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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-throughput multimodal exploration of a nanocrystalline Cu-Ag library

Sputter-deposited, nanocrystalline Cu-Ag thin films produced across a broad compositional and deposition-parameter space were evaluated to unravel the process-structure-property relationships important for creating hard, conductive electrical contacts and coatings. Combinatorial deposition involving pulsed direct current magnetron sputtering of elemental targets enabled swift examination of nearly the full range of alloy compositions and a relevant portion of deposition atomistics. Several high-throughput characterization modalities were employed to evaluate the chemistry, structure, and properties of the films. The resultant hardness, modulus, film density, crystal texture, and resistivity were analyzed in terms of key deposition characteristics (incident atom kinetic energy and incidence angle) predicted by binary-collision, kinematic Monte Carlo simulations. The study revealed improved hardness, parabolic resistivity dependence on composition, and compositional and process dependencies of film tarnishing. The results are discussed in the context of variations in microstructure and film density. Transmission electron microscopy and X-ray diffraction demonstrate several forms of compositional variation including solute segregation to grain boundaries as well as periodic, intragranular compositional modulations. Annealing of a Cu-rich alloy film exhibiting grain boundary segregation showed that this as-deposited, compositional variation is not stable above 100 °C. Finally, the Cu-Ag system is shown to have potential for hard, conductive, tarnish-resistant and room temperature-stable nanocrystalline thin films across the composition space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Heat affected zone liquation cracking evaluation on FeMnAl alloys

FeMnAl steels are currently generating a lot of interest with potential applications for structural parts in armored vehicles due to their lower density and outstanding mechanical properties. Despite the extensive mechanical performance and heat treatment exploration of this alloy class, further weldability investigation is required for future large-scale deployment. In the present study, the liquation cracking of four heats of cast FeMnAl alloys was investigated by the spot-Varestraint technique. The study focuses primarily on the effect of the major elements of the FeMnAl system: C, Mn and Al. Optical and electron microscopy were employed to investigate the microstructural features, and CALPHAD was employed to aid the discussion regarding the alloy’s composition differences and their effect on the liquation cracking susceptibility. The study was able to identify that compositions with the higher Mn, C, and lower Al presented the highest liquation cracking susceptibility. Conversely, composition presenting lower Mn, C, and Al showed the most resistant behavior. Furthermore, lower Al content promoted a fully-γ microstructure at low temperatures, which encouraged the appearance of longer cracks as a γ-matrix is more susceptible to HAZ cracking than a fully ferritic (α) or duplex (α + γ) microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Macromolecular gelatin properties affect fibrin microarchitecture and tumor spheroid behavior in fibrin-gelatin gels

The biophysical properties of extracellular matrices (ECM) are known to regulate cell behavior, however decoupling cell behavior changes due to the relative contributions of material microstructure versus biomechanics or nutrient permeability remains challenging, especially within complex, multi-material matrices. We developed four gelatin-fibrin interpenetrating network (IPN) formulations which are identical in composition but possess variable gelatin molecular weight distributions, and display differences in microstructure, biomechanics, and diffusivity. In this work we interrogate the response of multicellular tumor spheroids to these IPN formulations and found that a high stiffness, gelatin-network dominated IPNs impeded remodeling and invasion of multicellular tumor spheroids; whereas relatively lower stiffness, fibrin-network dominated IPNs permitted protease-dependent remodeling and spheroid invasion. Cell proliferation correlated to nutrient diffusivity across tested IPN formulations. These findings demonstrate the complexity of ECM IPNs, relative to single polymer matrices, and highlight that cell response does not derive from a single aspect of the ECM, but rather from the interplay of multiple biomechanical properties. The methodology developed in this study represents a framework for future studies which aim to characterize cellular phenotypic responses to biophysical cues present within complex, multi-material matrices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel–Bronze Composites

In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors’ level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors’ level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis of a 316L stainless steel-copper composite by laser melting

This paper demonstrates a laser melting method to produce a metal matrix composite with a higher thermal conductivity compared to 316 L stainless steel using a Jettable Cu ink. A novel canister was used to control the oxygen level during laser processing to emulate a hybrid inkjet-powder bed fusion technique for doping the stainless steel powder bed with Cu precursor ink. Here, the thermal conductivity of the composite was found to be 187% higher than that of 316 L stainless steel, while the microhardness decreased by 39%. Microstructural results show opportunities to further enhance the thermal conductivity and mechanical properties of the composite by eliminating interfacial cracking.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity

Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.

