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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Advantages and Disadvantages of using a Focused Ion Beam to Prepare TEM Samples From Irradiated U-10Mo Monolithic Nuclear Fuel

Transmission electron microscopy (TEM), scanning electron microscopy (SEM), and focused ion beam (FIB) milling were performed on an irradiated U-10Mo monolithic fuel to understand its irradiation microstructure. This is the first reported TEM work of irradiated fuel sample prepared using a FIB. Advantages and disadvantages of using the FIB to create TEM samples from this irradiated fuel will be presented along with some results from the work. Sample preparation techniques used to create SEM and FIB samples from the brittle irradiated monolithic sample will also be discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

An efficient and cost-effective method for preparing transmission electron microscopy samples from powders

The preparation of transmission electron microcopy (TEM) samples from powders with particle sizes larger than ~100 nm poses a challenge. The existing methods are complicated and expensive, or have a low probability of success. Herein, we report a modified methodology for preparation of TEM samples from powders, which is efficient, cost-effective, and easy to perform. This method involves mixing powders with an epoxy on a piece of weighing paper, curing the powder–epoxy mixture to form a bulk material, grinding the bulk to obtain a thin foil, punching TEM discs from the foil, dimpling the discs, and ion milling the dimpled discs to electron transparency. Compared with the well established and robust grinding–dimpling–ion-milling method for TEM sample preparation for bulk materials, our modified approach for preparing TEM samples from powders only requires two additional simple steps. In this article, step-by-step procedures for our methodology are described in detail, and important strategies to ensure success are elucidated. Furthermore, our methodology has been applied successfully for preparing TEM samples with large thin areas and high quality for many different mechanically milled metallic powders.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Simple Sodium Dodecyl Sulfate-Assisted Sample Preparation Method for LC-MS-based Proteomic Applications

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for highly efficient biological sample extraction; however, SDS presents a significant challenge to LC-MS-based proteomic analyses due to its severe interference with reversed-phase LC separations and electrospray ionization interfaces. This study reports a simple SDS-assisted proteomic sample preparation method facilitated by a novel peptide-level SDS removal protocol. After SDS-assisted protein extraction and digestion, SDS was effectively (>99.9%) removed from peptides through ion substitution-mediated DS- precipitation with potassium chloride (KCl) followed by {approx}10 min centrifugation. Excellent peptide recovery (>95%) was observed for less than 20 {mu}g of peptides. Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage from this SDS-assisted protocol was comparable to or better than those obtained from other standard proteomic preparation methods in both mammalian tissues and bacterial samples. These results suggest that this SDS-assisted protocol is a practical, simple, and broadly applicable proteomic sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Design and Evaluation of a Tethered, Open Port Sampling Interface for Liquid Extraction-Mass Spectrometry Chemical Analysis

Presented in this work is a tethered, liquid-extraction-sampling interface designed for the mass spectrometric surface sampling/analysis of 3D objects. The tethered, open port sampling interface (TOPSI) incorporates a vacuum line between the sampling probe and ionization source, which enables the ability for an extended, tethered sample transfer line. Herein, several designs of the hand-held TOPSI are presented and evaluated on the basis of the analytical metrics of analyte transport time, peak width, and analyte sensitivity. The best analytical metrics were obtained with capillary flow resistances arranged in a particular order and the vacuum region set at 6.2 kPa. This TOPSI design incorporated a transfer capillary 1 m in length, while retaining a fast analyte transport time (12 s), short signal peak width (5 s baseline-to-baseline), and high analyte signal at 90% of that obtained with a regular open port sampling interface (OPSI). The hand-held TOPSI was demonstrated for the characterization of extracted small molecules and metabolites from the surface of mint and rosemary leaves.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Improved explosive collection and detection with rationally assembled surface sampling materials

Sampling and detection of trace explosives is a key analytical process in modern transportation safety. In this work we have explored some of the fundamental analytical processes for collection and detection of trace level explosive on surfaces with the most widely utilized system, thermal desorption IMS. The performance of the standard muslin swipe material was compared with chemically modified fiberglass cloth. The fiberglass surface was modified to include phenyl functional groups. When compared to standard muslin, the phenyl functionalized fiberglass sampling material showed better analyte release from the sampling material as well as improved response and repeatability from multiple uses of the same swipe. The improved sample release of the functionalized fiberglass swipes resulted in a significant increase in sensitivity. Various physical and chemical properties were systematically explored to determine optimal performance. The results herein have relevance to improving the detection of other explosive compounds and potentially to a wide range of other chemical sampling and field detection challenges.

