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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
NASA NTRS2012

Mars Science Laboratory Navigation Results

The Mars Science Laboratory (MSL), carrying the Curiosity rover to Mars, was launched on November 26, 2011, from Cape Canaveral, Florida. The target for MSL was selected to be Gale Crater, near the equator of Mars, with an arrival date in early August 2012. The two main interplanetary navigation tasks for the mission were to deliver the spacecraft to an entry interface point that would allow the rover to safely reach the landing area, and to tell the spacecraft where it entered the atmosphere of Mars, so it could guide itself accurately to close proximity of the landing target. MSL used entry guidance as it slowed down from the entry speed to a speed low enough to allow for a successful parachute deployment, and this guidance allowed shrinking the landing ellipse to a 99% conservative estimate of 7 by 20 kilometers. Since there is no global positioning system in Mars, achieving this accuracy was predicated on flying a trajectory that closely matched the reference trajectory used to design the guidance algorithm, and on initializing the guidance system with an accurate Mars-relative entry state that could be used as the starting point to integrate the inertial measurement unit data during entry and descent. The pre-launch entry flight path angle (EFPA) delivery requirement was +/- 0.20 deg, but after launch a smaller threshold of +/- 0.05 deg was used as the criteria for late trajectory correction maneuver (TCM) decisions. The pre-launch requirement for entry state knowledge was 2.8 kilometers in position error and 2 meters per second in velocity error, but also smaller thresholds were defined after launch to evaluate entry state update opportunities. The biggest challenge for the navigation team was to accurately predict the trajectory of the spacecraft, so the estimates of the entry conditions could be stable, and late trajectory correction maneuvers or entry parameter updates could be waved off. As a matter of fact, the prediction accuracy was such that the last TCM performed was a small burn executed eight days before landing, and the entry state that was calculated just 36 hours after that TCM, and that was uploaded to the spacecraft the same day, did not need to be updated. The final EFPA was 0.013 deg shallower than the -15.5 deg target, and the on-board entry state was just 200 meters in position and 0.11 meters per second in velocity from the post-landing reconstructed entry state. Overall the entry delivery and knowledge requirements were fulfilled with a margin of more than 90% with respect to the pre-launch thresholds. This excellent accuracy contributed to a very successful and accurate entry, descent, and landing, and surface mission.

navigation↗
DOE OSTI2023

Enhanced resistance to helium irradiations through unusual interaction between high-entropy-alloy and helium

Finding high performance plasma-facing materials (PFMs) is one of the most important and challenging tasks for realizing the commercial application of fusion reactors. Herein, we found the CrMoTaWV high entropy alloy (HEA) is highly resistant to low-energy and high-flux He plasma exposure. The nanochannel HEA film has 20 times higher initial fluence for the formation of fuzz and a remarkable 8.9 times slower fuzz growth rate than those of W. Combining the in-situ TEM observation and the Molecular dynamics (MD) simulation of the He bubble growth process, a new mechanism for the enhanced radiation resistance in HEA with the unusual interaction between HEA and He is found, where, differing from traditional metal, bubble growth in HEA leads to non-directional emission of interstitial atoms while HEA greatly suppress the growth of He bubbles. Additionally, the special nanochannel structure further rise the radiation resistance through releasing He out of the HEA film and reducing the He concentration. This new nanochannel refractory HEA material presents a promising choice as the PFMs with excellent performance and a much longer serving lifetime for future commercial fusion reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Determination of filter pore size for use in HB line phase II production of plutonium oxide

