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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Composition of conglomerates analyzed by the Curiosity rover: Implications for Gale Crater crust and sediment sources

The Curiosity rover has analyzed various detrital sedimentary rocks at Gale Crater, among which fluvial and lacustrine rocks are predominant. Conglomerates correspond both to the coarsest sediments analyzed and the least modified by chemical alteration, enabling us to link their chemistry to that of source rocks on the Gale Crater rims. Here, we report the results of six conglomerate targets analyzed by Alpha-Particle X-ray Spectrometer and 40 analyzed by ChemCam. The bulk chemistry derived by both instruments suggests two distinct end-members for the conglomerate compositions. The first group (Darwin type) is typical of conglomerates analyzed before sol 540; it has a felsic alkali-rich composition, with a Na 2 O/K 2 O > 5. The second group (Kimberley type) is typical of conglomerates analyzed between sols 540 and 670 in the vicinity of the Kimberley waypoint; it has an alkali-rich potassic composition with Na 2 O/K 2 O < 2. The variety of chemistry and igneous textures (when identifiable) of individual clasts suggest that each conglomerate type is a mixture of multiple source rocks. Conglomerate compositions are in agreement with most of the felsic alkali-rich float rock compositions analyzed in the hummocky plains. The average composition of conglomerates can be taken as a proxy of the average igneous crust composition at Gale Crater. Finally, the differences between the composition of conglomerates and that of finer-grained detrital sediments analyzed by the rover suggest modifications by diagenetic processes (especially for Mg enrichments in fine-grained rocks), physical sorting, and mixing with finer-grained material of different composition.

58 GEOSCIENCES↗
DOE OSTI2017

A Low Viscosity Lunar Magma Ocean Forms a Stratified Anorthitic Flotation Crust With Mafic Poor and Rich Units

Much of the lunar crust is monomineralic, comprising >98% plagioclase. The prevailing model argues the crust accumulated as plagioclase floated to the surface of a solidifying lunar magma ocean (LMO). Whether >98% pure anorthosites can form in a flotation scenario is debated. An important determinant of the efficiency of plagioclase fractionation is the viscosity of the LMO liquid, which was unconstrained. Here we present results from new experiments conducted on a late LMO-relevant ferrobasaltic melt. The liquid has an exceptionally low viscosity of 0.22 $+0.11\atop{-0.19}$to 1.45 $+0.46\atop{-0.82}$ Pa s at experimental conditions (1,300–1,600°C; 0.1–4.4 GPa) and can be modeled by an Arrhenius relation. Extrapolating to LMO-relevant temperatures, our analysis suggests a low viscosity LMO would form a stratified flotation crust, with the oldest units containing a mafic component and with very pure younger units. Old, impure crust may have been buried by lower crustal diapirs of pure anorthosite in a serial magmatism scenario.

58 GEOSCIENCES↗
DOE OSTI2021

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. Further, the different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.

36 MATERIALS SCIENCE↗
DOE OSTI2017

para ‐Xylene Ultra‐selective Zeolite MFI Membranes Fabricated from Nanosheet Monolayers at the Air–Water Interface

Abstract The control of membrane morphology and microstructure is crucial to improve the separation performance of molecular‐sieve membranes. This can be enabled by making thin, dense, and uniform seed‐crystal coatings, which are then intergrown into continuous membranes. Herein, we show a novel and simple floating particle coating method can give closely packed monolayers of zeolite nanosheets on nonporous or porous supports. The zeolite nanosheet monolayer is formed at the air–water interface in a conical Teflon trough. As the water in the trough is drained, the monolayer is deposited on a support placed below. Membranes prepared by gel‐free secondary growth of the nanosheets deposited by this method show unprecedented ultra‐selective performance for separation of para‐ from ortho‐xylene (separation factor >10 000).