Explosive detection↗
DOE OSTI2012

Note: A sample holder design for sensitive magnetic measurements at high temperatures in a magnetic properties measurement system

A sample holder design for high temperature measurements in a commercial MPMS SQUID magnetometer from Quantum Design is presented. It fulfills the requirements for the simultaneous use of the oven and reciprocating sample option (RSO) options, thus allowing sensitive magnetic measurements up to 800 K. Alternating current susceptibility can also be measured, since the holder does not induce any phase shift relative to the ac driven field. It is easily fabricated by twisting Constantan Copyright-Sign wires into a braid nesting the sample inside. This design ensures that the sample be placed tightly into a tough holder with its orientation fixed, and prevents any sample displacement during the fast movements of the RSO transport, up to high temperatures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Compact cold stage for micro-computerized tomography imaging of chilled or frozen samples

High resolution X-ray microCT (computerized tomography) can be used to image a variety of objects, including temperature-sensitive materials. In cases where the sample must be chilled or frozen to maintain sample integrity, either the microCT machine itself must be placed in a refrigerated chamber, or a relatively expensive commercial cold stage must be purchased. We describe here the design and construction of a low-cost custom cold stage suitable for use in a microCT imaging system. Our device uses a boron nitride sample holder, two-stage Peltier cooler, fan-cooled heat sink, and electronic controller to maintain sample temperatures as low as −25 °C ± 0.2 °C for the duration of a tomography acquisition. The design does not require modification to the microCT machine, and is easily installed and removed. Our custom cold stage represents a cost-effective solution for refrigerating CT samples for imaging, and is especially useful for shared equipment or machines unsuitable for cold room use.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

ANALYZING STAR CLUSTER POPULATIONS WITH STOCHASTIC MODELS: THE HUBBLE SPACE TELESCOPE/WIDE FIELD CAMERA 3 SAMPLE OF CLUSTERS IN M83

The majority of clusters in the universe have masses well below 10{sup 5} M{sub Sun }. Hence, their integrated fluxes and colors can be affected by the presence or absence of a few bright stars introduced by stochastic sampling of the stellar mass function. Specific methods are being developed to extend the analysis of cluster energy distributions into the low-mass regime. In this paper, we apply such a method to real observations of star clusters, in the nearby spiral galaxy M83. We reassess the ages and masses of a sample of 1242 clusters for which UBVIH{alpha} fluxes were obtained from observations with the Wide Field Camera 3 instrument on board the Hubble Space Telescope. Synthetic clusters with known properties are used to characterize the limitations of the method (valid range and resolution in age and mass, method artifacts). The ensemble of color predictions of the discrete cluster models are in good agreement with the distribution of observed colors. We emphasize the important role of the H{alpha} data in the assessment of the fraction of young objects, particularly in breaking the age-extinction degeneracy that hampers an analysis based on UBVI data only. We find the mass distribution of the cluster sample to follow a power law of index -2.1 {+-} 0.2, and the distribution of ages a power law of index -1.0 {+-} 0.2 for log (M/ M{sub Sun }) > 3.5, and ages between 10{sup 7} and 10{sup 9} yr. An extension of our main method, which makes full use of the probability distributions of age and mass obtained for the individual clusters of the sample, is explored. It produces similar power-law slopes and will deserve further investigation. Although the properties derived for individual clusters significantly differ from those obtained with traditional, non-stochastic models in about 30% of the objects, the first-order aspect of the age and mass distributions is similar to those obtained previously for this M83 sample in the range of overlap of the studies. We extend the power-law description to lower masses with better mass and age resolution and without most of the artifacts produced by the classical method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Cosmic ray sampling of a clumpy interstellar medium