H-Canyon and HB-Line are tasked with the production of plutonium oxide (PuO 2 ) from a feed of plutonium (Pu) metal. The PuO 2 will provide feed material for the Mixed Oxide (MOX) Fuel Fabrication Facility. After dissolution of the Pu metal in H-Canyon, plans are to transfer the solution to HB-Line for purification by anion exchange. Anion exchange will be followed by plutonium(IV) oxalate precipitation, filtration, and calcination to form PuO 2 . The filtrate solutions, remaining after precipitation, contain low levels of Pu ions, oxalate ions, and may include solids. These solutions are transferred to H-Canyon for disposition. To mitigate the criticality concern of Pu solids in a Canyon tank, past processes have used oxalate destruction or have pre-filled the Canyon tank with a neutron poison. The installation of a filter on the process lines from the HB-Line filtrate tanks to H-Canyon Tank 9.6 is proposed to remove plutonium oxalate solids. This report describes SRNL’s efforts to determine the appropriate pore size for the filters needed to perform this function. Information provided in this report aids in developing the control strategies for solids in the process.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Gradient twinned 304 stainless steels for high strength and high ductility

Gradient materials often have attractive mechanical properties that outperform uniform microstructure counterparts. It remains a difficult task to investigate and compare the performance of various gradient microstructures due to the difficulty of fabrication, the wide range of length scales involved, and their respective volume percentage variations. We have investigated four types of gradient microstructures in 304 stainless steels that utilize submicrotwins, nanotwins, nanocrystalline-, ultrafine- and coarse-grains as building blocks. Tensile tests reveal that the gradient microstructure consisting of submicrotwins and nanotwins has a persistent and stable work hardening rate and yields an impressive combination of high strength and high ductility, leading to a toughness that is nearly 50% higher than that of the coarse-grained counterpart. Ex- and in-situ transmission electron microscopy indicates that nanoscale and submicroscale twins help to suppress and limit martensitic phase transformation via the confinement of martensite within the twin lamellar. Twinning and detwinning remain active during tensile deformation and contribute to the work hardening behavior. We discuss the advantageous properties of using submicrotwins as the main load carrier and nanotwins as the strengthening layers over those coarse and nanocrystalline grains. Furthermore, our work uncovers a new gradient design strategy to help metals and alloys achieve high strength and high ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Bayesian optimization with active learning of design constraints using an entropy-based approach

Abstract The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and constraints. Candidate alloys must be ductile at room temperature and retain their yield strength at high temperatures, as well as possess low density, high thermal conductivity, narrow solidification range, high solidus temperature, and a small linear thermal expansion coefficient. Traditional Integrated Computational Materials Engineering (ICME) methods are not sufficient for exploring combinatorially-vast alloy design spaces, optimizing for multiple objectives, nor ensuring that multiple constraints are met. In this work, we propose an approach for solving a constrained multi-objective materials design problem over a large composition space, specifically focusing on the Mo-Nb-Ti-V-W system as a representative Multi-Principal Element Alloy (MPEA) for potential use in next-generation gas turbine blades. Our approach is able to learn and adapt to unknown constraints in the design space, making decisions about the best course of action at each stage of the process. As a result, we identify 21 Pareto-optimal alloys that satisfy all constraints. Our proposed framework is significantly more efficient and faster than a brute force approach.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Finding new perovskite halides via machine learning

Advanced materials with improved properties have the potential to fuel future technological advancements. However, identification and discovery of these optimal materials for a specific application is a non-trivial task, because of the vastness of the chemical search space with enormous compositional and configurational degrees of freedom. Materials informatics provides an efficient approach toward rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning, henceforth referred to as ML) via building a support vector machine (SVM) based classifier that uses elemental features (or descriptors) to predict the formability of a given ABX 3 halide composition (where A and B represent monovalent and divalent cations, respectively, and X is F, Cl, Br, or I anion) in the perovskite crystal structure. The classification model is built by learning from a dataset of 185 experimentally known ABX 3 compounds. After exploring a wide range of features, we identify ionic radii, tolerance factor, and octahedral factor to be the most important factors for the classification, suggesting that steric and geometric packing effects govern the stability of these halides. As a result, the trained and validated models then predict, with a high degree of confidence, several novel ABX 3 compositions with perovskite crystal structure.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications

