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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Key Perseverance Sampling Locations for the Ancient Martian Crust and Implications for Mars Science

Since Feb 2021, the Perseverance rover has collected samples in the Jezero crater. The plan baselined at the 2018 landing site selection, subsequently further developed by the Mars-2020 team, and presented to the Decadal Survey included the exploration and sampling of the Jezero crater rim and the Nili Planum area, a rock record that is important to preserving the science return of the endeavor. Specifically, the science team identified the following prioritized science objectives aligned with community objectives that are not covered by the current sample cache: 1) Investigate the habitable environments with potential biosignatures from a more ancient time interval and from a diverse set of geological environments (incl. exposed subsurface) than the Jezero crater sedimentary deposits (Fig. 2). (2) Determine radioisotopic ages for well-defined craterretaining surfaces and/or the Isidis basin impact event. (3) Characterize ancient aqueous environments to study climate, environmental transitions, and habitability on ancient Mars. (4) Investigate planetary accretion, crustal evolution, and dynamo activity through analysis and sampling of igneous lithologies. (5) Study the geology of basin-forming impacts. In addition, for the Jezero rim and any Jezero ejecta: (6) Analyze Jezero impactites for potentially habitable hydrothermal environments and radioisotopic dating of the Jezero crater formation. From 2018 to now, we used a combination of High Resolution Imaging Experiment (HiRISE) and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data to further characterize Jezero rim and Nili Planum, culminating in our prioritized sample location recommendations: (1) Monument Valley and (2) Northwest Jezero rim.

Mars sample return↗
DOE OSTI2017

Method for Hot Real-Time Sampling of Pyrolysis Vapors

Biomass Pyrolysis has been an increasing topic of research, in particular as a replacement for crude oil. This process utilizes moderate temperatures to thermally deconstruct the biomass which is then condensed into a mixture of liquid oxygenates to be used as fuel precursors. Pyrolysis oils contain more than 400 compounds, up to 60 percent of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during the condensation and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors, many challenges must be overcome. Sampling must occur within a narrow range of temperatures to reduce product composition changes from overheating or partial condensation or plugging of lines from condensed products. Residence times must be kept at a minimum to reduce further reaction chemistries. Pyrolysis vapors also form aerosols that are carried far downstream and can pass through filters resulting in build-up in downstream locations. The co-produced bio-char and ash from the pyrolysis process can lead to plugging of the sample lines, and must be filtered out at temperature, even with the use of cyclonic separators. A practical approach for considerations and sampling system design, as well as lessons learned are integrated into the hot analytical sampling system of the National Renewable Energy Laboratory's (NREL) Thermochemical Process Development Unit (TCPDU) to provide industrially relevant demonstrations of thermochemical transformations of biomass feedstocks at the pilot scale.

09 BIOMASS FUELS↗
DOE OSTI2018

Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch

Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Sample Complexity of Power System State Estimation using Matrix Completion: Preprint

In this paper, we propose an analytical framework to quantify the amount of data samples needed to obtain accurate state estimation in a power system-a problem known as \emph{sample complexity} analysis in computer science. Motivated by the increasing adoption of distributed energy resources into the distribution-level grids, it becomes imperative to estimate the state of distribution grids in order to ensure stable operation. Traditional power system state estimation techniques mainly focus on the transmission network which involve solving an overdetermined system and eliminating bad data. However, distribution networks are typically \emph{underdetermined} due to the large number of connection points and high cost of pervasive installation of measurement devices. In this paper, we consider the recently proposed state-estimation method for underdetermined systems that is based on \emph{matrix completion}. In particular, a \emph{constrained} matrix completion algorithm was proposed, wherein the standard matrix completion problem is augmented with additional equality constraints representing the physics (namely power-flow constraints). We analyze the sample complexity of this general method by proving an upper bound on the sample complexity that depends directly on the properties of these constraints that can lower number of needed samples as compared to the unconstrained problem. To demonstrate the improvement that the constraints add to state estimation, we test the method on a 141-bus distribution network case study and compare it to the traditional least squares minimization state estimation method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

