conditions using both in-situ and post-processing analysis. By carefully quantifying the distributions and correlations of pore positions, we show that an existing pore in one track often catalyzes the formation of another pore in an adjacent track. In a raster scan strategy commonly used to construct bulk material, this phenomenon has the result of forming subsurface perforations, or lines of pores transverse to the scanning direction in a rastered patch. If controlled, this effect can be eliminated to improve the yield strength of the build, or exploited to create programmable failures for specific purposes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A computational study of the effects of graphene additions on electrical properties of polycrystalline copper

The addition of graphene has recently shown promise as a route for the significant improvement of the bulk electrical properties of metallic materials. Here, we explore the effects these additions have on the net electrical conductivity of fabricated copper-graphene (Cu-Gr) nanocomposites as a function of grain structure and grain boundary properties. Synthetic 3D microstructures were generated to represent polycrystalline copper with different average grain diameters and twinned grain boundary fractions. Then, the Poisson equation of electrical transport was solved using a finite difference method in order to predict the net electrical conductivity of each microstructure. In this context, the potential effect of graphene on the conductivity of the composite was evaluated as a function of the number of affected grain boundaries. The results of these calculations indicate that 1.) as supported by literature, net electrical conductivity decreases with decreasing grain size, 2.) the presence of twinned grain boundaries results in smaller loss of conductivity than would otherwise be expected, and 3.) the presence of graphene on the grain boundaries can be expected to lead to improvements in net electrical conductivity. However, we also find that 4.) when the Cu grain structure becomes sufficiently refined, the addition of graphene could conceivably result in significant improvements in electrical conductivity over and above coarse-grained Cu. It is estimated from our calculations that, assuming microstructures with average grain sizes between 100 nm and 100 μm and graphene conductivity 1000 to 10,000 that of a typical Cu grain boundary, an improvement in electrical conductivity of approximately 17% over that of bulk Cu may be attainable. Therefore, by performing this study we suggest a possible route for the improvement of Cu electrical properties through the addition of graphene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

From anti-Arrhenius to Arrhenius behavior in a dislocation-obstacle bypass: Atomistic simulations and theoretical investigation

Dislocations are the primary carriers of plasticity in metallic materials. Understanding the basic mechanisms for dislocation movement is paramount to predicting the material mechanical response. Relying on atomistic simulations, we observe a transition from non-Arrhenius to Arrhenius behavior in the rate of an edge dislocation overcoming the long-range elastic interaction with a prismatic loop in tungsten. Close to the critical resolved shear stress, the process shows a non-Arrhenius behavior at low temperatures. However, as the temperature increases, the activation entropy starts to dominate, leading to a traditional Arrhenius-like behavior. Here, we have computed the activation entropy analytically along the minimum energy path following Schoeck’s method, which captures the cross-over between anti-Arrhenius and Arrhenius domains. Also, the Projected Average Force Integrator (PAFI), another simulation method to compute free energies along an initial transition path, exhibits considerable concurrence with Schoeck’s formalism. We conclude that entropic effects need to be considered to understand processes involving dislocations bypassing elastic barriers close to the critical resolved shear stress. More work needs to be performed to fully understand the discrepancies between Schoeck’s and PAFI compared to molecular dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗
DOE OSTI2020

Understanding Asteroid 16 Psyche’s composition through 3D impact crater modeling

Asteroid 16 Psyche is the largest M-type (metallic) Main Belt Asteroid (MBA). Radar albedo data indicate Psyche’s surface is rich in metallic content, but estimates for Psyche’s bulk structure vary widely, with bulk density estimates ranging from 1.4 ± 0.3 g/cm 3 to 4.5 ± 1.4 g/cm 3 and porosity estimates ranging from 30% to 70%. A forthcoming NASA discovery mission will visit Psyche. Narrowing the range of estimated compositions of Psyche prior to mission launch can help to determine the necessary tools for asteroid analysis. Psyche has two large impact structures in its Southern hemisphere, with estimated diameters from 50 km to 70 km and estimated depths up to 6.4 km. In this work, we present results from 2D and 3D hydrocode simulations of the largest of these impact structures. Through quantitative comparison of the simulated crater dimensions with measured values, our models suggest that Psyche is largely composed of porous, metallic material. In addition, to match the crater dimensions, our simulations indicate that the angle of impact was significantly altered from vertical by 45–60 degrees.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Improved adhesion of polyurethane-based nanocomposite coatings to tin surface through silane coupling agents

