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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 NTRS1995

Gas chromatography/ion mobility spectrometry as a hyphenated technique for improved explosives detection and analysis

Ion Mobility Spectrometry (IMS) is currently being successfully applied to the problem of on-line trace detection of plastic and other explosives in airports and other facilities. The methods of sample retrieval primarily consist of batch sampling for particulate residue on a filter card for introduction into the IMS. The sample is desorbed into the IMS using air as the carrier and negative ions of the explosives are detected, some as an adduct with a reagent ion such as Cl(-). Based on studies and tests conducted by different airport authorities, this method seems to work well for low vapor pressure explosives such as RDX and PETN, as well as TNT that are highly adsorptive and can be found in nanogram quantities on contaminated surfaces. Recently, the changing terrorist threat and the adoption of new marking agents for plastic explosives has meant that the sample introduction and analysis capabilities of the IMS must be enhanced in order to keep up with other detector developments. The IMS has sufficient analytical resolution for a few threat compounds but the IMS Plasmogram becomes increasingly more difficult to interpret when the sample mixture gets more complex.

Mercado, AL↗
NASA NTRS2003

The Dependence of Target Properties Upon Fresh Crater Morphologies on Mars

Viking and Mars Orbiter Camera (MOC) images for approx. 900 "fresh" complex craters were chosen for inspection from a database of 1599 complex craters for which physical attributes have been obtained using the Mars Orbiter Laser Altimeter (MOLA). Preliminary analysis revealed that many of the complex craters have been significantly modified by various processes of denudation, as well as partial or complete infilling with sediments +/- impact melt +/- lava, considerably shallowing many of the craters. This study confirms that the majority of the 894 sampled complex craters are affected by such processes. In 474 cases (52%), no central peaks were observed owing to erosion or burial. Of the remaining craters with visible central peaks, 159 of the freshest craters were selected for further study. These were chosen based on: the absence of significant infilling materials; the presence of a sharp rim and, typically; the preservation of the finer scale morphologic features of the associated ejecta blanket. These craters were used in order to assess the association between the target type and various central peak morphologies, ejecta types and crater depth/diameter relations.

Whitehead, J.↗
NASA NTRS2018

A Blueprint for Demonstrating Quantum Supremacy with Superconducting Qubits

Long coherence times and high fidelity control recently achieved in scalable superconducting circuits paved the way for the growing number of experimental studies of many-qubit quantum coherent phenomena in these devices. Albeit full implementation of quantum error correction and fault tolerant quantum computation remains a challenge the near term pre-error correction devices could allow new fundamental experiments despite inevitable accumulation of errors. One such open question foundational for quantum computing is achieving the so called quantum supremacy, an experimental demonstration of a computational task that takes polynomial time on the quantum computer whereas the best classical algorithm would require exponential time and/or resources. It is possible to formulate such a task for a quantum computer consisting of less than a 100 qubits. The computational task we consider is to provide approximate samples from a non-trivial quantum distribution. This is a generalization for the case of superconducting circuits of ideas behind boson sampling protocol for quantum optics introduced by Arkhipov and Aaronson. In this presentation we discuss a proof-of-principle demonstration of such a sampling task on a 9-qubit chain of superconducting gmon qubits developed by Google. We discuss theoretical analysis of the driven evolution of the device resulting in output approximating samples from a uniform distribution in the Hilbert space, a quantum chaotic state. We analyze quantum chaotic characteristics of the output of the circuit and the time required to generate a sufficiently complex quantum distribution. We demonstrate that the classical simulation of the sampling output requires exponential resources by connecting the task of calculating the output amplitudes to the sign problem of the Quantum Monte Carlo method. We also discuss the detailed theoretical modeling required to achieve high fidelity control and calibration of the multi-qubit unitary evolution in the device. We use a novel cross-entropy statistical metric as a figure of merit to verify the output and calibrate the device controls. Finally, we demonstrate the statistics of the wave function amplitudes generated on the 9-gmon chain and verify the quantum chaotic nature of the generated quantum distribution. This verifies the implementation of the quantum supremacy protocol.