Typically, thousands of computationally expensive micro-scale simulations of brittle crack propagation are needed to upscale lower length scale phenomena to the macro-continuum scale. Running such a large number of crack propagation simulations presents a significant computational challenge, making reduced-order models (ROMs) attractive for this task. Here, the ultimate goal of this research is to develop ROMs that have sufficient accuracy and low computational cost so that these upscaling simulations can be readily performed. However, constructing ROMs for these complex simulations presents its own challenge. Here, we present and compare four different approaches for reduced-order modeling of brittle crack propagation in geomaterials. These methods rely on machine learning (ML) and graph-theoretic algorithms to approximate key aspects of the brittle crack problem. These methods also incorporate different physics-based assumptions in order to reduce the training requirements while maintaining accurate physics as much as possible. Results from the ROMs are directly compared against a high-fidelity model of brittle crack propagation. Further, the strengths and weaknesses of the ROMs are discussed, and we conclude that combining smart physics-informed feature engineering with highly trainable ML models provides the best performance. The ROMs considered here have computational costs that are orders-of-magnitude less than the cost associated with high-fidelity physical models while maintaining good accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase‐Change‐Memory Process at the Limit: A Proposal for Utilizing Monolayer Sb 2 Te 3

Abstract One central task of developing nonvolatile phase change memory (PCM) is to improve its scalability for high‐density data integration. In this work, by first‐principles molecular dynamics, to date the thinnest PCM material possible (0.8 nm), namely, a monolayer Sb 2 Te 3 , is proposed. Importantly, its SET (crystallization) process is a fast one‐step transition from amorphous to hexagonal phase without the usual intermediate cubic phase. An increased spatial localization of electrons due to geometrical confinement is found to be beneficial for keeping the data nonvolatile in the amorphous phase at the 2D limit. The substrate and superstrate can be utilized to control the phase change behavior: e.g., with passivated SiO 2 (001) surfaces or hexagonal Boron Nitride, the monolayer Sb 2 Te 3 can reach SET recrystallization in 0.54 ns or even as fast as 0.12 ns, but with unpassivated SiO 2 (001), this would not be possible. Besides, working with small volume PCM materials is also a natural way to lower power consumption. Therefore, the proposed PCM working process at the 2D limit will be an important potential strategy of scaling the current PCM materials for ultrahigh‐density data storage.

2D limit↗
DOE OSTI2019

Synthesis and Properties of Poly-Ether/Ethylene Carbonate Electrolytes with High Oxidative Stability

New electrolyte designs are necessary for overcoming multiple challenges posed by emerging lithium-metal battery chemistries. Task-specific viscoelastic electrolytes are specifically required that are capable of simultaneously sustaining reversible electrochemistry at the Li metal anode, maintaining high oxidative stability at the battery cathode and achieving high room-temperature ionic conductivity in the electrolyte bulk. Here, we synthesize and study a series of polymeric electrolytes composed of poly-1,3-dioxolane (poly-DOL) networks formed by ring-opening polymerization of 1,3-dioxolane/ethylene carbonate (EC) mixtures by a commonly used LiPF 6 electrolyte salt. The complex kinetics of the DOL polymerization reaction in EC results in nonlinear phase behavior, including the appearance of a critical transition to an entangled, solid-like electrolyte state at 40% DOL. Additionally, the transition is mediated by a range of physicochemical regimes—from liquid-like solutions to highly viscous conducting gels. We show that poly-DOL/EC electrolytes with a high concentration of the DOL precursor exhibit improved electrochemical stability compared to conventional DOL-based electrolytes, while maintaining good room temperature ionic conductivity. We show further that the EC component imparts oxidative stability, enabling their use in rechargeable, room-temperature Li||LiNi 0.6 Co 0.2 Mn 0.2 O 2 electrochemical cells.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Unsupervised phase mapping of X-ray diffraction data by nonnegative matrix factorization integrated with custom clustering