Conformal coatings with higher adhesion strength is critical for mitigating the growth of whiskers from the pure tin (Sn) or Sn-rich surfaces of the Pb-free electronics. Silane coupling agents have the ability to form a durable bond between polymeric coatings and metallic materials. The main goal of this paper is to investigate the effect of silane agents on the adhesion behavior of polyurethane (PU), polyurethane acrylate (PUA) and both coatings filled with silicone rubber (SR) nanoparticles on the tin solder pads. It was found that an isocyanate-based silane provided excellent adhesion for PU and PU + SR coatings and an acrylic-based silane for PUA and PUA + SR coatings on the tin surface. This was due to the reaction bond formation between the silane coupling agent and the coating. Hence, the selection of silane coupling agents with the organofunctional group similar to the coating material is crucial to improve the adhesion properties of the coating.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A cycle-jump acceleration method for the crystal plasticity simulation of high cycle fatigue of the metallic microstructure

For metallic materials, high-cycle fatigue life is sensitive to underlying microstructure features including secondary phases, textures, grains morphology, etc. The traditional, data-based safe-life approaches for modeling fatigue don’t explicitly consider the microstructure and can’t guide study in microstructure modification for improved fatigue property. Crystal plasticity-based simulation provides increased model fidelity at the expense of immense computation time, making it inapplicable for high cycle fatigue. In this work, an acceleration method based on cycle-jump approach (Lesne and Savalle, 1989) was developed for microstructure-based high-cycle FE simulation using crystal plasticity constitutive-model. We report this method demonstrated high efficiency in benchmark tests of various conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experimental verification of a crystal plasticity-based simulation framework for predicting microstructure and geometric shape changes: Application to bending and Taylor impact testing of Zr

This paper is concerned with experimental verification of a recently developed multi-scale simulation framework for plastic deformation of metallic materials from quasi-static to impact deformation conditions. The framework is a visco-plastic self-consistent (VPSC) polycrystalline model embedded in an implicit finite element method (FE-VPSC) to provide a microstructure-sensitive constitutive response at each material point. Each material point of the FEM model is a polycrystalline aggregate with crystallographic deformation mechanisms operating at the single crystal scale with their evolving activity based on a dislocation density-based hardening law and texture. Four beams and three cylinders machined in different orientations from a textured plate of high-purity zirconium are tested quasi-statically in 4-point bending and at speeds of 100 m/s, 170 m/s and 243 m/s during Taylor impact tests, respectively. The variation in dimensional changes resulting from different sample orientations in the plate with respect to loading directions is measured for each sample. Moreover, texture and twinning characterization is performed using electron backscattered diffraction (EBSD). The deformation processes and underlying evolution of microstructure are successfully simulated using the FE-VPSC framework. In doing so, the model parameters are optimized and validated across a broad range of strain rates and temperatures. Simulation results in terms of geometrical changes and microstructural evolution are compared with the experimental measurements. The model predicts anisotropic material flow resulting from the hard-to-deform crystallographic directions, the development of gradients in texture and twinning through the geometries, tension–compression asymmetry, as well as the extent of plasticity under impact.

42 ENGINEERING↗
DOE OSTI2025

Attribution of heterogeneous stress distributions in low-grain polycrystals under conditions leading to damage

In high-purity polycrystalline metallic materials, voids tend to favor grain boundaries as nucleation sites due to the elevated stress states produced by granular interactions and the weakened grain boundary from the relative atomic disorder. To quantify the key factors of this elevated stress state, simple compression of a small multi-grain cylinder of body-centered cubic tantalum was simulated using a single crystal plasticity model that incorporates non-Schmid effects. Four increasingly complex synthetic microstructures were created to tractably incorporate grain boundary interactions, and a statistically significant number of combinations were performed by varying the initial crystallographic orientations of the microstructure. Most of these simulations produce the maximum von Mises stress on a grain boundary and less frequently at the multi-grain junctions. To build a statistical model for the maximum von Mises stress at the grain boundary, physically based features that could contribute to the elevated stress state were selected. Then, a learning algorithm based on information theory was used to identify which of these features contributed the most information to the data set. The identified features include a grain’s propensity to accommodate both elastic and plastic deformations and their directional components. The misalignment of the direction of each grain’s mechanical response was found to be strongly correlated to the magnitude of the stress near the grain boundary. For all of the synthetic microstructures, the statistical models produce a residual distribution that is nearly Gaussian with a variance of, at most, 10% of the prior distribution. The successful performance of the statistical model implies the correct identification of the physical features that cause severe stress localization in polycrystalline materials. The statistical models constructed here can be used to formulate a physically motivated void nucleation model which is sensitive to a microstructure’s propensity to produce elevated stress states. As a result, these statistical models also enable the design of material microstructures, in which the crystallographic orientation is chosen to resist void nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Magnetic anisotropy in two-orbital models