An Efficient Sampling-Based Method for Sensitivity and Uncertainty Analysis Through RAVEN

Sensitivity analysis (SA) and uncertainty quantification (UQ) are now widely recognized as essential parts of analyses for complex nuclear systems. Plenty of well-established methodologies are already available for performing SA and UQ, such as Monte Carlo analysis, adjoint-based method, and variance decomposition. The focus of this summary is on developing an efficient sampling-based approach to perform SA and UQ through RAVEN. RAVEN (Risk Analysis and Virtual control Environment) is a software framework able to perform SA and UQ, currently under development at the Idaho National Laboratory. In literature, a number of approaches have been developed to accelerate the process of SA and UQ for large complex systems, such as principal component analysis (PCA) of input space, input-output correlation analysis, and intersection subspace methods. The fundamental idea is to identify the dominant active directions in the parameter space prior to conducting SA and UQ. The premise is that the number of active directions is much less than the dimensionality of input space. In this work, the PCA or Karhunen-Loeve expansion or SVD method is implemented in RAVEN to identify the active directions. This approach is also combined with the forward sampling approaches, such as Monte Carlo, Grid, Latin Hypercube, and Response Surface Design sampling approaches that are currently available in RAVEN, to perform SA and UQ more efficiently. The summary is organized as follows. In the following section, we present the PCA-based forward sampling approach. The effectiveness and efficiency are discussed in the numerical results section. The paper then ends with a concluding summary. In this summary, we have presented PCA-based forward sampling approach to perform SA and UQ. The goal is to reduce the computational overhead for repetitive executions of complex nuclear systems that are generally required when performing SA and UQ. The control of correlations between input parameters is implemented in RAVEN to better represent the input relationships. In addition, we are currently examining our implementations with more realistic models, and we are also focusing on implementation of some new high-dimensional input reduction techniques in RAVEN. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Improvement of Drop‐Hammer Impact Testing for Safety Assessment of High Explosives Using 10‐mg Samples

Here, in this study, we established an improved method for drop-hammer impact testing of small quantities of high explosives (10 mg). We performed about seven hundred impact tests under various experimental conditions (e.g., sandpaper vs bare anvil, different sample masses, drop-weights, and striker diameters) to determine an optimal set of conditions and reaction detection methods (e.g., gas analysis, video, and sound recordings) that give the most statistically reliable results with 10 mg samples. We used both Frequentist and Bayesian statistical approaches to compare estimates of the drop height (DH50) that initiates a reaction 50% of the time, and to quantify the associated uncertainty. Gas analysis proved to be the most reliable reaction detection method, showing unambiguous rises in HE decomposition products (e.g., CO 2 ) even when the other indicators (e.g., sound, video) were inconclusive. The impact tests performed with a bare anvil showed much better reproducibility than those conducted with sandpaper, reducing the largest uncertainty observed in the data sets by a factor of 1.7. The DH 50 values obtained from three different sample masses (10, 20, and 35 mg) fell within the uncertainties of the measurements. We demonstrated the improved procedure (i.e., 10-mg samples, gas analysis, bare anvil, and Bayesian approach) on a variety of PETN samples having different surface areas and thermal histories.

PETN↗
DOE OSTI2016

Fukushima Daiichi reactor source term attribution using cesium isotope ratios from contaminated environmental samples

