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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Design for Additive Manufacturing: Exploring Remelt Strategies to Tailor Density and Microstructure

The potential advantages of AM (e.g. weight reduction, novel geometries) are well understood within a systems context. However, adoption of AM at the system level has been slow due to the relative uncertainty in the final material properties, which leaves capabilities and/or performance gains unrealized. Utilizing remelt strategies it may be possible to expand the available process window to provide densities and microstructures beyond what is capable with standard scan strategies. This work explored remelting strategies for 316L stainless steel to tailor grain size and increase density. Twelve scan strategies were explored experimentally and computationally to understand the limitations of remelt strategies and the robustness of the current simulation package. Results show tailoring of grain size, density, and texture is achievable through remelting and several key lessons learned were made to improve the texture evaluation through simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗
NASA NTRS2017

Magnesium Alloys for Space Hardware Design

There have been advances in magnesium alloy development that NASA has not taken into consideration for space hardware because of a lack of test data. Magnesium alloys offer excellent weight reduction, specific strength, and deep space radiation mitigation. Traditionally, magnesium has been perceived as having too poor of a flammability resistance and corrosion resistance to be used for flight. Recent developments in magnesium alloying has led to the formation of two alloys, WE43 and Elektron 21, which are self-extinguishing and significantly less flammable because of their composition. Likewise, an anodizing process called Tagnite was formulated to deter any concern with galvanic and saltwater corrosion. The Materials Science Branch at Kennedy Space Center is currently researching these new alloys and treatments to better understand how they behave in the harsh environment of space. Successful completion of the proposed testing should result in a more thorough understanding of modern aerospace materials and processes, and possibly the permission to use magnesium alloys in future NASA designs.

microstructure↗
DOE OSTI2026

Microstructural stability of irradiated yttrium hydride under thermal cycles

Hydrides that retain their hydrogen in service are critical for advanced microreactor and space nuclear systems. Hydrogen retention is affected by evolving microstructure under temperature and irradiation extremes. This study investigated microstructural features in neutron-irradiated yttrium hydride and the stability of these features under thermal cycles. Differential scanning calorimetry was used to determine hydrogen desorption and temperatures at which significant phase changes are occurring, and transmission electron microscopy was used for microstructural analysis after each thermal cycle. Cyclic heating led to crystallization and epitaxial growth of surface oxidation and dehydriding of the matrix. Other features such as the bulk matrix crystal structure, irradiation-induced cavities, and matrix precipitation remained constant after thermal cycling. Results allow us to design better hydride alloys through microstructure tailoring and potential irradiation conditioning treatments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Microstructural characteristics of σ phase and P phase in Ru-containing single crystal superalloys

Microstructural instability caused by topologically close-packed (TCP) phase precipitation restricts the useful compositional range of advanced Ni-base single crystal superalloys in industrial applications. Limited systematic investigations of TCP formers (Cr and Mo) additions on microstructural evolution of both the σ phase and the P phase in Ru-containing single crystal superalloys have been reported. In this study, the microstructural characteristics of σ phase and P phase were investigated in three Ru-containing superalloys with different levels of Cr and Mo additions at 950 °C and 1100 °C by using phase extraction, X-ray diffraction, scanning electron microscope and high resolution transmission electron microscopy. The experimental results indicated that the high level additions of Cr and Mo promoted the formation of σ phase and P phase, respectively. The amount of σ phase was much higher than that of P phase after long term exposure at 950 °C and 1100 °C. The sheet-like σ phase existed in the alloy with higher Cr addition after thermal exposure at 950 °C and 1100 °C for 1000 h, while the needle-like P phase precipitated in high Mo content alloy after thermal exposure at 1100 °C for 1000 h and the intergrowth of σ phase and P phase was observed after thermal exposure at 950 °C for 500 h. Both the σ phase and P phase were enriched in Re, W, Cr and Mo, but the σ phase contained more Re and Cr while the P phase contained more Mo and Ni, and Ru was found in both phases. The nucleation of σ phase was much easier than P phase due to the more ledge steps in the interfacial structure between σ phase and matrix, as well as the higher partitioning ratios of Re, Cr and Mo. This study is helpful to understand the microstructural evolution of σ phase and P phase, and to optimize the alloy design in Ru-containing superalloys. - Highlights: •Microstructures of σ phase and P phase were characterized in detail. •Cr and Mo influenced the precipitation of σ phase and P phase, respectively. •Partitioning ratios and interfacial relationship decided precipitation behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Fracture toughness of plasma-sprayed thermal barrier ceramics: Influence of processing, microstructure, and thermal aging