Kim, Donghun↗
DOE OSTI2014

Using Ambient Ion Beams to Write Nanostructured Patterns for Surface Enhanced Raman Spectroscopy

Electrolytic spray deposition was used to pattern surfaces with 2D metallic nanostructures. Spots that contain silver nanoparticles (AgNP) were created by landing solvated silver ions at desired locations using electrically floated masks to focus the metal ions to an area as little as 20 mm in diameter. The AgNPs formed are unprotected and their aggregates can be used for surface-enhanced Raman spectroscopy (SERS). The morphology and SERS activity of the NP structures were controlled by the surface coverage of landed silver ions. The NP structures created could be used as substrates onto which SERS samples were deposited or prepared directly on top of predeposited samples of interest. The evenly distributed hot spots in the micron-sized aggregates had an average SERS enhancement factor of 108. The surfaces showed SERS activity when using lasers of different wavelengths (532, 633, and 785 nm) and were stable in air.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Amphiphilic Nanoparticles Control the Growth and Stability of Lipid Bilayers with Open Edges

Molecular amphiphiles self-assemble in polar media to form ordered structures such as micelles and vesicles essential to a broad range of industrial and biological processes. Some of these architectures such as bilayer sheets, helical ribbons, and hollow tubules are potentially useful but inherently unstable owing to the presence of open edges that expose the hydrophobic bilayer core. Here, we describe a strategy to stabilize open bilayer structures using amphiphilic nanoparticle surfactants that present mixtures of hydrophilic and hydrophobic ligands on their surface. We observe that these particles bind selectively to the open edge of bilayer membranes to stabilize otherwise transient amphiphile assemblies. We show how such particles can precisely control the size of lipid tubules, how they can inhibit the formation of undesirable assemblies such as gallstone precursors, and how they can stabilize free-floating lipid microdiscs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

para -Xylene Ultra-selective Zeolite MFI Membranes Fabricated from Nanosheet Monolayers at the Air-Water Interface

The control of membrane morphology and microstructure is crucial to improve the separation performance of molecular-sieve membranes. This can be enabled by making thin, dense, and uniform seed-crystal coatings, which are then intergrown into continuous membranes. Herein, we show a novel and simple floating particle coating method can give closely packed monolayers of zeolite nanosheets on nonporous or porous supports. The zeolite nanosheet monolayer is formed at the air–water interface in a conical Teflon trough. As the water in the trough is drained, the monolayer is deposited on a support placed below. Membranes prepared by gel-free secondary growth of the nanosheets deposited by this method show unprecedented ultra-selective performance for separation of para- from ortho-xylene (separation factor >10,000).

36 MATERIALS SCIENCE↗
DOE OSTI2016

Alkyl Substitution Effect on Oxidation Stability of Sulfone-Based Electrolytes

Organic sulfone compounds have been widely used as high-voltage electrolytes for lithium-ion batteries for decades. However, owing to the complexity of the synthesis of new sulfones, only a few commercially available sulfones have been studied. In this paper, we report the synthesis of new sulfone compounds with various substituent groups and the impact of the substituent group on the oxidation stability of sulfones. Electrochemical floating tests using a 5 V LiNi0.5Mn1.5O4 spinel cathode and density functional theory calculations showed that the cyclopentyl-substituted sulfone McPS suffered from oxidation instability, starting from 4.9 V versus Li+/Li, as observed by the large leakage currents. On the other hand, the isopropyl-substituted sulfone MiPS and tetramethylene substituted sulfone TMS showed much improved oxidation stability under identical testing conditions. The substitution structure of the sulfone plays a significant role in the determination of its oxidative stability and should first be considered for the development of new sulfone-based electrolytes for high-voltage, high-energy lithium-ion batteries.

alkyl substitution↗
DOE OSTI2019

Parallel membership queries on very large scientific data sets using bitmap indexes

© 2019 John Wiley & Sons, Ltd. Many scientific applications produce very large amounts of data as advances in hardware fuel computing and experimental facilities. Managing and analyzing massive quantities of scientific data is challenging as data are often stored in specific formatted files, such as HDF5 and NetCDF, which do not offer appropriate search capabilities. In this research, we investigated a special class of search capability, called membership query, to identify whether queried elements of a set are members of an attribute. Attributes that naturally have classification values appear frequently in scientific domains such as category and object type as well as in daily life such as zip code and occupation. Because classification attribute values are discrete and require random data access, performing a membership query on a large scientific data set creates challenges. We applied bitmap indexing and parallelization to membership queries to overcome these challenges. Bitmap indexing provides high performance not only for low cardinality attributes but also for high cardinality attributes, such as floating-point variables, electric charge, or momentum in a particle physics data set, due to compression algorithms such as Word-Aligned Hybrid. We conducted experiments, in a highly parallelized environment, on data obtained from a particle accelerator model and a synthetic data set.