Kechedzhi, Kostyantyn↗
DOE OSTI2020

Direct SERDS sensing of molecular biomarkers in plants under field conditions

Molecular biomarkers such as microRNAs (miRNAs) play important roles in regulating various developmental processes in plants. Understanding these pathways will help bioengineer designing organisms for efficient biomass accumulation. Current methods for RNA analysis require sample extraction and multi-step sample analysis, hindering work in field studies. Recent work in the incorporation of nanomaterials for plant bioengineering research is leading the way of an agri-tech revolution. As an example, surface-enhanced Raman scattering (SERS)–based sensors can be used to monitor RNA in vivo. However, the use of SERS in the field has been limited due to issues with observing Raman signal over complex background. To this end, shifted-excitation Raman difference spectroscopy (SERDS) offers an effective solution to extract the SERS signal from high background based on a physical approach. In this manuscript, we report the first application of SERDS on SERS sensors. We investigated this technique on SERS sensor developed for the detection of a microRNA biomarker, miR858. We tested the technique on in vitro samples and validated the technique by detecting the presence of exogenous miR858 in plants directly under ambient light in a growth chamber. The possibility of moving the detection of nucleic acid targets outside the constraints of laboratory setting enables numerous important bioengineering applications. Finally, such applications can revolutionize biofuel production and agri-tech through the use of nanotechnology-based monitoring of plant growth, plant health, and exposure to pollution and pathogens.

09 BIOMASS FUELS↗
DOE OSTI2023

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier-transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)

Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Could Microplasma Ionization and Ultrahigh Mass Resolution Alleviate Chemical Separations for Elemental and Isotopic Analysis?

At the extremes, all analytical spectrometric measurements are limited by the resolution of the spectrometer system. Spectral overlaps, isobars in the case of mass spectrometry, can lead to the implementation of complex and time-consuming chemical separations to alleviate those interferences. In the area of elemental/isotopic mass spectrometry, use of sector-field instruments can provide a mass resolution of ~10,000, but still necessitate chemical separations. Described here is the coupling of the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma to ultra-high resolution Orbitrap mass analyzer systems to yield mass resolution values ranging from 70k to 1M. Resolution of this order, with commensurate improvements in precision and accuracy, holds the promise to affect elemental/isotopic determinations without the need for chemical separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Space Weathering of Lunar Rocks and Regolith Grains

The exposed surfaces of lunar soil grains and lunar rocks become modified and coated over time with a thin rind of material (patina) through complex interactions with the space environment. These interactions encompass many processes including micrometeorite impacts, vapor and melt deposition, and solar wind implantation/sputtering effects that collectively are referred to as "space weathering". Studies of space weathering effects in lunar soils and rocks provide important clues to understanding the origin and evolution of the lunar regolith as well as aiding in the interpretation of global chemical and mineralogical datasets obtained by remote-sensing missions. The interpretation of reflectance spectra obtained by these missions is complicated because the patina coatings obscure the underlying rock mineralogy and compositions. Much of our understanding of these processes and products comes from decades of work on remote-sensing observations of the Moon, the analysis of lunar samples, and laboratory experiments. Space weathering effects collectively result in a reddened continuum slope, lowered albedo, and attenuated absorption features in reflectance spectra of lunar soils as compared to finely comminuted rocks from the same Apollo sites. Space weathering effects are largely surface-correlated, concentrated in the fine size fractions, and occur as amorphous rims on individual soil grains. Rims on lunar soil grains are highly complex and span the range between erosional surfaces modified by solar wind irradiation to depositional surfaces modified by the condensation of sputtered ions and impact-generated vapors. The optical effects of space weathering effects are directly linked to the production of nanophase Fe metal in lunar materials]. The size of distribution of nanophase inclusions in the rims directly affect optical properties given that large Fe(sup o) grains (approx 10 nm and larger) darken the sample (lower albedo) while the tiny Fe(sup o) grains (<5nm) are the primary agent in spectral "reddening". More recent work has focused on the nature and abundance of OH/H2O in the lunar regolith using orbital data and samples analyses. Advances in sample preparation techniques have made possible detailed analyses of patina-coated rock surfaces. Major advances are occurring in quantifying the rates and efficiency of space weathering processes through laboratory experimentation.