Fracture toughness has become one of the dominant design parameters that dictates the selection of materials and their microstructure to obtain durable thermal barrier coatings (TBCs). Much progress has been made in characterizing the fracture toughness of relevant TBC compositions in bulk form, and it has become apparent that this property is significantly affected by process-induced microstructural defects. In this investigation, a systematic study of the influence of coating microstructure on the fracture toughness of atmospheric plasma sprayed (APS) TBCs has been carried out. Yttria partially stabilized zirconia (YSZ) coatings were fabricated under different spray process conditions inducing different levels of porosity and interfacial defects. Fracture toughness was measured on free standing coatings in as-processed and thermally aged conditions using the double torsion technique. Results indicate significant variance in fracture toughness among coatings with different microstructures including changes induced by thermal aging. Comparative studies were also conducted on an alternative TBC composition, Gd 2 Zr 2 O 7 (GDZ), which as anticipated shows significantly lower fracture toughness compared to YSZ. Furthermore, the results from these studies not only point towards a need for process and microstructure optimization for enhanced TBC performance but also a framework for establishing performance metrics for promising new TBC compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tailoring plasticity mechanisms in compositionally graded hierarchical steels fabricated using additive manufacturing

Abstract While there exists in nature abundant examples of materials with site-specific gradients in microstructures and properties, engineers and designers have traditionally used monolithic materials with discrete properties. Now, however, additive manufacturing (AM) offers the possibility of creating structures that mimic some aspects of nature. One example that has attracted attention in the recent years is the hierarchical structure in bamboo. The hierarchical architecture in bamboo is characterized by spatial gradients in properties and microstructures and is well suited to accommodate and survive complex stress states, severe mechanical forces, and large deformations. While AM has been used routinely to fabricate functionally graded materials, this study distinguishes itself by leveraging AM and physical metallurgy concepts to trigger cascading deformation in a single sample. Specifically, we have been successful in using AM to fabricate steel with unique spatial hierarchies in structure and property to emulate the structure and deformation mechanisms in natural materials. This study shows an improvement in the strength and ductility of the nature-inspired “hierarchical steel” compared with conventional cast stainless steels. In situ characterization proves that this improvement is due to the sequential activation of multiple deformation mechanisms namely twinning, transformation-induced plasticity, and dislocation-based plasticity. While significantly higher strengths can be achieved by refining the chemical and processing technique, this study sets the stage to achieve the paradigm of using AM to fabricate structures which emulate the flexibility in mechanical properties of natural materials and are able to adapt to in-service conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mechanical Properties of Tritium Precharged and Aged Additively Manufactured Austenitic Stainless Steel

What is “known” about tritium effects on austenitic steel • Decreased ductility and fracture resistance • Hardening/strengthening • Hydrogen is believed to interact with dislocations, grain boundaries, vacancies, and other microstructural features2 • But what about AM?? • Similar behavior/trends? • How do we account for differences between AM and forged? • Can we design based on material with similar microstructure that has already been tested?

Wieber, Natalie [Savannah River National Laborator↗
DOE OSTI2017

Elucidating the Irreversible Mechanism and Voltage Hysteresis in Conversion Reaction for High-Energy Sodium-Metal Sulfide Batteries

We present that irreversible electrochemical behavior and large voltage hysteresis are commonly observed in battery materials, in particular for materials reacting through conversion reaction, resulting in undesirable round-trip energy loss and low coulombic efficiency. Seeking solutions to these challenges relies on the understanding of the underlying mechanism and physical origins. Here, this study combines in operando 2D transmission X-ray microscopy with X-ray absorption near edge structure, 3D tomography, and galvanostatic intermittent titration techniques to uncover the conversion reaction in sodium–metal sulfide batteries, a promising high-energy battery system. This study shows a high irreversible electrochemistry process predominately occurs at first cycle, which can be largely linked to Na ion trapping during the first desodiation process and large interfacial ion mobility resistance. Subsequently, phase transformation evolution and electrochemical reaction show good reversibility at multiple discharge/charge cycles due to materials' microstructural change and equilibrium. The origin of large hysteresis between discharge and charge is investigated and it can be attributed to multiple factors including ion mobility resistance at the two-phase interface, intrinsic slow sodium ion diffusion kinetics, and irreversibility as well as ohmic voltage drop and overpotential. In conclusion, this study expects that such understandings will help pave the way for engineering design and optimization of materials microstructure for future-generation batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generalized thermo-mechanical framework for heterogeneous materials through asymptotic homogenization