Abstract Analyzing large X-ray diffraction (XRD) datasets is a key step in high-throughput mapping of the compositional phase diagrams of combinatorial materials libraries. Optimizing and automating this task can help accelerate the process of discovery of materials with novel and desirable properties. Here, we report a new method for pattern analysis and phase extraction of XRD datasets. The method expands the Nonnegative Matrix Factorization method, which has been used previously to analyze such datasets, by combining it with custom clustering and cross-correlation algorithms. This new method is capable of robust determination of the number of basis patterns present in the data which, in turn, enables straightforward identification of any possible peak-shifted patterns. Peak-shifting arises due to continuous change in the lattice constants as a function of composition and is ubiquitous in XRD datasets from composition spread libraries. Successful identification of the peak-shifted patterns allows proper quantification and classification of the basis XRD patterns, which is necessary in order to decipher the contribution of each unique single-phase structure to the multi-phase regions. The process can be utilized to determine accurately the compositional phase diagram of a system under study. The presented method is applied to one synthetic and one experimental dataset and demonstrates robust accuracy and identification abilities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

CFD Study of Countercurrent Flow in Triply Periodic Minimal Surfaces with CO 2 BOL Solvent

Triply periodic minimal surfaces (TPMS) are promising structures for heat exchangers and ultrafiltration due to their high heat and mass transfer efficiency compared to traditional devices. Because of this, the TPMS structures are a potential candidate for building the multifunctional, intensified devices in CO 2 capture tasks. With the Lawrence Livermore National Laboratory’s (LLNL’s) additive manufacturing (AM) capability, these complicated TPMS structures can be printed in the packed column for experimental tests. To optimize the TPMS structure and enable fast prototyping, a computationally-efficient computational fluid dynamics (CFD) framework was established to explore the TPMS structure’s hydrodynamics and mass transfer performance. The established model was able to simulate the countercurrent flows by integrating the Pacific Northwest National Laboratory (PNNL) CO 2 binding organic liquids (CO 2 BOL) solvent into the TPMS structures. Three typical TPMS structures - namely, Gyroid, Schwarz-D, and Schwarz-P - were investigated using the periodic boundary set up in all three directions. Two different unit cell size (1 cm and 2 cm) geometries are tested for each type of TPMS. The solvent flow rate in this study covered a range of [0, 0.1] m/s with an initial liquid film thickness of [0.1, 1.8] mm. These simulations provided a preliminary understanding of the TPMS structure behaviors in countercurrent flow conditions. The study also related the TPMS geometry requirement to the given CO 2 BOL solvent physical property and covered reasonable packed column operation ranges.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Density Functional Theory Investigation of the NiO@Graphene Composite as a Urea Oxidation Catalyst in the Alkaline Electrolyte

Developing efficient and low-cost urea oxidation reaction (UOR) catalysts is a promising but still challenging task for environment and energy conversion technologies such as wastewater remediation and urea electrolysis. In this work, NiO nanoparticles that incorporated graphene as the NiO@Graphene composite were constructed to study the UOR process in terms of density functional theory. The single-atom model, which differed from the previous heterojunction model, was employed for the adsorption/desorption of urea and CO 2 in the alkaline media. As demonstrated from the calculated results, NiO@Graphene prefers to adsorb the hydroxyl group than urea in the initial stage due to the stronger adsorption energy of the hydroxyl group. After NiOOH@Graphene was formed in the alkaline electrolyte, it presents excellent desorption energy of CO 2 in the rate-determining step. Electronic density difference and the d band center diagram further confirmed that the Ni(III) species is the most favorable site for urea oxidation while facilitating charge transfer between urea and NiO@Graphene. Moreover, graphene provides a large surface for the incorporation of NiO nanoparticles, enhancing the electron transfer between NiOOH and graphene and promoting the mass transport in the alkaline electrolyte. Notably, this work provides theoretical guidance for the electrochemical urea oxidation work.

