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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 OSTI2014

Influence of NaX (X=I or Cl) additions on GeS{sub 2}–Ga{sub 2}S{sub 3} based glasses

Chalcogenide glasses in the pseudo-ternary system NaX–GeS{sub 2}–Ga{sub 2}S{sub 3} (X=Cl or I) were synthesized. Different series were investigated in order to highlight the influence of the sodium halide addition on two different host glasses (GeS{sub 2}){sub 80}(Ga{sub 2}S{sub 3}){sub 20} and (GeS{sub 2}){sub 72}(Ga{sub 2}S{sub 3}){sub 28}. Macroscopic properties including density and characteristic temperatures, such as glass transition temperatures T{sub g} and crystallization temperature T{sub x}, were determined for a maximum molar content of NaX equal to 15%. The evolution of the optical band-gap and the chemical stability following the composition were also studied. Conductivity measurements were also performed and compared to other Li-based GeS{sub 2}–Ga{sub 2}S{sub 3} glasses. The results were discussed taking into account the cation and anion nature and also the glass packing density. - Graphical abstract: Characterizations of NaX–GeS{sub 2}–Ga{sub 2}S{sub 3} chalcogenide glasses (X=Cl or I). - Highlights: • Synthesis and characterization of NaX–GeS{sub 2}–Ga{sub 2}S{sub 3} chalcogenide glasses (X=Cl or I). • We compare results with analoguous LiX-bearing glasses. • Correlation between electrical conductivity and glass packing density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

D 2 O Interaction with Planar ZnO(0001) Bilayer Supported on Au(111): Structures, Energetics and Influence of Hydroxyls

Here, we investigate the interaction between D 2 O and the planar ZnO(0001) bilayer grown on Au(111) with temperature programmed desorption (TPD), low energy electron diffraction (LEED), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. We show that D 2 O molecules adsorbed on this planar surface form two ordered overlayers, a (3 × 3) and a (√3 × √3) R 30°, not seen before on any of the bulk ZnO single crystal surfaces. The apparent activation energies of desorption (Ed) estimated from TPD peaks are 15.2 and 16.7–17.3 kcal/mol for (3 × 3) and (√3 × √3) R 30°, respectively, which agree well with the adsorption energy values calculated from DFT (14.9–15.6 kcal/mol and 16.8–16.9 kcal/mol, respectively). The DFT calculations reveal that the formation of the overlayers takes place at different packing densities and is mediated by extensive hydrogen bonding among the molecules. The hydroxyl groups, which accumulate very slowly on the ZnO(0001) bilayer surface under the standard ultrahigh vacuum (UHV) environment, strongly suppress the formation of the (√3 × √3) R 30° overlayer but have less impact on the (3 × 3) overlayer. These findings are explained based on the difference in packing densities of the overlayers such that only the (3 × 3) overlayer with a more open structure can accommodate small amounts of the adsorbed hydroxyl groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Parallel Optical Random Access Memory (PORAM)

It is shown that the need to minimize component count, power and size, and to maximize packing density require a parallel optical random access memory to be designed in a two-level hierarchy: a modular level and an interconnect level. Three module designs are proposed, in the order of research and development requirements. The first uses state-of-the-art components, including individually addressed laser diode arrays, acousto-optic (AO) deflectors and magneto-optic (MO) storage medium, aimed at moderate size, moderate power, and high packing density. The next design level uses an electron-trapping (ET) medium to reduce optical power requirements. The third design uses a beam-steering grating surface emitter (GSE) array to reduce size further and minimize the number of components.

Alphonse, G. A.↗
DOE OSTI2019

An Industrial Membrane System Suitable for Distributed Used Oil Re-refining

Under this SBIR project, Media and Process Technology Inc (MPT) has achieved ~60% cost reduction and system foot print of its ceramic membrane product, which leads to successful commercialization of its industrial ceramic membrane process to large scale applications. Ceramic membrane is known for its rugged materials and performance reliability; however, it has been limited in niche applications due to its cost and footprint. The low-cost ceramic membrane thus developed under this project has been field tested successfully in our semi-works production facility for used oil re-refining. Our membrane subsystem of our re-refining production capacity was tripled through the installation of this low-cost high packing density of ceramic membranes. In addition, we have successfully field tested/demonstrated with a pilot unit in two large scale applications for refinery FCC slurry upgrading and decoker/amine scrubber wastewater treatment. Commercialization of these two applications in oil refineries are currently actively pursued by our commercialization partner. With regard to the membrane product sales, we have produced >500 m 2 ceramic membranes for two full-scale installations for industrial oil/water separations in 2017, which is equivalent to ~50% of the annual US ceramic membrane market size. We will continue to push our low-cost high packing density ceramic membrane developed from this project for large scale applications, which are not currently occupied by existing ceramic membranes.