Abstract A fundamental understanding of the interaction between microstructure and underlying physical mechanisms is essential, especially for developing more accurate multi-physics models for heterogeneous materials. Effects of microstructure on the material response at the macroscale are modeled by using the generalized thermomechanics. In this study, strain gradient theory is employed as a higher-order theory on the macroscale with thermodynamics modeled as a first-order theory on the microscale. Hence, energy depends only on the temperature such that we circumvent an extension of Fourier’s law and analyze the “simplest” thermo-mechanical model in strain gradient elasticity. Developing multiphysics models for heterogeneous materials is indeed a challenge and even this “simplest” model in generalized thermomechanics creates dozens of parameters to be determined. We develop a thermo-mechanical framework, in which microstructure is modeled as a periodic structure and through asymptotic homogenization approach, higher-order parameters at macroscopic scale are calculated. To illustrate the importance of higher-order parameters in overall thermo-mechanical response of a heterogeneous materials, finite element method (FEM) is employed with the aid of open-source codes (FEniCS). Verification example of a bulk system and several case studies of porous structures demonstrate how such numerical framework can be beneficial in the design of materials with tailored microstructures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

When and Where Lithium Plating Occurs, Its Correlation with Microstructure Heterogeneity, and the Mechanisms That Initiate and Self-Regulate Electrochemical Heterogeneity (A02-0444)

A microstructure scale electrochemical LIB model was used to investigate lithium plating onset, material non-uniform utilization, and in-plane heterogeneities for an NMC-graphite full cell. Model predicts active material particle surface roughness and size distribution (respectively, non-uniform curvature within and between particles) initiate in-plane heterogeneity, and that particle size heterogeneity at the separator interface controls the lithium plating preferential deposition ("Where"). These in-plane heterogeneities are then exacerbated by through-plane heterogeneities induced at fast charge as electrolyte depletion occurs and concentrates intercalation reaction near the anode-separator interface. Also, magnitude and occurrence of lithium plating is controlled by effective, or macroscale, microstructure parameters ("When"). As local states of charge start to diverge between nearby active material regions, overpotential differences induced by OCP difference kick in and contribute to reduce these SOC local heterogeneities. However, for staged materials such as graphite, with OCP profile alternating between plateaus and varying regions, this balancing mechanism is, respectively, inactive and active. This leads to a dynamic, non-monotonic, in-plane heterogeneity time evolution for state of charge and Faraday current density, for which their respective in-plane heterogeneity magnitude alternates. Such behavior has been modeled both for the whole electrode at the microstructure scale and at the particle scale. In-plane heterogeneities are usually considered to be detrimental, as they result in material non-uniform utilization (i.e., under and over stressed regions) and earlier degradations. However, this work provides a more granular approach as it discriminates between a harmful in-plane heterogeneity (non-uniform curvature) that triggers SOC in-plane heterogeneity, and a beneficial in-plane heterogeneity (Faraday current density) that contributes to reduce SOC in-plane heterogeneity. This work comprehensively explains the mechanisms that initiate, exacerbate, and regulate heterogeneity at the microstructure scale, while providing some design suggestions to reduce both in-plane and through-plane heterogeneities, as summarized in the graphical abstract.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Linking Initial Microstructure to ORR Related Property Degradation in SOFC Cathode: A Phase Field Simulation

Microstructure evolution driven by thermal coarsening is an important factor for the loss of oxygen reduction reaction rates in SOFC cathode. In this work, the effect of an initial microstructure on the microstructure evolution in SOFC cathode is investigated using a recently developed phase field model. Specifically, we tune the phase fraction, the average grain size, the standard deviation of the grain size and the grain shape in the initial microstructure, and explore their effect on the evolution of the grain size, the density of triple phase boundary, the specific surface area and the effective conductivity in LSM-YSZ cathodes. It is found that the degradation rate of TPB density and SSA of LSM is lower with less LSM phase fraction (with constant porosity assumed) and greater average grain size, while the degradation rate of effective conductivity can also be tuned by adjusting the standard deviation of grain size distribution and grain aspect ratio. The implication of this study on the designing of an optimal initial microstructure of SOFC cathodes is discussed.

25 ENERGY STORAGE↗
DOE OSTI2017

DE-NE0000724 - Research Performance Final Report - Investigation of Thermal Aging Effects on the Evolution of Microstructure and Mechanical Properties of Cast Duplex Stainless Steels