Keller, L. P.↗
DOE OSTI2021

Stabilized Lithium, Manganese-Rich Layered Cathode Materials Enabled by Integrating Co-Doping and Nanocoating

While lithium, manganese-rich (LMR) layered oxide cathode materials offer high energy density (>900 Wh kg –1 ) and low cost, LMR is susceptible to continuous capacity and voltage decay from the oxygen migration and side reaction with aqueous electrolyte at high voltage. Herein, the integration of Na/F co-doping (CD) and AlF 3 coating on LMR is achieved without the need of complex atomic layer deposition. Akin to pristine and CD samples, CD with 1 wt % AlF 3 (CD-1.0 wt %) shows excellent electrochemical performance with the capacity and voltage retentions of 93 and 91% after 150 cycles at 0.5C, respectively, and increased ionic conductivity. Spectroscopic analysis indicates that the coating mainly influences the Co distribution, where Co is enriched on the surface, and partial diffusion of Al 3+ ions toward the bulk, leading to a slight change of transition-metal (TM) valence states at the nanometer scale and the formation of a stable Li x (CoAl)O y phase. Post-cycling analysis reveals that CD-1.0 wt % can alleviate the formation of rock-salt structure and Mn dissolution. Besides, little to no metal segregation is detected for the cycled CD-1.0 wt % sample. This finding presents the first instance to apply co-doping and AlF 3 coating as a new strategy to enhance the structural homogeneity and takes another step toward their commercial viability.

25 ENERGY STORAGE↗
DOE OSTI2024

Bragg glass signatures in Pd x ErTe 3 with X-ray diffraction temperature clustering

The Bragg glass phase is a nearly perfect crystal with glassy features predicted to occur in vortex lattices and charge-density-wave systems in the presence of disorder. Detecting it has been challenging, despite its sharp theoretical definition in terms of diverging correlation lengths. Here we present bulk probe evidence supporting a Bragg glass phase in the systematically disordered charge-density-wave material of Pd x ErTe 3 . We do this by using comprehensive X-ray data and a machine-learning-based analysis tool called X-ray diffraction temperature clustering (X-TEC). We establish a diverging correlation length in samples with moderate intercalation over a wide temperature range. To enable this analysis, we introduced a high-throughput measure of inverse correlation length that we call peak spread. The detection of Bragg glass order and the resulting phase diagram advance our understanding of the complex interplay between disorder and fluctuations. Moreover, the use of our analysis technique to target fluctuations through a high-throughput measure of peak spread can revolutionize the study of fluctuations in scattering experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Standardized phylogenetic and molecular evolutionary analysis applied to species across the microbial tree of life

There is growing interest in reconstructing phylogenies from the copious amounts of genome sequencing projects that target related viral, bacterial or eukaryotic organisms. To facilitate the construction of standardized and robust phylogenies for disparate types of projects, we have developed a complete bioinformatic workflow, with a web-based component to perform phylogenetic and molecular evolutionary (PhaME) analysis from sequencing reads, draft assemblies or completed genomes of closely related organisms. Furthermore, the ability to incorporate raw data, including some metagenomic samples containing a target organism (e.g. from clinical samples with suspected infectious agents), shows promise for the rapid phylogenetic characterization of organisms within complex samples without the need for prior assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67

High-resolution spectroscopic surveys of the Milky Way have entered the Big Data regime and have opened avenues for solving outstanding questions in Galactic archeology. However, exploiting their full potential is limited by complex systematics, whose characterization has not received much attention in modern spectroscopic analyses. In this work, we present a novel method to disentangle the component of spectral data space intrinsic to the stars from that due to systematics. Using functional principal component analysis on a sample of 18,933 giant spectra from APOGEE, we find that the intrinsic structure above the level of observational uncertainties requires ≈10 functional principal components (FPCs). Our FPCs can reduce the dimensionality of spectra, remove systematics, and impute masked wavelengths, thereby enabling accurate studies of stellar populations. To demonstrate the applicability of our FPCs, we use them to infer stellar parameters and abundances of 28 giants in the open cluster M67. We employ Sequential Neural Likelihood, a simulation-based Bayesian inference method that learns likelihood functions using neural density estimators, to incorporate non-Gaussian effects in spectral likelihoods. By hierarchically combining the inferred abundances, we limit the spread of the following elements in M67: Fe ≲ 0.02 dex; C ≲ 0.03 dex; O, Mg, Si, Ni ≲ 0.04 dex; Ca ≲ 0.05 dex; N, Al ≲ 0.07 dex (at 68% confidence). Our constraints suggest a lack of self-pollution by core-collapse supernovae in M67, which has promising implications for the future of chemical tagging to understand the star formation history and dynamical evolution of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Hierarchical multisensor analysis for robotic exploration

Robotic vehicles for lunar and Mars exploration will carry an array of complex instruments requiring real-time data interpretation and fusion. The system described here uses hierarchical multiresolution analysis of visible and multispectral images to extract information on mineral composition, texture and object shape. This information is used to characterize the site geology and choose interesting samples for acquisition. Neural networks are employed for many data analysis steps. A decision tree progressively integrates information from multiple instruments and performs goal-driven decision making. The system is designed to incorporate more instruments and data types as they become available.