How cosmic rays sample the multi-phase interstellar medium (ISM) in starburst galaxies has important implications for many science goals, including evaluating the cosmic ray calorimeter model for these systems, predicting their neutrino fluxes, and modeling their winds. Here, we use Monte Carlo simulations to study cosmic ray sampling of a simple, two-phase ISM under conditions similar to those of the prototypical starburst galaxy M82. The assumption that cosmic rays sample the mean density of the ISM in the starburst region is assessed over a multi-dimensional parameter space where we vary the number of molecular clouds, the galactic wind speed, the extent to which the magnetic field is tangled, and the cosmic ray injection mechanism. We evaluate the ratio of the emissivity from pion production in molecular clouds to the emissivity that would be observed if the cosmic rays sampled the mean density, and seek areas of parameter space where this ratio differs significantly from unity. The assumption that cosmic rays sample the mean density holds over much of parameter space; however, this assumption begins to break down for high cloud density, injection close to the clouds, and a very tangled magnetic field. We conclude by evaluating the extent to which our simulated starburst region behaves as a proton calorimeter and constructing the time-dependent spectrum of a burst of cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Alignment of sample position and rotation during in situ synchrotron X-ray micro-diffraction experiments using a Laue cross-correlation approach

Laue micro-diffraction has proven to be able to reveal material properties at the sub-grain scale for many polycrystalline materials and is now routinely available at several synchrotron facilities, providing an approach for nondestructive three-dimensional probing of the microstructures and mechanical states of materials. However, for in situ experiments, maintaining the positioning of the sample throughout the experiment, to achieve a good alignment of the characterized volumes, is a challenging issue. The aim of the present work is to address this problem by developing an approach based on digital image correlation of focused-beam Laue diffraction patterns. The method uses small changes in the diffraction signal as a focused X-ray beam is scanned over a surface region to allow corrections to be made for both sample lateral movement and rotation. The method is demonstrated using a tensile deformation experiment on an Al sample with 2.5 µm average grain size. The results demonstrate an accuracy of 0.5 µm for sample position registration and a precision in sample rotation of ~0.01°. Finally, the proposed method is fast to implement and does not require the use of additional surface markers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗
DOE OSTI2019

Sample Complexity of Power System State Estimation Using Matrix Completion

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 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 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 matrix completion. In particular, a 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 OSTI2012

False-Negative Rate and Recovery Efficiency Performance of a Validated Sponge Wipe Sampling Method

Recovery of spores from environmental surfaces varies due to sampling and analysis methods, spore size and characteristics, surface materials, and environmental conditions. Tests were performed to evaluate a new, validated sponge wipe method using Bacillus atrophaeus spores. Testing evaluated the effects of spore concentration and surface material on recovery efficiency (RE), false-negative rate (FNR), limit of detection (LOD), and their uncertainties. Ceramic tile and stainless steel had the highest mean RE values (48.9 and 48.1%, respectively). Faux leather, vinyl tile, and painted wood had mean RE values of 30.3, 25.6, and 25.5, respectively, while plastic had the lowest mean RE (9.8%). Results show roughly linear dependences of RE and FNR on surface roughness, with smoother surfaces resulting in higher mean REs and lower FNRs. REs were not influenced by the low spore concentrations tested (3.10x10^-3 to 1.86 CFU/cm^2). Stainless steel had the lowest mean FNR (0.123), and plastic had the highest mean FNR (0.479). The LOD90 (>1 CFU detected 90% of the time) varied with surface material, from 0.015 CFU/cm^2 on stainless steel up to 0.039 on plastic. It may be possible to improve sampling results by considering surface roughness in selecting sampling locations and interpreting spore recovery data. Further, FNR values (calculated as a function of concentration and surface material) can be used presampling to calculate the numbers of samples for statistical sampling plans with desired performance and postsampling to calculate the confidence in characterization and clearance decisions.