This report details the research activities carried out under DOE-NEUP award number DE-NE0000724 concerning the evolution of structural and mechanical properties during thermal aging of CF–3 and CF–8 cast duplex stainless steels (CDSS). The overall objective of this project was to use state-of-the-art characterization techniques to elucidate trends and phenomena in the mechanical and structural evolution of cast duplex stainless steels (CDSS) during thermal aging. These steels are commonly used as structural materials in commercial light water nuclear power plants, undergoing aging for decades in operation as cooling water pipes, pump casings, valve bodies, etc. During extended exposure to these conditions, CDSS are known to undergo a change in mechanical properties resulting in a loss of ductility, i.e. embrittlement. While it is generally accepted that structural changes within the ferrite phase, such as decomposition into iron (Fe)-rich and chromium (Cr)-rich domains, lead to the bulk embrittlement of the steels, many questions remain as to the mechanisms of embrittlement at multiple length scales. This work is intended to shed insight into the atomic level composition changes, associated kinetic mechanisms, and effects of changing phase structure on micro- and nano-scale deformation that lead to loss of impact toughness and tensile ductility in these steels. In general, this project provides a route to answer some of these major questions using techniques such as 3-dimensional (3-D) atom probe tomography (APT) and real-microstructure finite element method (FEM) modeling, which were not readily available when these steels were originally selected for service in light water reactors. Mechanical properties evaluated by Charpy V-notch impact testing (CVN), tensile testing, and microhardness and nanohardness measurements were obtained for each condition and compared with the initial baseline properties to view trends in deformation behavior during aging. Concurrent analysis of the microstructure and nanostructure by atom probe tomography (APT) and transmission electron microscopy (TEM) provide mechanistic insight into the kinetic and mechanical behavior occurring on the nano-scale. The presence and morphology of the ferrite, austenite, and carbide phases have been characterized, and formation of new phases during aging, including spinodal decomposition products (α- and α'-ferrite) and G-phase, have been observed. The mechanical and structural characterization have been used to create accurate FEM models based on the real micro- and nano-structures of the systems. These models provide new insight into the local deformation behavior of these steels and the effects of each individual phase (including ferrite, austenite, carbides, and spinodal decomposition products) on the evolving bulk mechanical behavior of the system. The project was divided into three major tasks: 1. Initial Microstructure and Mechanical Property Survey and Initiate Heat Treatment; 2. Microstructural Characterization and Mechanical Property Testing During Aging; and 3. Microstructure-based Finite Element Modeling. Each of these tasks was successfully executed, resulting in reliable data and analysis that add to the overall body of work on the CDSS materials. Baseline properties and aging trends in mechanical data confirm prior observations and add new insights into the mechanical behavior of the steels. Structural characterization on multiple length scales provides new information on phase changes occurring during aging and sheds light on the kinetic processes occurring at the atomic scale. Furthermore, a combination of mechanical testing and microstructural characterization techniques was utilized to design FEM models of local deformation behavior of the ferrite and austenite phases, providing valuable new information regarding the effects of each of the microstructural components on the hardening and embrittlement processes. The data and analysis presented in this report and the publication associated with this project (§V) increase the understanding of aging and deformation in CF–3 and CF–8 steels. These results provide valuable information that can be utilized to aid in making informed decisions regarding the ongoing use of these steels in commercial nuclear infrastructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Shock propagation in aerogel and TPP foams for inertial fusion energy target design

Achieving practical inertial fusion energy (IFE) requires the development of target designs with well-characterized microstructure and compression response. We measured shock dynamics in low-density (17.5–500 mg/cm 3 ) aerogel and two-photon polymerization (TPP) foams using x-ray phase contrast imaging (XPCI) methods and the Velocity Interferometer System for Any Reflector. By analyzing shock front evolution, we examined how target type and density influence shock propagation and energy dissipation. Talbot-XPCI shows that aerogels support a smooth, bowed shock front due to their homogeneous nanometer-scale pore network. In contrast, TPP foams exhibit irregular, stepwise propagation driven by interactions with their periodic micrometer-scale lattice. Shock velocity follows a power-law relation: aerogels deviate from classical ρ −1/2 scaling due to pore-collapse dissipation, while TPP foams follow the trend with larger uncertainties from density variations. Comparisons with xRAGE simulations reveal systematic underestimation of shock speeds. These results provide the first experimental constraints on shock propagation in TPP foams over a wide density range and highlight the influence of internal structure on anisotropic shock behavior. Our findings support improved benchmarking of EOS and hydrodynamic models and inform the design of foam architectures that promote implosion symmetry in IFE capsules.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Computer vision in microstructural analysis

The following is a laboratory experiment designed to be performed by advanced-high school and beginning-college students. It is hoped that this experiment will create an interest in and further understanding of materials science. The objective of this experiment is to demonstrate that the microstructure of engineered materials is affected by the processing conditions in manufacture, and that it is possible to characterize the microstructure using image analysis with a computer. The principle of computer vision will first be introduced followed by the description of the system developed at Texas A&M University. This in turn will be followed by the description of the experiment to obtain differences in microstructure and the characterization of the microstructure using computer vision.

Srinivasan, Malur N.↗