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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization of the Soluble and Insoluble Portions of Solids from the Salt Waste Processing Facility Tank 201 and Tank 202 Samples

The Salt Waste Processing Facility (SWPF) Tank 201 and Tank 202 samples have been characterized using X-ray diffraction (XRD), scanning electron microscope/energy dispersive x-ray (SEM/EDX), particle size analysis (PSA-Microtrac), Fourier transform-infrared (FT-IR) and nuclear magnetic resonance ( 1 H NMR) spectroscopic techniques to characterize and identify organic and inorganic components in Tanks 201 and 202 as part of efforts to understand the problems occurring at SWPF due to the presence of solids in the recovered solvent.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Characterization of the Soluble and Insoluble Portions of Solids from the Salt Waste Processing Facility Tank 201 and Tank 202 Samples

The Salt Waste Processing Facility (SWPF) Tank 201 and Tank 202 samples have been characterized using X-ray diffraction (XRD), scanning electron microscope/energy dispersive x-ray (SEM/EDX), particle size analysis (PSA-Microtrac), Fourier transform-infrared (FT-IR) and nuclear magnetic resonance ( 1 H NMR) spectroscopic techniques to characterize and identify organic and inorganic components in Tanks 201 and 202 as part of efforts to understand the problems occurring at SWPF due to the presence of solids in the recovered solvent.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗
NASA NTRS2019

Cleanroom Contamination Identification Method Development

During fabrication, assembly, and testing of spacecraft and flight hardware it is vital to avoid contaminants that can cause degradation and could result in significant failure. Yet, there is no existing contamination monitoring method that provides the identity of airborne particles in a cleanroom facility. Knowing the particle identities, would allow scientists and engineers to determine the source of the contaminants and prevent setbacks before they occur or cause damage. Current cleanliness monitoring methods include airborne particle counters (APCs), fallout filters, and visual inspections. Particle counts from APCs are the primary metric used to define a cleanroom class and hence its level of cleanliness, but do not provide identification nor can they differentiate between large and small sizes of particles. In addition, using fallout filters is not a proactive, timely, or representative approach to cleanroom contamination monitoring because these samples are only retrieved after 30 days and are placed away from spacecraft processing to avoid interference with operations. In contrast, the forced air sampling method can collect a sample within an hour at any location required and provide results in less than a day. This system uses a cassette and filter sample medium to capture airborne particles which are then taken to a scanning electron microscope with energy dispersive spectroscopy (SEM/EDS) to identify and size the captured particles. Development of forced air sampling into an established laboratory capability will allow for fast sampling and routine identification of unknown contamination sources within the cleanroom. The test method development required market research for an air sampling cassette that increases sample collection efficiency and a filter with low enough background contamination to allow differentiation between a blank (control) and the collected sample. It was determined that a conductive black cassette and a polycarbonate filter were the best options. Conductive black cassettes, in comparison to the standard styrene, are manufactured using polypropylene filled with carbon. This makes the cassette conductive and minimizes the tendency of particles to stick to the wall of the cassette due to electrostatic force. In previous trials a mixed cellulose ester (MCE) filter was used to capture the contaminants, however the rougher surface of the filter contributed to entrapment of the particles within the filter structure and made it harder to identify the particles. In comparison, track etched polycarbonate filters have random cylindrical pores and a smooth surface which contributes to uniform sample distribution on the surface of the filter. Future work includes: testing the system using control samples to determine the efficiency and suitability of the medium, performing sample collection in various environments to establish ideal operating parameters and analyzing contaminant particles using SEM/EDS and assistant characterization techniques. Once fully developed, employing the forced air sampling method will help to prevent damage to spacecraft, avoid schedule delays, and allow for mission success.