Yildiz, Beytullah↗
DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗
DOE OSTI2020

Detailed modeling of the video signal and optimal readout of charge-coupled devices

This paper provides a practical design methodology to calculate an optimal filter for noise reduction in the readout of charge-coupled devices (CCDs) taking into account the charge transfer and feedthroughs due to capacitive coupling in the CCD. A detailed analysis of the dynamics of the video signal and charge transfer is presented, including the circuital modeling of the output stage of the CCD and the dynamics of the electronics in the video chain before the analog-to-digital (AD) converter. This model is used to compute an optimal filter that minimizes the variance of the pixel noise and uses the samples of the charge transfer, before the charge is fully settled. This is necessary to enhance the performance of previous results that also use optimal filters but do not use the transition samples, while also reducing the pixel readout time, resulting in faster readouts. As a proof of concept for the optimal filter, we present in this paper novel experimental results using a Skipper CCD, which has a floating sense node that allows to measure the charge packet an arbitrary number of times. However, this technique can be applied to any CCD that has a readout system that digitally samples the video signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Matrix-free preconditioning for high-order H (curl) discretizations

The greater arithmetic intensity of high-order finite element discretizations makes them attractive for implementation on next-generation hardware, but assembly of high-order finite element operators as matrices is prohibitively expensive. As a result, the development of general algebraic solvers for such operators has been an open research challenge. Fast matrix-free application of high-order operators has received significant attention in the literature in the context of Poisson-type problems, but preconditioners and solvers for inverting more general operators are not very well-developed. In this paper, we consider the problem of preconditioning a definite Maxwell operator at high polynomial order without assembling a matrix. We show that given efficient preconditioners for high-order H 1 finite element problems on the same mesh, efficient H(curl) preconditioners can be constructed in an auxiliary space framework. We demonstrate the resulting preconditioners in a practical setting with tensor-product basis functions on an unstructured mesh of quadrilaterals. Overall, our approach uses a sparsified H 1 solver constructed on a low-order mesh of the nodal points of the underlying high-order space, and we show that the resulting H(curl) preconditioner is effective at very high polynomial orders for two-dimensional model problems with complicated geometry, varying piecewise constant coefficients, and curved elements. The resulting preconditioner scales with nearly optimal O(p d+1 ) floating point operation count and optimal O(p d ) memory transfer requirements, outperforming existing Maxwell preconditioners in the high-order regime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multistage mixed precision iterative refinement

Abstract Low precision arithmetic, in particular half precision (16‐bit) floating point arithmetic, is now available in commercial hardware. Using lower precision can offer significant savings in computation and communication costs with proportional savings in energy. Motivated by this, there has been a renewed interest in mixed precision iterative refinement schemes for solving linear systems , and new variants of GMRES‐based iterative refinement have been developed. Each particular variant with a given combination of precisions leads to different condition number‐based constraints for convergence of the backward and forward errors, and each has different performance costs. The constraints for convergence given in the literature are, as an artifact of the analyses, often overly strict in practice, and thus could lead a user to select a more expensive variant when a less expensive one would have sufficed. In this work, we develop a multistage mixed precision iterative refinement solver which aims to combine existing mixed precision approaches to balance performance and accuracy and improve usability. For a user‐specified initial combination of precisions, the algorithm begins with the least expensive approach and convergence is monitored via inexpensive computations with quantities produced during the iteration. If slow convergence or divergence is detected using particular stopping criteria, the algorithm switches to use a more expensive, but more reliable variant. A novel aspect of our approach is that, unlike existing implementations, our algorithm first attempts to use “stronger” GMRES‐based solvers for the solution update before resorting to increasing the precision(s). In some scenarios, this can avoid the need to refactorize the matrix in higher precision. We perform extensive numerical experiments on a variety of random dense problems and problems from real applications which confirm the benefits of the multistage approach.

Oktay, Eda↗
DOE OSTI2016

Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Summary Reduced order models are useful for accelerating simulations in many‐query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models (ROMs) can have prohibitively expensive memory and floating‐point operation costs in high‐performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time‐stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition‐based ROMs, and memory usage is minimized by computing the singular value decomposition using a single‐pass incremental algorithm. Results for a viscous Burgers' test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full‐order model is recovered to within discretization error. A parallel version of the resulting method can be used on supercomputers to generate proper orthogonal decomposition‐based ROMs, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space. Copyright © 2016 John Wiley & Sons, Ltd.