Source term attribution of environmental contamination following the Fukushima Daiichi Nuclear Power Plant (FDNPP) disaster is complicated by a large number of possible similar emission source terms (e.g. FDNPP reactor cores 1–3 and spent fuel ponds 1–4). Cesium isotopic analyses can be utilized to discriminate between environmental contamination from different FDNPP source terms and, if samples are sufficiently temporally resolved, potentially provide insights into the extent of reactor core damage at a given time. In this work, rice, soil, mushroom, and soybean samples taken 100–250 km from the FDNPP site were dissolved using microwave digestion. Radiocesium was extracted and purified using two sequential ammonium molybdophosphate-polyacrylonitrile columns, following which 135 Cs/ 137 Cs isotope ratios were measured using thermal ionization mass spectrometry (TIMS). Results were compared with data reported previously from locations to the northwest of FDNPP and 30 km to the south of FDNPP. 135 Cs/ 137 Cs isotope ratios from samples 100–250 km to the southwest of the FDNPP site show a consistent value of 0.376 ± 0.008. 135 Cs/ 137 Cs versus 134 Cs/ 137 Cs correlation plots suggest that radiocesium to the southwest is derived from a mixture of FDNPP reactor cores 1, 2, and 3. Conclusions from the cesium isotopic data are in agreement with those derived independently based upon the event chronology combined with meteorological conditions at the time of the disaster. In conclusion, cesium isotopic analyses provide a powerful tool for source term discrimination of environmental radiocesium contamination at the FDNPP site. For higher precision source term attribution and forensic determination of the FDNPP core conditions based upon cesium, analyses of a larger number of samples from locations to the north and south of the FDNPP site (particularly time-resolved air filter samples) are needed. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Sample size estimation for case‐crossover studies

Case‐crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case‐crossover study is self‐controlled, its advantages include better control for confounding because the design controls for any time‐invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self‐matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case‐crossover study, investigators currently use Dupont's formula ( Biometrics 1988; 43 :1157‐1168), which was originally developed for a matched case‐control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self‐controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case‐crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.

Dharmarajan, Sai↗
DOE OSTI2024

Robust surfactant-assisted one-pot sample preparation for label-free single-cell and nanoscale proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.

Single-cell proteomics, nanoscale proteomics, SOP-↗
DOE OSTI2018

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Rapid fusion method for the determination of Pu, Np, and Am in large soil samples

A new rapid sodium hydroxide fusion method for the preparation of 10-20 g soil samples has been developed by the Savannah River National Laboratory (SRNL). The method enables lower detection limits for plutonium, neptunium, and americium in environmental soil samples. The method also significantly reduces sample processing time and acid fume generation compared to traditional soil digestion techniques using hydrofluoric acid. Ten gram soil aliquots can be ashed and fused using the new method in 1-2 hours, completely dissolving samples, including refractory particles. Pu, Np and Am are separated using stacked 2mL cartridges of TEVA and DGA Resin and measured using alpha spectrometry. The method can be adapted for measurement by inductively-coupled plasma mass spectrometry (ICP-MS). Two 10 g soil aliquots of fused soil may be combined prior to chromatographic separations to further improve detection limits. Total sample preparation time, including chromatographic separations and alpha spectrometry source preparation, is less than 8 hours.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Rapid method to determine actinides and 89/90 Sr in limestone and marble samples

A new method for the determination of actinides and radiostrontium in limestone and marble samples has been developed that utilizes a rapid sodium hydroxide fusion to digest the sample. Following rapid pre-concentration steps to remove sample matrix interferences, the actinides and 89/90 Sr are separated using extraction chromatographic resins and measured radiometrically. The advantages of sodium hydroxide fusion versus other fusion techniques will be discussed. Lastly, this approach has a sample preparation time for limestone and marble samples of <4 hours.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Theoretical realization of three-dimensional nanolattice structure fabrication based on high-order waveguide-mode interference and sample rotation

A theoretical method of using high-order waveguide-mode interference combined with sample rotation is proposed to fabricate different kinds of three-dimensional nanolattice structures. The lithography sample is assisted by an asymmetric metal-cladding dielectric waveguide structure. High-order waveguide modes can be excited in the photoresist layer by both transverse magnetic and transverse electric polarized light. By utilizing multiple exposures of high-order waveguide-mode interference combined with sample-rotation, various three-dimensional nanolattice structures can be obtained. The resulting optical field distributions are simulated using the finite element method in this study, and sample rotation is expressed by coordinate matrix transformation. As examples, the three-dimensional optical field distributions resulting from fifth-order waveguide-mode interference were simulated with 90° and 60° sample rotations and multiple exposures. The results show that a quasi-cuboid structure with a simple tetragonal arrangement and a quasi-hexagonal structure with a hexagonal close-packed lattice can be obtained. Moreover, the numerical simulation results revealed that the shapes, sizes, arrangements, and periods of the structures can be controlled by the rotation method, photoresist thickness, waveguide modes used for exposure, and so on.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗
DOE OSTI2016