Hernandez Melendez, Jailyn M.↗
DOE OSTI2022

Onion-Like nanoparticles of the metal–organic framework UiO-66 synthesized by sequential spike crystal growth

Reproducible size and morphology of metal–organic framework (MOF) particles are essential for tuning these materials for applications like heterogeneous catalysis. Particle size measurements from electron micrographs provide information about the impact of changing synthetic parameters on MOF growth, but reported data are usually limited to averages and statistical distributions. Further elucidating synthetic control parameters could facilitate studies of facet-dependent and non-classical growth mechanisms. Here, in this work, phase-pure nanoparticles of the MOF UiO-66 were synthesized using alternating spikes of zirconium and hafnium-based nodes, forming an onion-like structure with alternating layers of Zr-UiO-66 and Hf-UiO-66. In conventional, bright-field transmission electron micrographs, Hf-UiO-66 and Zr-UiO-66 layers appeared darker and lighter, respectively. Alternating layers of Hf-UiO-66 and Zr-UiO-66 were also apparent in elemental maps obtained using scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy. Average particle sizes increased monotonically with each spike, and no Zr-only or Hf-only particles were observed after the first spike, indicating that new material was consistently incorporated onto existing seeds. Surface area of the onion-like particles and their uptake of Ni 2+ from solution were both between the values measured for Zr-UiO-66 and Hf-UiO-66. Results demonstrate the use of sequential spikes of nodes in monitoring crystal growth in MOFs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Resin chemistry and particle size influence on stereolithography with silicon carbide

Stereolithography (SLA) is an established process able to produce high resolution polymer parts with complex geometries. Silicon carbide (SiC) has uses in a variety of applications, but traditionally was difficult to manufacture into complex geometries. There have been advances in producing SiC through SLA using a SiC-derived ceramic such as silicon oxycarbide (SiOC). In this study, a slurry using a commercially available resin as the base material with additional modifiers was investigated to create a SiC slurry ready for pressureless sintering. The effects of photoinitiator, dispersant and a bimodal distribution of SiC particle sizes was studied using a design of experiments (DOE). A slurry with a bimodal distribution of 70 % coarse and 30 % fine SiC powder at 40 % solids loading by volume was prepared and successfully printed. Rheology measurements show the slurry to have viscoelastic shear thinning behavior below the recommended 1000 Pas necessary for printing. Printing parameters for the new material on a commercially available SLA printer were studied parametrically. The laser marking speeds found to print the slurry was 260 mm/s and 130 mm/s. A slurry and printing parameters were determined to produce a green part with a proposed debinding cycle.

Herd, Tien [ORNL]↗
DOE OSTI2021

A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme

In the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category), and with a two-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice—in particular, hail—due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a three-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution. The details of the three-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the three-moment ice configuration controls size sorting in a physically based way and leads to an improved capacity to simulate large, heavily rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solid-state polymer-particle hybrid electrolytes: Structure and electrochemical properties

Solid-state electrolytes (SSEs) are challenged by complex interfacial chemistry and poor ion transport through the interfaces they form with battery electrodes. Here, we investigate a class of SSE composed of micrometer-sized lithium oxide (Li 2 O) particles dispersed in a polymerizable 1,3-dioxolane (DOL) liquid. Ring-opening polymerization (ROP) of the DOL by Lewis acid salts inside a battery cell produces polymer-inorganic hybrid electrolytes with gradient properties on both the particle and battery cell length scales. These electrolytes sustain stable charge-discharge behavior in Li||NCM811 and anode-free Cu||NCM811 electrochemical cells. On the particle length scale, Li 2 O retards ROP, facilitating efficient ion transport in a fluid-like region near the particle surface. On battery cell length scales, gravity-assisted settling creates physical and electrochemical gradients in the hybrid electrolytes. By means of electrochemical and spectroscopic analyses, we find that Li 2 O particles participate in a reversible redox reaction that increases the effective CE in anode-free cells to values approaching 100%, enhancing battery cycle life.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Matrix effects for reflectivity spectra of dispersed nanophase (superparamagnetic) hematite with application to Martian spectral data