Anthrax↗
DOE OSTI2016

Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling

The increasing complexity of both scientific simulations and high-performance computing system architectures are driving the need for adaptive workflows, in which the composition and execution of computational and data manipulation steps dynamically depend on the evolutionary state of the simulation itself. Consider, for example, the frequency of data storage. Critical phases of the simulation should be captured with high frequency and with high fidelity for postanalysis; however, we cannot afford to retain the same frequency for the full simulation due to the high cost of data movement. We can instead look for triggers, indicators that the simulation will be entering a critical phase, and adapt the workflow accordingly. In this paper, we present a methodology for detecting triggers and demonstrate its use in the context of direct numerical simulations of turbulent combustion using S3D. We show that chemical explosive mode analysis (CEMA) can be used to devise a noise-tolerant indicator for rapid increase in heat release. However, exhaustive computation of CEMA values dominates the total simulation, and thus is prohibitively expensive. To overcome this computational bottleneck, we propose a quantile sampling approach. Our sampling-based algorithm comes with provable error/confidence bounds, as a function of the number of samples. Most importantly, the number of samples is independent of the problem size, and thus our proposed sampling algorithm offers perfect scalability. Our experiments on homogeneous charge compression ignition and reactivity controlled compression ignition simulations show that the proposed method can detect rapid increases in heat release, and its computational overhead is negligible. Our results will be used to make dynamic workflow decisions regarding data storage and mesh resolution in future combustion simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling.

The recent growth in multifidelity uncertainty quantification has given rise to a large set of variance reduction techniques that leverage information from model ensembles to provide variance reduction for estimates of the statistics of a high-fidelity model. In this paper we provide two contributions: (1) we utilize an ensemble estimator to account for uncertainties in the optimal weights of approximate control variate (ACV) approaches and derive lower bounds on the number of samples required to guarantee variance reduction; and (2) we extend an existing multifidelity importance sampling (MFIS) scheme to leverage control variates. Our approach directly addresses a limitation of many multifidelity sampling strategies that require the usage of pilot samples to estimate covariances. As such we make significant progress towards both increasing the practicality of approximate control variates—for instance, by accounting for the effect of pilot samples—and using multifidelity approaches more effectively for estimating low-probability events. The numerical results indicate our hybrid MFIS-ACV estimator achieves up to 50% improvement in variance reduction over the existing state-of-the-art MFIS estimator, which had already shown an outstanding convergence rate compared to the Monte Carlo method, on several problems of computational mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Related sensor data are published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054. This data package was originally published September 2022. It was updated May 2023 (modified files) and November 2024 (new and modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), ions, and benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol (8) readme; (9) methods codes; (10) international generic-sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We thank the United States Forest Service, Washington Department of Natural Resources, Washington Department of Fish and Wildlife, Washington State Parks, Confederated Tribes and Bands of the Yakama Nation, and Cowiche Canyon Conservancy for access to field locations where these samples were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Characteristics of KE Basin Sludge Samples Archived in the RPL - 2007

Samples of sludge were collected from the K East fuel storage basin (KE Basin) floor, contiguous pits (Weasel Pit, North Load Out Pit, Dummy Elevator Pit, and Tech View Pit), and fuel storage canisters between 1995 and 2003 for chemical and radionuclide concentration analysis, physical property determination, and chemical process testing work. Because of the value of the sludge in this testing and because of the cost of obtaining additional fresh samples, an ongoing program of sludge preservation has taken place with the goals to track the sludge identities and preserve, as well as possible, the sludge composition by keeping the sludge in sealed jars and maintaining water coverage on the sludge consistent with the controlling Fluor Hanford (FH) Sampling and Analysis plans and FH contracts with the Pacific Northwest National Laboratory (PNNL). This work was originally initiated to provide material for planned hydrothermal treatment testing in accordance with the test plan for the Sludge Treatment Project (STP) corrosion process chemistry follow on testing (Delegard et al. 2007). Although most of the planned hydrothermal testing was canceled in July 2007 (as described in the forward of Delegard et al. 2007), sample consolidation and characterization was continued to identify a set of well-characterized sludge samples that are suited to support evolving STP initiatives. The work described in the letter was performed by the PNNL under the direction of the Sludge Treatment Project, managed by Fluor Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