25 ENERGY STORAGE↗
DOE OSTI2019

Tritium Aging of Regenerated LANA.75

Tritium Aging of Regenerated LANA.75 is a multi-year project. Activities include: tritium aging of a LANA.75 sample regenerated in 2018, regenerating a second tritium-aged LANA.75 sample, and verifying the thermal stability of LANA.75 under regeneration conditions. During FY19, the Task Technical Plan (TTP) addendum providing testing guidance for monitoring tritium aging of the regenerated LANA.75 sample was approved. A desorption isotherm at 150 °C was collected on the regenerated LANA.75 sample. A second desorption isotherm at 150 °C is scheduled to be collected along with additional desorption isotherms at 80 and 120 °C. Fabrication, pressure testing, and leak testing of the high temperature test cell for regeneration of the second tritium-aged LANA.75 sample was completed. Selection of the second LANA.75 sample to be regenerated is anticipated in FY20. Thermal stability testing of LANA.75 material was completed. Hydrogen desorption isotherms at 80, 100 and 120 °C were collected prior to and after a lengthy annealing process (200 hours combined over two weeks) at 750 °C. The isotherms showed similar performances for all temperatures. However, the plateau region for the isotherms after the annealing process were flatter, suggesting that the annealing process was beneficial to the hydride. Sample analyses, including XRD, SEM, ICP and particle size distribution, are ongoing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Reversible Binding Interfaces Made of Microstructured Polymer Brushes

The polymer brush architecture of the end-tethered polymer molecules is one of the most widely used efficient methods to regulate interfacial interactions in colloidal systems found in live matter and manufactured materials. Emerging applications of polymer brush structures require solutions to new tasks in the control of interfacial interactions. The rapid development of live cell manufacturing relies on scalable and efficient cell harvesting methods. Stimuli-responsive surfaces made of surface-grafted poly(N-isopropylacrylamide) (PNIPAM) can bind and detach the adherent cell upon changes in temperature and have been used for cell growth and harvesting. The applications are limited by the requirement to satisfy a range of PNIPAM coating characteristics that depend on the dimensions of the integrin complex in the cell membrane and the basal surface. The analysis of the microstructured surfaces, when adhesive and disjoining functions of the microdomains are decoupled, shows that many limitations of PNIPAM one-component coatings can be avoided by using a much broader range of structural characteristics of the microstructured interfaces composed of alternating disjoining PNIPAM domains and adhesive polymeric domains with cell-affinity functional groups. Temperature-controlled reversible adhesion to such microstructured interfaces is studied here experimentally with model systems of solid spherical particles and by employing simulations for solid and soft membranes interacting with the microstructured surfaces to mimic interactions with soft and solid disk-like particles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Examination of 3013 Containers Baseline Surface Features

The Surveillance and Monitoring Program at Los Alamos National Laboratory (LANL) was tasked with evaluating the baseline features of 3013 containers. This baseline is to be used as a basis for comparison for 3013 containers that had been packaged with corrosive plutonium materials. The LANL team evaluated an unwelded container, an unused welded container, and a welded container that had held plutonium metal without any corrosive impurities. These three containers had features with depths no larger than 6 µm and had similar depth distributions. The features observed in the baseline containers were all shallower than those seen in containers packaged with corrosive plutonium materials. This work establishes workflows for feature identification and measurement, as well as establishment of baseline data for future comparison with corroded containers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Filament-Free Bulk Resistive Memory Enables Deterministic Analogue Switching