The effect of the matrix on the reflectivity spectra of nanophase (superparamagnetic) hematite (np-Hm) dispersed within the matrix was investigated in four series of powder samples containing np-Hm dispersed within discrete powder particles (of two size ranges) of silica gel and activated alumina. The spectral data show that matrix effects are large. Samples with the same Fe2O3 content can have np-Hm absorption edges characterized by very different positions and curvature and slope indices, while samples with equivalent absorption edges can have very different Fe2O3 concentrations. Thus, quantitative relationships between the positions of ferric absorption edges and Fe2O3 concentrations are unreliable without knowledge of matrix properties of the system. It is shown that it was possible to match the Fe2O3 concentration, magnetic properties, and spectral data for Martian surface material with a laboratory mixture whose only ferric-bearing phase was hematite.

Morris, Richard V.↗
NASA NTRS2003

Palagonitic (Not Andesitic) Mars: Evidence from Thermal Emission and VNIR Spectra of Palgonitic Alteration Rinds on Basaltic Rock

Visible and near-IR (VNIR) spectra of both Martian bright and dark regions are characterized by a ferric absorption edge extending from approx. 400 to 750 nm, with bright regions having about twice the reflectivity at 750 nm as dark regions. Between 750 nm to beyond 2000 nm, bright and dark regions have nearly constant and slightly negative spectral slopes, respectively. Depending on location, bright regions have shallow reflectivity minima in the range 850-910 nm that are attributed to ferric oxides. Similarly, dark regions have shallow reflectivity minima near approx. 950 and 1700-2000 nm that are attributed to ferrous silicate minerals (pyroxene). Among terrestrial geologic materials, the best spectral analogues for Martian bright regions are certain palagonitic tephras from Mauna Kea Volcano (Hawaii). By definition, palagonite is a "yellow or orange isotropic mineraloid formed by hydration and devitrification of basaltic glass". The ferric pigment in palagonite is nanometer-sized ferric oxide particles (np-Ox) dispersed throughout the hydrated basaltic glass matrix. The hydration state of the np-Ox particles is not known, but the best Martian spectral analogues contain allophane-like materials and not crystalline phyllosilicates.

R V Morris↗
NASA NTRS2003

Palagonitic Mars from Rock Rinds to Dust: Evidence from Visible, Near-IR, and Thermal Emission Spectra of Poorly Crystalline Materials

Visible and near-IR (VNIR) spectral data for Martian bright regions are characterized by a general shape consisting of a ferric absorption edge extending from about 400 to 750 nm and relatively constant reflectivity extending from about 750 nm to beyond 2000 nm . Among terrestrial geologic materials, the best spectral analogues are certain palagonic tephras from Mauna Kea Volcano (Hawaii). By definition, palagonite is a yellow or orange isotropic mineraloid formed by hydration and devitrification of basaltic glass. The ferric pigment in palagonite is nanometer-sized ferric oxide particles (np-Ox) dispersed throughout the hydrated basaltic glass matrix. The hydration state of the np-Ox particles is not known, and the best Martian spectral analogues contain allophane-like materials and not crystalline phyllosilicates. We show here that laboratory VNIR and TES spectra of palagonitic alteration rinds developed on basaltic rocks are spectral endmembers that provide a consistent explanation for both VNIR and TES data of Martian dark regions.

Morris, R. V.↗
NASA NTRS2004

Palagonitic Mars: A Basalt Centric View of Surface Composition and Aqueous Alteration