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

Mesoscale modeling of microstructure-dependent thermal conductivity in U-Zr fuels

In uranium-zirconium (U-Zr) based metallic fuels, different phases can form at different compositions and temperatures. Typically, lamellar δ-UZr 2 and α-U phases are the dominant microstructures in U-rich U-Zr alloys at temperatures below 880 K. In this work, a finite element method based mesoscale modeling technique is used to calculate the effective thermal conductivities of such heterogeneous microstructures, using the thermal conductivities of two individual phases and their interphase thermal resistance (Kapitza resistance) as input parameters. The Kapitza resistance between δ-UZr 2 and α-U is determined at different temperatures, which shows an approximately T 3 dependence in the temperature range between 300 and 800 K. In addition, the Kapitza resistance exhibits a strong dependence on the aspect ratio of the δ-UZr 2 phase. Further, an analytical model is therefore developed to quantify the effects of both temperature and δ-UZr 2 aspect ratio on the Kapitza resistance. Using this newly developed Kapitza resistance model, the effective thermal conductivities of a number of δ-UZr 2 + α-U heterogeneous microstructures in U-Zr alloys, including non-lamellar microstructures, can be estimated accurately.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Cooling rate and dendrite spacing control in direct metal deposition printed Cu-Fe alloys

Over the last several decades, additive manufacturing (AM) has been primarily used for rapid prototyping or to create novel geometries that would be difficult or impossible to create by normal manufacturing methods. More recently, research has been focused on expanding the list of materials that can be made through additive manufacturing, opening a greater range of material properties for this manufacturing method. Due to the unusual conditions during AM, including the high cooling rates and voxel by voxel method of production, AM parts often have anisotropic material microstructures and properties. In this investigation, the laser power, composition, and nozzle head speed during direct metal deposition of copper-iron alloys was varied to understand how the grain structure within the printed parts could be changed and controlled. The resulting dendrite spacing was measured and compared to calculated cooling rates from Gaussian beams on flat plates under similar material and laser properties, which resulted in a cooling rate to dendrite spacing relationship following an inverse square root, as is found in other dendritic systems [Young and Kerkwood, Metall. Trans. A 6, 197–205 (1975)]. Thus, it is demonstrated that in the Cu-Fe system, dendrite spacing can be controlled through manipulation of printing parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying electron transport in aggregated colloidal suspensions in the strong flow regime

Electron transport in complex fluids, biology, and soft matter is a valuable characteristic in processes ranging from redox reactions to electrochemical energy storage. These processes often employ conductor–insulator composites in which electron transport properties are fundamentally linked to the microstructure and dynamics of the conductive phase. While microstructure and dynamics are well recognized as key determinants of the electrical properties, a unified description of their effect has yet to be determined, especially under flowing conditions. In this work, the conductivity and shear viscosity are measured for conductive colloidal suspensions to build a unified description by exploiting both recent quantification of the effect of flow-induced dynamics on electron transport and well-established relationships between electrical properties, microstructure, and flow. These model suspensions consist of conductive carbon black (CB) particles dispersed in fluids of varying viscosities and dielectric constants. In a stable, well-characterized shear rate regime where all suspensions undergo self-similar agglomerate breakup, competing relationships between conductivity and shear rate were observed. To account for the role of variable agglomerate size, equivalent microstructural states were identified using a dimensionless fluid Mason number, Mn f , which allowed for isolation of the role of dynamics on the flow-induced electron transport rate. At equivalent microstructural states, shear-enhanced particle–particle collisions are found to dominate the electron transport rate. This work rationalizes seemingly contradictory experimental observations in literature concerning the shear-dependent electrical properties of CB suspensions and can be extended to other flowing composite systems.

Science & Technology - Other Topics↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2024

Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites

The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.

Athanasiou, Christos↗
DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗
DOE OSTI2022

Creep Behavior and Phase Equilibria in Model Precipitate Strengthened Alumina-Forming Austenitic Alloys

Abstract Creep-rupture behavior and microstructural response in alumina-forming austenitic (AFA) alloys with two different precipitation strengthening mechanisms, “Laves-phase + M 23 C 6 carbide” and “coherent L1 2 γ′-Ni 3 (Al,Ti),” were explored as “model” cases of multi-phase, multi-scale heat-resistant AFA alloys for 650–750°C use. These alloys will be used to guide and verify computational alloy design and life-prediction modeling under an on-going eXtremeMAT project through the Office of Fossil Energy and Carbon Management, US Department of Energy. Computational thermodynamics were used to design and predict the amounts of strengthening and deteriorating secondary phases at 750°C. Creep-rupture lives of the alloys tested at 750°C and 100 MPa were in a range of 4000–9000 h, and the microstructure at the gage/grip after creep-rupture testing was compared with isothermally aged alloys for 1500 h, as well as the calculated phases. Detailed microstructure characterization includes phase identification, volume fraction measurement, and compositional analysis, which were correlated with the creep-rupture properties. High-temperature oxidation resistance was also screened and compared with commercial, chromia-forming heat-resistant steels. These model alloys also provide the basis for further design and optimization of next generation AFA alloys with improved creep resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nonequilibrium spherulitic magnetite in the Ryugu samples