02 PETROLEUM↗
DOE OSTI2016

Modeling of reduced effective secondary electron emission yield from a velvet surface

Complex structures on a material surface can significantly reduce total secondary electron emission from that surface. A velvet is a surface that consists of an array of vertically standing whiskers. The reduction occurs due to the capture of low-energy, true secondary electrons emitted at the bottom of the structure and on the sides of the velvet whiskers. We performed numerical simulations and developed an approximate analytical model that calculates the net secondary electron emission yield from a velvet surface as a function of the velvet whisker length and packing density, and the angle of incidence of primary electrons. We found that to suppress secondary electrons, the following condition on dimensionless parameters must be met: (π/2) DΑ tan θ >> 1, where theta is the angle of incidence of the primary electron from the normal, D is the fraction of surface area taken up by the velvet whisker bases, and A is the aspect ratio, A = h/r, the ratio of height to radius of the velvet whiskers. We find that velvets available today can reduce the secondary electron yield by 90% from the value of a flat surface. As a result, the values of optimal velvet whisker packing density that maximally suppresses the secondary electron emission yield are determined as a function of velvet aspect ratio and the electron angle of incidence.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New insights into the mechanism governing the elasticity of calcium silicate hydrate gels exposed to high temperature: A molecular dynamics study

When exposed to fire, the integrity of cement-based materials is governed by thermally-induced changes in the mechanical properties of their binding phase, i.e., the calcium–silicate–hydrate (C–S–H) gel. However, the effect of temperature on the structure, density, and mechanical properties of C–S–H remains only partially known. Here, based on reactive molecular dynamics simulations, we reveal the nature of thermally-induced damage in C–S–H gels. In general, we show that, at the atomic scale, exposure to high temperature results in partial dehydration, volumetric shrinkage, disordering, and stiffening in the C–S–H grains. However, we show that the thermal response of C–S–H strongly depends on its chemical composition, wherein C–S–H systems associated with lower Ca/Si molar ratios are able to undergo higher temperatures before amorphization. Based on these results, we demonstrate that the stiffness of C–S–H gels (i.e., including porosity—as probed by nanoindentation) is governed by a competition between the stiffening of the grains and the decrease in packing density—wherein the latter eventually become predominant.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Porous media properties of reticulated shape memory polymer foams and mock embolic coils for aneurysm treatment

Background: Shape memory polymer (SMP) foams are being investigated as an alternative aneurysm treatment method to embolic coils. The goal of both techniques is the reduction of blood flow into the aneurysm and the subsequent formation of a stable thrombus, which prevents future aneurysm rupture. The purpose of this study is to experimentally determine the parameters, permeability and form factor, which are related to the flow resistance imposed by both media when subjected to a pressure gradient. Methods: The porous media properties—permeability and form factor—of SMP foams and mock embolic coils (MECs) were measured with a pressure gradient method by means of an in vitro closed flow loop. We implemented the Forchheimer-Hazen-Dupuit-Darcy equation to calculate these properties. Mechanically-reticulated SMP foams were fabricated with average cell sizes of 0.7E-3 and 1.1E-3 m, while the MECs were arranged with volumetric packing densities of 11-28%. Results: The permeability of the SMP foams was an order of magnitude lower than that of the MECs. The form factor differed by up to two orders of magnitude and was higher for the SMP foams in all cases. The maximum flow rate of all samples tested was within the inertial laminar flow regime, with Reynolds numbers ranging between 1 and 35. Conclusions: The SMP foams impose a greater resistance to fluid flow compared to MECs, which is a result of increased viscous and inertial losses. These results suggest that aneurysms treated with SMP foam will have flow conditions more favorable for blood stasis than those treated with embolic coils having packing densities ≤ 28%.