Eberlein, Susan↗
NASA NTRS2003

Origins of Solar Systems: Removing Activity-Related Radial Velocity Noise to Improve Extrasolar Planet Searches

We have continued the super high resolution (R is approximately 200,000), high S/N (> 300) echelle study of joint line bisector and radial velocity variations using the McDonald 2-D coude. A long observing run in October 2002 was quite successful (8 clear nights). We now have close to three years of data, which begins to sample a good fraction of the magnetic cycle timescales for some of our targets (e.g., K Ceti; P(sub cyc)=5.6 yrs). This will be very helpful in unraveling the complex relationships between plage and v(sub r), changes which we have uncovered. A preliminary analysis of the limited data in hand, and find some tantalizing evidence for correlations between median line bisector displacement and radial velocity v(sub r). The correlation appears to be specific to the particular star being considered, probably since it is a function of both spectral type and rotation rate. Additional information regarding progress on the grant is included.

Saar, Steven↗
NASA NTRS2004

Removing Activity-Related Radial Velocity Noise to Improve Extrasolar Planet Searches

We have made significant progress towards the proposal goals of understanding the causes and effects of magnetic activity-induced radial velocity (v_r) jitter and developing methods for correcting it. In the process, we have also made some significant discoveries in the fields of planet-induced stellar activity, planet detection methods, M dwarf convection, starspot properties, and magnetic dynamo cycles. We have obtained super high resolution (R approximately 200,000), high S / N (greater than 300) echelle study of joint line bisector and radial velocity variations using the McDonald 2-D coude. A long observing run in October 2002 in particular was quite successful (8 clear nights). We now have close to three years of data, which begins to sample a good fraction of the magnetic cycle timescales for some of our targets (e.g., kappa Ceti; P_cyc = 5.6 yrs). This will be very helpful in unraveling the complex relationships between plage and radial velocity (v-r) changes which we have uncovered. Preliminary analysis (Saar et al. 2003) of the data in hand, reveals correlations between median line bisector displacement and v_r. The correlation appears to be specific the the particular star being considered, probably since it is a function of both spectral type and rotation rate. Further analysis and interpretation will be in the context of evolving plage models and is in progress.

Saar, Steven↗
NASA NTRS2008

Schedule Risks Due to Delays in Advanced Technology Development

This paper discusses a methodology and modeling capability that probabilistically evaluates the likelihood and impacts of delays in advanced technology development prior to the start of design, development, test, and evaluation (DDT&E) of complex space systems. The challenges of understanding and modeling advanced technology development considerations are first outlined, followed by a discussion of the problem in the context of lunar surface architecture analysis. The current and planned methodologies to address the problem are then presented along with sample analyses and results. The methodology discussed herein provides decision-makers a thorough understanding of the schedule impacts resulting from the inclusion of various enabling advanced technology assumptions within system design.

Reeves, John D. Jr.↗
NASA NTRS2012

Laser Time-of-Flight Mass Spectrometry for Future In Situ Planetary Missions

Laser desorption/ionization time-of-flight mass spectrometry (LD-TOF-MS) is a versatile, low-complexity instrument class that holds significant promise for future landed in situ planetary missions that emphasize compositional analysis of surface materials. Here we describe a 5kg-class instrument that is capable of detecting and analyzing a variety of analytes directly from rock or ice samples. Through laboratory studies of a suite of representative samples, we show that detection and analysis of key mineral composition, small organics, and particularly, higher molecular weight organics are well suited to this instrument design. A mass range exceeding 100,000 Da has recently been demonstrated. We describe recent efforts in instrument prototype development and future directions that will enhance our analytical capabilities targeting organic mixtures on primitive and icy bodies. We present results on a series of standards, simulated mixtures, and meteoritic samples.

Getty, S. A.↗