Motivated by the recent first-principle discovery of giant perpendicular magnetic anisotropy (PMA) in Fe/III–V nitride thin films, we theoretically study magnetic crystalline anisotropy(MCA) in a series of lattices with trigonal symmetry. Due to the trigonal crystal field, MCA in these lattices is dominated by first-order perturbation of the spin–orbit coupling (SOC) in the atomic limit, instead of second-order in conventional transition metal materials. In particular, the proportionality between MCA and SOC is robust in Kagome and pyrochlore lattices due to the flat bands therein. While in triangle lattice the second-order relation is restored under the bandwidth effect. Furthermore, these findings give rise to a new understanding of magnetic anisotropy and provide a guide for the future hunting of high PMA materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cantor-derived medium-entropy alloys: bridging the gap between traditional metallic and high-entropy alloys

The year 2004 marked the beginning of a new era in the design of metallic materials, as the concept of multiple principal component alloys, commonly known as High-Entropy Alloys (HEAs), was proposed by Cantor and Yeh. The unexpected single-phase microstructure, instead of the expected brittle intermetallic compounds, was attributed to the large entropy of mixing and immediately caught the attention of the scientific community. Today, HEAs are considered important advanced materials and a broad range of alloys using nominally the same design principle have been investigated. Despite that, the CrMnFeCoNi (Cantor) alloy stands out as the most successful HEA due to its outstanding mechanical properties and microstructure. In this scenario, variants of the Cantor alloy, named medium-entropy alloys (MEAs), are gaining significant interest as they display a better industrial potential than both HEAs and traditional alloys. These variants of the Cantor alloy with only three or four main elements result in 15 possible combinations. The microstructure of these alloys is discussed in terms of advanced characterization as well as thermodynamic parameters and computational simulation. Their phase stability is addressed over a wide range of temperatures and strain rates. The mechanical properties, especially the fracture toughness, of the CrFeCoNi and CrCoNi alloys have been reported to be even superior to those of the Cantor alloy and most modern engineering alloys. This is associated with the formation of a continuous sequence of strengthening mechanisms, including hierarchical twin networks, which serve to prolong the strain hardening. The present article reviews and critically assesses, for the first time, recent advances in these Cantor-derived MEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enhancing fatigue life of aluminum alloy castings through cavitation water jet peening: Experiments and simulations

This study presents an investigation into the enhancement of the fatigue life of aluminum castings through the application of cavitation water-jet peening (CWJP). CWJP harnesses the impacts of water cavitation to induce surface compressive residual stress within metallic materials. In this work, CWJP was applied to a high pressure die-cast (HPDC) Al–Si alloy A380 with three different water-jet traverse velocities. The fatigue-life improvement, evaluated in a 4-point bending configuration (stress ratio R = 0.1), was found to vary with applied stress level and ranges from 1.6 to 10 times that of the parent alloy. The data also shows that decreasing the traverse velocity results in greater compressive residual stresses within the surface layer and a concurrent increase in surface roughness. This residual stress layer extends to a depth of 400 μm below the surface, as confirmed by through-thickness residual stress and microhardness measurements. CWJP treatment effectively slows down fatigue crack propagation, as evidenced by microstructural observations of narrower striation spacing. Simulations reveal that compressive residual stresses, in addition to surface hardening during CWJP, are key to improving fatigue life. A 20% increase in surface hardness and 150 MPa compressive residual stress imposed by CWJP process provides an average 5-fold enhancement of fatigue life across different stress levels. This study demonstrates the potential of CWJP as an effective surface treatment to enhance the fatigue life of aluminum castings, such as HPDC components for automotive applications.

Al casting↗
DOE OSTI2021

Heavy ion irradiation response of an additively manufactured 316LN stainless steel

Additive manufacturing has become an appealing technique to fabricate three-dimensional metallic materials and components for nuclear reactors. However, response of additively manufactured alloys to high-dose heavy ion irradiations at elevated temperatures is still not well understood. Here, an additively manufactured 316LN austenitic stainless steel with high-density solidification cells was irradiated using 3.5 MeV Fe ion to a peak dose of 220 dpa at 450 °C. Microscopy studies show a lower Frank loop density and smaller size in the additively manufactured sample compared with its cold worked counterpart, and the cellular structures may largely suppress the formation of perfect loops and dislocation networks and reduce the magnitude of solute segregations comparing with high angle grain boundaries. In conclusion, the present work advances the understanding on the high-temperature irradiation response of additively manufactured steels for nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal conversion of unsolvated Mg(B3H8)2 to BH4- in the presence of MgH2