Palagonitic tephra from certain areas on Mauna Kea Volcano (Hawaii) are well-established spectral and magnetic analogues of high-albedo regions on Mars. By definition, palagonite is "a yellow or orange isotropic mineraloid formed by hydration and devitrification of basaltic glass." The yellow to orange pigment is nanometer-sized ferric oxide particles (np-Ox) dispersed throughout the hydrated basaltic glass matrix. The hydration state of the np-Ox particles and the matrix is not known, but the best Martian spectral analogues contain allophane-like materials and not crystalline phyllosilicates. Martian low-albedo regions are also characterized by a palagonite-like ferric absorption edge, but, unlike the highalbedo regions, they also show evidence for absorption by ferrous iron. Thermal emission spectra (TES) obtained by the Mars Global Surveyor Thermal Emission Spectrometer suggest that basaltic (surface Type 1) and andesitic (surface Type 2) volcanic compositions preferentially occur in southern (Syrtis Major) and northern (Acidalia) hemispheres, respectively. The absence of a ferric-bearing component in the modeling of TES spectra is in apparent conflict with VNIR spectra of Martian dark regions, as discussed above. However, the andesitic spectra have also been interpreted as oxidized basalt using phyllosilicates instead of high-SiO2 glass as endmembers in the spectral deconvolution of surface Type 2 TES spectra. We show here that laboratory VNIR and TES spectra of rinds on basaltic rocks are spectral endmembers that provide a consistent explanation for both VNIR and TES data of Martian dark regions.

Morris, R. V.↗
NASA NTRS1997

Crystalline Colloidal Arrays in Polymer Matrices

Crystalline Colloidal Arrays (CCA, also known as colloidal crystals), composed of aqueous or nonaqueous dispersions of self-assembled nanosized polymer colloidal spheres, are emerging toward the development of advanced optical devices for technological applications. The spontaneous self assembly of polymer spheres in a dielectric medium results from the electrostatic repulsive interaction between particles of uniform size and charge distribution. In a way similar to atomic crystals that diffract X-rays, CCA dispersions in thin quartz cells selectively and efficiently Bragg diffract the incident visible light. The reason for this diffraction is because the lattice (body or face centered cubic) spacing is on the order of the wavelength of visible light. Unlike the atomic crystals that diffract a fixed wavelength, colloidal crystals in principle, depending on the particle size, particle number and charge density, can diffract W, Vis or IR light. Therefore, the CCA dispersions can be used as laser filters. Besides, the diffraction intensity depends on the refractive index mismatch between polymer spheres and dielectric medium; therefore, it is possible to modulate incident light intensities by manipulating the index of either the spheres or the medium. Our interest in CCA is in the fabrication of all-optical devices such as optical switches, limiters, and spatial light modulators for optical signal processing. The two major requirements from a materials standpoint are the incorporation of suitable nonlinear optical materials (NLO) into polymer spheres which will allow us to alter the refractive index of the spheres by intense laser radiation, and preparation of solid CCA filters which can resist laser damage. The fabrication of solid composite filters not only has the advantage that the films are easier to handle, but also the arrays in solid films are more robust than in liquid media. In this paper, we report the photopolymerization process used to trap CCA in polymer matrices, the factors which affect the optical diffraction qualities of resulting polymer films, and methods to improve the efficiencies of solid optical filters. Before this, we also present the experimental demonstration, of controlling the optical diffraction intensities from aqueous CCA dispersions by varying the temperature, which establishes the feasibility of fabricating all-optical switching devices with nonlinear periodic array structures.

Sunkara, Hari B.↗
DOE OSTI2024

Predicting Adhesion Energies of Metal Nanoparticles to Support Surfaces, Which Determines Metal Chemical Potential versus Particle Size and Thus Catalyst Performance

Improved catalysts and electrocatalysts composed of transition metal nanoparticles dispersed on high-area supports are essential for energy and environmental technologies. The chemical potential of the metal atoms in these supported nanoparticles is an important descriptor that correlates with both their catalytic activity and deactivation rate. This descriptor (μ M ) is predictably determined by the particle size and the adhesion energy per unit area at the metal/support interface (E adh ). We show here that the adhesion energies for different metals on a given support scale linearly with a simple property of the metal: for oxides, it is proportional to the metal oxophilicity, and for the carbon support, it increases linearly with metal carbophilicity (both divided by the area per metal atom). Furthermore, these relationships allow predicting E adh for other metal/support combinations, thus allowing estimation of μ M versus particle size and thereby better structure-based predictions of catalysts’ performance, which can aid in designing improved catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