Oxberry, Geoffrey M.↗
DOE OSTI2016

Plasma Treatment of Onychomycosis

We report on the use of three “cold” atmospheric plasma (CAP) devices in treating model nails that have been coated on the backside of the nail with either Escherichia coli ( E. coli ) bacteria or Trichophyton rubrum ( T. rubrum ) fungus. We tested a helium plasma jet; a surface microdischarge plasma device; and a floating electrode dielectric barrier discharge. All of the devices, acting through the model nail, showed significant log reductions of bacterial and fungal targets in several tens of minutes. CAP technology appears to offer promise as a safe, effective, and inexpensive therapy for fungal nail infection treatment.

Xiong, Zilan↗
DOE OSTI2021

Time-Resolved Grazing Incidence X-Ray Absorption Spectroscopy for the In Situ Investigation of the Initial Stages of Sputter-Deposited Copper Thin Films

The sputter deposition and the growth of thin copper films on float glass substrates are in situ studied using grazing incidence, reflection mode X-ray absorption fine structure spectroscopy with subsecond time resolution. The experimental data are compared with model calculations, assuming the presence of crystalline, face-centered cubic metallic Cu nanostructures. From a detailed analysis of the measured spectra, the film thickness as well as the surface roughness is determined, leading to a detailed understanding of the films growth as a function of the sputter deposition time. In particular, different stages of film growth can clearly be distinguished from the fits of the experimental data. The results suggest the formation of isolated, approximately nm-sized copper clusters in the initial phase of the film deposition for the first few seconds, a coalescence phase with a nominal thickness of ≈1.5–2.8 nm, constant roughness of about 1.4 nm for the subsequent ≈5 s, and finally 3D growth of the Cu crystallites in the film for later stages of film growth. Further prospects of the methodology are given.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Study of the Au-Cr bilayer system using X-ray reflectivity, GDOES, and ToF-SIMS

Here, we study a Au (25 nm)/Cr (10 nm) bilayer system as a model of mirror for the soft X–ray energy range. The Au and Cr thin films are a few nanometer thick and are deposited on a float glass substrate. The sample is characterized by using 3 complementary techniques: soft X–ray reflectivity, glow discharge optical emission spectrometry (GDOES), and time–of–flight secondary ion mass spectroscopy (ToF–SIMS). Soft X–ray reflectivity provides information about the thickness and roughness of the different layers, while GDOES is used to obtain the elemental depth profile of the stack and ToF–SIMS to obtain the elemental and chemical depth profiles. GDOES and ToF–SIMS have both a nanometer depth resolution. A coherent description of the bilayer stack is obtained through the combination of these techniques. It consists in 5 layers namely a surface contamination layer, a principal gold layer, a Au–Cr mixed layer, a Cr layer, and another contamination layer at the top of the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of the Bulk Resistivity on Silicon Heterojunction Solar Cells and Module Reliability

Recent developments in industry on surface passivation open the possibility of using less doped substrates in silicon solar cells. In this report we investigate how the bulk resistivity affects the performance of silicon cells and the reliability of modules. Herein, n- and p-type silicon heterojunction cells with bulk resistivities between 3 and 15 000 Ωcm are studied. We measure the current–voltage characteristics of n-type cells across the resistivity range, and we find comparable responses to illumination intensities between 0.1 and 1 suns. The cells with bulk resistivities over 1000 Ωcm show breakdown voltages larger than -1000 V, almost two orders of magnitude higher than in typical commercial cells. Although modules have bypass-diodes to prevent cells from going into breakdown, higher breakdown voltages can improve the reliability of modules in case of bypass-diode failure and reduce the module cost by easing the number of bypass-diodes required. Finally, the cells have been submitted to light soaking. The float-zone p-type cells with bulk resistivities over 10 000 Ωcm are less sensitive to light-induced degradation than cells with bulk resistivities below 10 Ωcm. The former show to recover few hours after light soaking, while the latter recover only after dark annealing.

14 SOLAR ENERGY↗