Effects of mechanical stress and vitreous samples in retinal pigment epithelial cells

In rhegmatogenous retinal detachment (RRD), scattered RPE cells from the basement membrane into the vitreous cavity undergo an epithelial mesenchymal transition (EMT) and form the intraocular fibrous membrane in response to vitreous fluid. We investigated whether exposure to vitreous samples was associated with EMT-associated signals and mesenchymal characters. Human vitreous samples were collected from patients with RRD, epiretinal membrane (ERM), or macular hole (MH). We evaluated the effects of vitreous on ARPE-19 cells in suspension cultures using poly 2-hydroxyethyl methacrylate-coated dishes and three-dimensional (3D) Matrigel cultures. We found that exposure to vitreous samples did not induce morphological changes or accelerate wound closure in monolayers. Several samples showed increased phosphorylation of Smad2 and nuclear translocation of nuclear factor-κB. Mechanical stress triggered an elevation of phosphorylation levels in Smad2. In addition, exposure to vitreous fluid increased the phosphorylation of p38 mitogen-activated protein kinase in cell suspension cultures after mechanical stress. Moreover, ARPE-19 cells showed a stellate invasive phenotype in 3D Matrigel cultures with vitreous samples. In this study, we demonstrated that mechanical stress and vitreous were associated with EMT-associated signals and invasive phenotypes in 3D cultures but not in monolayers. These results have important implications for the role of vitreous humor in the induction of EMT and intraocular fibrosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

135 Cs/ 137 Cs isotopic composition of environmental samples across Europe: Environmental transport and source term emission applications

135 Cs/ 137 Cs isotopic analyses represent an important tool for studying the fate and transport of radiocesium in the environment; in this work the 135 Cs/ 137 Cs isotopic composition in environmental samples taken from across Europe is reported. Surface soil and vegetation samples from western Russia, Ukraine, Austria, and Hungary show consistent aged thermal fission product 135 Cs/ 137 Cs isotope ratios of 0.58 ± 0.01 (age corrected to 1/1/15), with the exception of one sample of soil-moss from Hungary which shows an elevated 135 Cs/ 137 Cs ratio of 1.78 ± 0.12. With the exception of the outlier sample from Hungary, surface soil/vegetation data are in quantitative agreement with values previously reported for soils within the Chernobyl exclusion zone, suggesting that radiocesium at these locations is primarily composed of homogenous airborne deposition from Chernobyl. Seawater samples taken from the Irish Sea show 135 Cs/ 137 Cs isotope ratios of 1.22 ± 0.11 (age corrected to 1/1/15), suggesting aged thermal fission product Cs discharged from Sellafield. Furthermore, the differences in 135 Cs/ 137 Cs isotope ratios between Sellafield, Chernobyl, and global nuclear weapons testing fallout indicate that 135 Cs/ 137 Cs isotope ratios can be utilized to discriminate between and track radiocesium transport from different nuclear production source terms, including major emission sources in Europe.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Sampling two-dimensional isometric tensor network states

Sampling a quantum system’s underlying probability distributions is an important computational task, e.g., for quantum advantage experiments and quantum Monte Carlo algorithms. Tensor networks are an invaluable tool for efficiently representing states of large quantum systems with limited entanglement. Algorithms for sampling one-dimensional (1D) tensor networks are well-established and utilized in several 1D tensor network methods. In this paper we introduce two novel sampling algorithms for two-dimensional (2D) isometric tensor network states (isoTNS) that generalize existing 1D tensor network sampling algorithms. Our first proposed algorithm performs independent sampling and yields a single configuration together with its associated probability. The second algorithm employs a greedy search strategy to identify high-probability configurations and their corresponding probabilities. Numerical results demonstrate the effectiveness of these algorithms across quantum states with varying entanglement and system size.

Dumitrescu, Eugene [ORNL] (ORCID:0000000158519567)↗
DOE OSTI2023

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