36 MATERIALS SCIENCE↗
DOE OSTI2022

HyMARC Seedling: Optimized Hydrogen Adsorbents via Machine Learning and Crystal Engineering

This final report is presented in two parts: In Part 1, the H 2 capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced from 19 databases is predicted via machine learning (ML). Using only 7 structural features as input, ML identifies 8,282 MOFs with the potential to exceed the capacities of state-of-the-art materials. The identified MOFs are predominantly hypothetical compounds having low densities (<0.31 g/cm3) in combination with high surface areas (>5,300 m2/g), void fractions ($0.90), and pore volumes (>3.3 cm3/g). The relative importance of the input features are characterized, and dependencies on the ML algorithm and training set size are quantified. The most important features for predicting H 2 uptake are pore volume (for gravimetric capacity) and void fraction (for volumetric capacity). The ML models are available on the web, allowing for rapid and accurate predictions of the hydrogen capacities of MOFs from limited structural data; the simplest models require only a single crystallographic feature. In part 2, ways to improve the poor powder packing density of MOFs is discussed. More specifically, a strategy that improves packing efficiency and volumetric hydrogen gas storage density dramatically through engineered morphologies and controlled-crystal size distributions is presented that holds promise for maximizing storage capacity for a given MOF. The packing density improvement, demonstrated for the benchmark sorbent MOF-5, leads to a significant enhancement of volumetric hydrogen storage performance relative to commercial MOF-5. System model projections demonstrate that engineering of crystal morphology/size or use of a bimodal distribution of cubic crystal sizes in tandem with system optimization can surpass the 25 g/L volumetric capacity of a typical 700 bar compressed storage system and exceed the DOE targets 2020 volumetric capacity (30 g/L). Finally, a critical link between improved powder packing density and reduced damage upon compaction is revealed leading to sorbents with both high surface area and high density.

08 HYDROGEN↗
DOE OSTI2024

Impact of reactor architecture and design parameters on the performance of microbial electrolysis cells revealed by the electrode potential slope analysis

Microbial electrolysis cells (MECs) are appealing for recovering the chemical energy contained in domestic and industrial liquid wastes as hydrogen gas. Despite several years of research in the field, there is still a lack of critical analysis of how the reactor architecture dictates the electrochemical performance of the cell. In this study, internal resistance and onset voltage from the electrode potential slope analysis (EPS) were used in combination with current density, hydrogen production rate, reactor packing density, electrode spacing, membrane type and composition from 23 different studies to identify the reactor design parameters that primarily govern electrochemical performance of MECs. Using anion exchange membranes resulted in smaller internal resistances (AEM R int = 41± 40 mΩ m 2 ) and larger current density (18 ± 14 A m −2 ) compared to single chamber reactors (SC R int = 68 ± 58 mΩ m 2 ; 22 ± 16 A m −2 ) or MECs with cation exchange membranes (CEM R int = 376 ± 280 mΩ m 2 ; 3.0 ± 2.1 A m −2 ). Higher electrochemical performance for AEM- and SC-MECs translated in larger hydrogen gas production rates (0.122 mL H 2 C −1 for AEM vs 0.117 mL H 2 C −1 for SC), but only when inhibitors against hydrogen scavengers were added in single chamber systems (0.080 mL H 2 C −1 for SC without inhibitors). Following membrane type and composition, maintaining a small electrode spacing was the most critical parameter to improve MEC performance, indicating that the low conductivity of the media primarily limit performance by increasing ohmic resistance. Here, reactor volume and electrode surface area negatively correlated with internal resistance and current density, indicating that better performance of scaled-up reactors can likely be obtained by stacking multiple smaller units rather than just increasing reactor size. Although challenges remain in the implementation of MECs for hydrogen production from liquid wastes, advances in electrochemical engineering of the reactors can facilitate scale up and performance prediction at scale.