Here, we have investigated several particles collected during each of two touchdowns of the Hayabusa2 spacecraft at the surface of the C-type asteroid 162173 Ryugu using various electron microscope techniques. Our detailed transmission electron microscopy study shows the presence of magnetite with various morphologies coexisting in close proximity. This is characteristic of CI chondrite-like materials and consistent with the mineral assemblages and compositions in the Ryugu parent body. We describe the microstructural characteristics of magnetite with different morphologies, which could have resulted from the chemical conditions (growth vs. diffusion rate) during their formation. Furthermore, we describe the presence of magnetites with a spherulitic structure composed of individual radiating fibers that are characterized by pervasive, homogeneously distributed euhedral to subhedral pores that have not been described in previous chondrite studies. This particular spherulitic structure is consistent with crystallization under nonequilibrium conditions. Additionally, the presence of a high density of defects within the magnetite fibers, the high surface/volume ratio of this morphology, and the presence of amorphous materials in several pores and at the edges of the acicular fibers further support their formation under nonequilibrium conditions. We suggest that the growth processes that lead to this structure result from the solution reaching a supersaturated state, resulting in an adjustment to a lower free energy condition via nucleation and rapid growth.

58 GEOSCIENCES↗
DOE OSTI2020

Laser metal deposition of refractory high-entropy alloys for high-throughput synthesis and structure-property characterization

Progress in materials development is often paced by the time required to produce and evaluate a large number of alloys with different chemical compositions. This applies especially to refractory high-entropy alloys (RHEAs), which are difficult to synthesize and process by conventional methods. To evaluate a possible way to accelerate the process, high-throughput laser metal deposition was used in this work to prepare a quinary RHEA, TiZrNbHfTa, as well as its quaternary and ternary subsystems by in-situ alloying of elemental powders. Compositionally graded variants of the quinary RHEA were also analyzed. Our results show that the influence of various parameters such as powder shape and purity, alloy composition, and especially the solidification range, on the processability, microstructure, porosity, and mechanical properties can be investigated rapidly. The strength of these alloys was mainly affected by the oxygen and nitrogen contents of the starting powders, while substitutional solid solution strengthening played a minor role.

additive manufacturing↗
DOE OSTI2022

Steam oxidation and microstructural evolution of rare earth silicate environmental barrier coatings

A primary failure mode for environmental barrier coatings (EBCs) on SiC ceramic matrix composites (CMCs) is the oxidation of the intermediate Si-bond coating, where the formation of SiO 2 at the bond coating–EBC interface results in debonding and spallation. This work compares the microstructure evolution and steam oxidation kinetics of the Si-bond coating beneath yttrium/ytterbium disilicate ((Y/Yb)DS) and ytterbium disilicate/monosilicate (YbDS/YbMS) EBCs to better understand the impact of EBC composition on oxidation kinetics. After 500 1-h cycles at 1350°C, (Y/Yb)DS displayed a decreasing concentration of the monosilicate minor phase and increasing concentration of porosity as furnace cycling time increased, whereas the YbDS/YbMS EBC displayed negligible microstructural evolution. For both EBC systems, thermally grown oxide growth rates in steam were found to increase by approximately an order magnitude compared to dry air oxidation. The (Y/Yb)DS EBC displayed a reduced steam oxidation rate compared to YbDS/YbMS.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗
DOE OSTI2025

Microstructural Evolution of Steel During Magnetic Field-Assisted Processing

Advancing magnetic field-assisted processing, as an energy-efficient method for tailoring steel microstructures, requires a thorough understanding of how the high magnetic field impacts microstructural evolution, particularly its effect on prior austenite grain structures. The current investigation of a near-eutectoid composition, Fe-C alloy, uses electron backscatter diffraction to examine the morphology and orientation of martensite and pearlite microstructures, and to reconstruct the parent austenite microstructures present during equivalent heating under varied magnetic field strengths (0-T, 2-T, 5-T, and 9-T). It was observed that the magnetic field has a negligible effect on martensite lath/block width, slightly decreases prior austenite grain size, and increases the fraction of austenite grains with annealing twins. Additionally, the magnetic field increases the phase fraction of proeutectoid ferrite but has a negligible effect on pearlite block size and the distribution of boundary misorientation angles. No preferred texture was induced by the magnetic field, regardless of the applied field direction, in the proeutectoid ferrite phase or the martensite and prior austenite microstructures. Furthermore, the observed results contradict previous literature, and the differences are discussed.

Magnetic Materials↗