In the search for energy storage materials, metal octahydrotriborates, M(B3H8)n, n=1,2, are promising candidates but their synthesis suffers from residual solvents which tend to interact and greatly alter their decomposition mechanism. Therefore, we studied the thermal conversion of unsolvated Mg(B3H8)2 to BH4 -: as synthesized, and in the presence of MgH2. The conversion of our unsolvated Mg(B3H8)2 starts at ~100°C and yields ~22 wt% of BH4 - along with the formation of (closo-hydro)borates and volatile boranes. This loss of boron (B) is a sign of poor cyclability of the system. However, the addition of MgH2 to unsolvated Mg(B3H8)2 drastically increases the thermal conversion to 85-88wt% of BH4 - while simultaneously decreasing the amounts of B-losses. Our results strongly indicate that the presence of activated MgH2 substantially decreases the formation of (closohydro) borates and provides the necessary H2 for the B3H8-to-BH4 conversion. This is the first report of a metal octahydrotriborate system to selectively convert to BH4 - under moderate conditions of temperature (200°C) in less than 1h, making the MgB3H8-MgH2 system very promising for energy storage applications.

Gigante, Angelina↗
DOE OSTI2023

Interplanar Ferromagnetism Enhanced Ultrawide Zero Thermal Expansion in Kagome Cubic Intermetallic (Zr,Nb)Fe 2

A cubic metal exhibiting zero thermal expansion (ZTE) over a wide temperature window demonstrates significant applications in a broad range of advanced technologies but is extremely rare in nature. Here, enabled by high-temperature synthesis, we realize tunable thermal expansion via magnetic doping in the class of kagome cubic (Fd-3m) intermetallic (Zr,Nb)Fe 2 . A remarkably isotropic ZTE is achieved with a negligible coefficient of thermal expansion (+0.47 x 10 -6 K -1 ) from 4 to 425 K, almost wider than most ZTE in metals available. A combined in situ magnetization, neutron powder diffraction, and hyperfine Mössbauer spectrum analysis reveals that interplanar ferromagnetic ordering contributes to a large magnetic compensation for normal lattice contraction upon cooling. Trace Fe-doping introduces extra magnetic exchange interactions that distinctly enhance the ferromagnetism and magnetic ordering temperature, thus engendering such an ultrawide ZTE. Finally, this work presents a promising ZTE in kagome metallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Simulating the mechanisms of serrated flow in interstitial alloys with atomic resolution over diffusive timescales

Abstract The Portevin-Le Chatelier (PLC) effect is a phenomenon by which plastic slip in metallic materials becomes unstable, resulting in jerky flow and the onset of inhomogeneous deformation. The PLC effect is thought to be fundamentally caused by the dynamic interplay between dislocations and solute atoms. However, this interplay is almost always inaccessible experimentally due to the extremely fine length and time scales over which it occurs. In this paper, simulations of jerky flow in W-O interstitial solid solutions reveal three dynamic regimes emerging from the simulated strain rate-temperature space: one resembling standard solid solution strengthening, another one mimicking solute cloud formation, and a third one where dislocation/solute coevolution leads to jerky flow as a precursor of dynamic strain aging. The simulations are carried out in a stochastic framework that naturally captures rare events in a rigorous manner, providing atomistic resolution over diffusive time scales using no adjustable parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Upcycled high-strength aluminum alloys from scrap through solid-phase alloying

Although recycling secondary aluminum can lead to energy consumption reduction compared to primary aluminum manufacturing, products produced by traditional melt-based recycling processes are inherently limited in terms of alloy composition and microstructure, and thus final properties. To overcome the constraints associated with melting, we have developed a solid-phase recycling and simultaneous alloying method. This innovative process enables the alloying of 6063 aluminum scrap with copper, zinc, and magnesium to form a nanocluster-strengthened high-performance aluminum alloy with a composition and properties akin to 7075 aluminum alloy. The unique nanostructure with a high density of Guinier-Preston zones and uniformly precipitated nanoscale η‘/Mg(CuZn) 2 strengthening phases enhances both yield and ultimate tensile strength by >200%. By delivering high-performance products from scrap that are not just recycled but upcycled , this scalable manufacturing approach provides a model for metal reuse, with the option for on-demand upcycling of a variety of metallic materials from scrap sources.

36 MATERIALS SCIENCE↗