Digital computing is nearing its physical limits as computing needs and energy consumption rapidly increase. Analogue-memory-based neuromorphic computing can be orders of magnitude more energy efficient at data-intensive tasks like deep neural networks, but has been limited by the inaccurate and unpredictable switching of analogue resistive memory. Filamentary resistive random access memory (RRAM) suffers from stochastic switching due to the random kinetic motion of discrete defects in the nanometer-sized filament. Here, this stochasticity is overcome by incorporating a solid electrolyte interlayer, in this case, yttria-stabilized zirconia (YSZ), toward eliminating filaments. Filament-free, bulk-RRAM cells instead store analogue states using the bulk point defect concentration, yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects is deterministic even when individual defects are stochastic. Both experiments and modeling show bulk-RRAM devices using TiO2-X switching layers and YSZ electrolytes yield deterministic and linear analogue switching for efficient inference and training. Bulk-RRAM solves many outstanding issues with memristor unpredictability that have inhibited commercialization, and can, therefore, enable unprecedented new applications for energy-efficient neuromorphic computing. Beyond RRAM, this work shows how harnessing bulk point defects in ionic materials can be used to engineer deterministic nanoelectronic materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Additive Manufacturing of Fuel Injectors

Additive manufacturing (AM), also known as 3D-printing, has been shifting from a novelty prototyping paradigm to a legitimate manufacturing tool capable of creating components for highly complex engineered products. An emerging AM technology for producing metal parts is the laser powder bed fusion (L-PBF) process; however, industry manufacturing specifications and component design practices for L-PBF have not yet been established. Solar Turbines Incorporated (Solar), an industrial gas turbine manufacturer, has been evaluating AM technology for development and production applications with the desire to enable accelerated product development cycle times, overall turbine efficiency improvements, and supply chain flexibility relative to conventional manufacturing processes (casting, brazing, welding). Accordingly, Solar teamed with EWI on a joint two-and-a-half-year project with the goal of developing a production L-PBF AM process capable of consistently producing high-nickel alloy material suitable for high temperature gas turbine engine fuel injector components. The project plan tasks were designed to understand the interaction of the process variables and their combined impact on the resultant AM material quality. The composition of the high-nickel alloy powders selected for this program met the conventional cast Hastelloy X compositional limits and were commercially available in different particle size distributions (PSD) from two suppliers. Solar produced all the test articles and both EWI and Solar shared responsibility for analyzing them. The effects of powder metal input stock, laser parameters, heat treatments, and post-finishing methods were evaluated. This process knowledge was then used to generate tensile, fatigue, and creep material properties data curves suitable for component design activities. The key process controls for ensuring consistent material properties were documented in AM powder and process specifications. The basic components of the project were: • Powder metal input stock: Powder characterization, dimensional accuracy, metallurgical characterization, and mechanical properties evaluation. • Process parameters: Laser parameter effects, post-printing heat-treatment development, mechanical properties evaluation, and post-finishing technique. • Material design curves: Room and elevated temperature tensiles, low cycle fatigue, and creep rupture properties curves generated. • AM specifications: Key metal powder characteristics, laser parameters, and heat-treatment controls identified.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Signatures of distinct impurity configurations in atomic-resolution valence electron-energy-loss spectroscopy: Application to graphene

The detection and identification of impurities and other point defects in materials is a challenging task. Signatures for point defects are typically obtained using spectroscopies without spatial resolution. Here in this paper, we demonstrate the power of valence electron-energy-loss spectroscopy (VEELS) in an aberration-corrected scanning transmission-electron microscope (STEM) to provide energy-resolved and atomically resolved maps of electronic excitations of individual impurities which, combined with theoretical simulations, yield unique signatures of distinct bonding configurations of impurities. We report VEELS maps for isolated Si impurities in graphene, which are known to exist in two distinct configurations. We also report simulations of the maps, based on density functional theory and dynamical scattering theory, which agree with and provide direct interpretation of observed features. We show that theoretical VEELS maps exhibit distinct and unambiguous signatures for the threefold- and fourfold-coordinated configurations of Si impurities in different energy-loss windows, corresponding to impurity-induced bound states, resonances, and antiresonances. With the advent of new monochromators and detectors with high energy resolution and low signal-to-noise ratio, the present work ushers an atomically resolved STEM-based spectroscopy of individual impurities as an alternative to conventional spectroscopies for probing impurities and defects.

36 MATERIALS SCIENCE↗