Electrochemistry↗
NASA NTRS1987

Space station architectural elements model study. Space station human factors research review

Presentation visuals and an extended abstract represent a study to explore and analyze the interaction of major utilities distribution, generic workstation, and spatial composition of the SPACEHAB space station module. Issues addressed include packing densities vs. circulation, efficiency of packing vs. standardization, flexibility vs. diversity, and composition of interior volume as space for living vs. residual negative volume. The result of the study is expected to be a series of observations and preliminary evaluation criteria which focus on the productive living environment for a module in orbit.

Taylor, Thomas C.↗
NASA NTRS2000

BOREAS HYD-3 Snow Measurements

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-3 team collected several data sets related to the hydrology of forested areas. This data set contains measurements of snow depth, snow density in three cm intervals, an integrated snow pack density and snow water equivalent (SWE), and snow pack physical properties from snow pit evaluation taken in 1994 and 1996. The data were collected from several sites in both the southern study area (SSA) and the northern study area (NSA). A variety of standard tools were used to measure the snow pack properties, including a meter stick (snow depth), a 100 cc snow density cutter, a dial stem thermometer, and the Canadian snow sampler as used by HYD-4 to obtain a snow pack-integrated measure of SWE. This study was undertaken to predict spatial distributions of snow properties important to the hydrology, remote sensing signatures, and the transmissivity of gases through the snow. The data are available in tabular ASCII files. The snow measurement data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Hardy, Janet P.↗
DOE OSTI2024

Synthetic β-sheets mimicking fibrillar and oligomeric structures for evaluation of spectral X-ray scattering technique for biomarker quantification

Archetypical cross-β spines sharpen the boundary between functional and pathological proteins including β-amyloid, tau, α-synuclein and transthyretin are linked to many debilitating human neurodegenerative and non-neurodegenerative amyloidoses. An increased focus on development of pathogenic β-sheet specific fluid and imaging structural biomarkers and conformation-specific monoclonal antibodies in targeted therapies has been recently observed. Identification and quantification of pathogenic oligomers remain challenging for existing neuroimaging modalities. We propose two artificial β-sheets which can mimic the nanoscopic structural characteristics of pathogenic oligomers and fibrils for evaluating the performance of a label free, X-ray based biomarker detection and quantification technique. Highly similar structure with elliptical cross-section and parallel cross-β motif is observed among recombinant α-synuclein fibril, Aβ-42 fibril and artificial β-sheet fibrils. We then use these β-sheet models to assess the performance of spectral small angle X-ray scattering (sSAXS) technique for detecting β-sheet structures. sSAXS showed quantitatively accurate detection of antiparallel, cross-β artificial oligomers from a tissue mimicking environment and significant distinction between different oligomer packing densities such as diffuse and dense packings. The proposed synthetic β-sheet models mimicked the nanoscopic structural characteristics of β-sheets of fibrillar and oligomeric states of Aβ and α-synuclein based on the ATR-FTIR and SAXS data. The tunability of β-sheet proportions and shapes of structural motifs, and the low-cost of these β-sheet models can become useful test materials for evaluating β-sheet or amyloid specific biomarkers in a wide range of neurological diseases. By using the proposed synthetic β-sheet models, our study indicates that the sSAXS has potential to evaluate different stages of β-sheet-enriched structures including oligomers of pathogenic proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Summary Statistics for LC_TA03_130719: Micro-CT Data Acquired at LLNL, Specimen 3 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, lithium carbonate (LC). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, LC_TA03_130719, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images 2 . The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗
DOE OSTI2013

Summary Statistics for TA_MP03_130620: Micro-CT Data Acquired at LLNL, Specimen 3 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MP03_130620, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images 2 . The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗
DOE OSTI2013

Summary Statistics for TA_MH03_130828: Micro-CT Data Acquired at LLNL, Specimen 3 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MH03_130828, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images. The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗
DOE OSTI2013

Summary Statistics for TA_MH01_130826: Micro-CT Data Acquired at LLNL, Specimen 1 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MH01_130826, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images. The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗
DOE OSTI2013

Summary Statistics for TA_MH02_130827: Micro-CT Data Acquired at LLNL, Specimen 2 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MH03_130827, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images. The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗
DOE OSTI2013

Summary Statistics for TA_MC03_130806: Micro-CT Data Acquired at LLNL, Specimen 3 of 3

Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MC03_130806, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images. The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.

42 ENGINEERING↗