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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI1969

Application of Nuclear Technology to Art Identification Problems: First Annual Report

Throughout the centuries, as man has become increasingly affluent, his interest in antiquities and objects of art, and the price he has been willing to pay for them, has increased. Inevitably, one result has been to attract the unscrupulous to the production and sale of counterfeit paintings, sculptures, and other works of art. The skill of forgers varies but often is highly sophisticated. However, dealers, museum curators, and other experts have also become more skillful in the detection of forgeries. Scientific tools of increasing sensitivity and sophistication have gradually been applied to the examination of the materials of art and archaeology. Such tools frequently support and render more reliable the judgment of the experts. The quality of forgeries may improve further as their makers become acquainted with the new methods of detection and in turn learn to circumvent or confound the methods. Therefore, the development of still more advanced methods of examination has great utility in the art world. This is particularly true if the ultimate effect is to make circumvention of the methods of examination so costly that the economic incentives for producing forgeries may be substantially reduced, if not eliminated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multifrontal Non-negative Matrix Factorization

Non-negative matrix factorization (Nmf) is an important tool in high-performance large scale data analytics with applications ranging from community detection, recommender system, feature detection and linear and non-linear unmixing. While traditional Nmf works well when the data set is relatively dense, however, it may not extract sufficient structure when the data is extremely sparse. Specifically, traditional Nmf fails to exploit the structured sparsity of the large and sparse data sets resulting in dense factors. We propose a new algorithm for performing Nmf on sparse data that we call multifrontal Nmf (Mf-Nmf) since it borrows several ideas from the multifrontal method for unconstrained factorization (e.g. LU and QR). We also present an efficient shared memory parallel implementation of Mf-Nmf and discuss its performance and scalability. We conduct several experiments on synthetic and realworld datasets and demonstrate the usefulness of the algorithm by comparing it against standard baselines. We obtain a speedup of 1.2x to 19.5x on 24 cores with an average speed up of 10.3x across all the real world datasets.

Sao, Piyush↗
DOE OSTI2024

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗
NASA NTRS1995

Standardization of surface contamination analysis systems

Corrosion products, oils and greases can potentially degrade material bonding properties. The Marshall Space Flight Center (MSFC) Surface Contamination Analysis Team (SCAT) utilizes a variety of analytical equipment to detect identify and quantify contamination on metallic and non-metallic substrates. Analysis techniques include FT-IR Microscopy (FT-IR), Near Infrared Optical Fiber Spectrometry (NIR), Optically Stimulated Electron Emission (OSEE), Ultraviolet Fluorescence (UVF) and Ellipsometry. To insure that consistent qualitative and quantitative information are obtained, standards are required to develop analysis techniques, to establish instrument sensitivity to potential contaminants, and to develop calibration curves. This paper describes techniques for preparing and preserving contamination standards. Calibration of surface contamination analysis systems is discussed, and methods are presented for evaluating the effects of potential contaminants on bonding properties.

Boothe, Richard E.↗
NASA NTRS2018

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efficient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufficiently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
NASA NTRS2005

Identifying or measuring selected substances or toxins in a subject using resonant raman signals

Methods and systems of the present invention identify the presence of and/or the concentration of a selected analyte in a subject by: (a) illuminating a selected region of the eye of a subject with an optical excitation beam, wherein the excitation beam wavelength is selected to generate a resonant Raman spectrum of the selected analyte with a signal strength that is at least 100 times greater than Raman spectrums generated by non-resonant wavelengths and/or relative to signals of normal constituents present in the selected region of the eye; (b) detecting a resonant Raman spectrum corresponding to the selected illuminated region of the eye; and (c) identifying the presence, absence and/or the concentration of the selected analyte in the subject based on said detecting step. The apparatus may also be configured to be able to obtain biometric data of the eye to identify (confirm the identity of) the subject.

Lambert, James L.↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Highly Stable Fe/Co-TPY-MIL-88(NH 2 ) Metal–Organic Framework (MOF) in Enzymatic Cascade Reactions for Chemiluminescence-Based Detection of Extracellular Vesicles

Metal-Organic Frameworks (MOFs) can deliver many advantages when acting as enzyme mimics to assist with signal amplification in molecular detection: they have abundant active catalytic sites per unit volume of the material; their structures and elemental compositions are highly tunable, and their high specific surface area and porous property can assist with target separation and enrichment. In the present work, we have demonstrated that, by adding the pore partition agent, 2,4,6-tris(4-pyridyl)pyridine (TPY) during synthesis of the bimetallic Fe/Co-MIL-88(NH 2 ) MOF to block the open metal sites, a highly porous MOF of Fe/Co-TPY-MIL-88(NH 2 ) can be produced. This material also exhibits high stability in basic solutions and biofluids and possesses high peroxidase-mimicking activity, which can be utilized to produce long-lasting chemiluminescence (CL) from luminol and H 2 O 2 . Moreover, acting as the peroxidase-mimic, the Fe/Co-TPY-MIL-88(NH 2 ) MOF can form the enzymatic cascade with glucose oxidase (GOx) for biomarker detection. Further, when applied to detect extracellular vesicles (EVs), the MOF material and GOx are brought to the proximity on the EVs through two surface proteins, which triggers the enzyme cascade to produce high CL from glucose and luminol. EVs within the concentration range of 5 × 10 5 - 4 ×10 7 particles/mL can be detected, and the method can be used to analyze EV contents in human serum without sample preparation and EV purification. Overall, our work demonstrates that the high versatility and tunability of the MOF structures could bring in significant benefits to biosensing and enable ultrasensitive detection of biomarkers with judicious material designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Geometrical and chemical effects on the electrochemistry of single-wall carbon nanotube (SWCNT) network electrodes

Single-wall carbon nanotube (SWCNT) network is a promising electrode material for bio detection. Unfortunately, the associations between their physical as well as chemical properties and observed electrochemical performance are not known. This hinders any systematic optimization of the network properties towards specific analytes. Here we present a consistent physicochemical and electrochemical characterization of differently treated SWCNT networks. The results unambiguously show that (i) even if the electrochemical properties of different electrodes are practically identical when assessed by surface insensitive outer sphere redox (OSR) probes their behavior with inner sphere redox (ISR) probes can be drastically different. Further, (ii) the choice of the modification method (structural, chemical, electrochemical) heavily depends on nature of the target analyte, which are typically ISR probes. Although, (iii) chemical changes in the carbon phase appeared to be minor, effects of different treatments on oxidation states of Fe appeared to have a strong effect on the electrochemical performance of the networks in the case of ISR probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Passive microwave measurements of temperature and salinity in coastal zones

Experimental methods and results from the maritime remote sensing (MARSEN) experiments using dual frequency microwave radiometer detecting systems on board aircraft are described. The radiometers were operated at 1.43 and 2.65 GHz and flown above U.S. Atlantic coastal areas, Chesapeake Bay, around Puerto Rico, and over the German Bight. The advanced switched radiometers used were configured to be independent of gain variations and errors originating from front-end losses and determined the absolute brightness temperatures to within a few tenths Kelvin. Corrections to the observed brightness temperature of the ocean are analytically defined, including accounts made for roughness, the cosmic background radiation, and the solar radio source. The coastal flight data for salinity gradients and surface temperatures were compared with sea truth measured from ships and found to be accurate to within 1 C and 1 pph.

Blume, H.-J. C.↗
NASA NTRS1984

Electrical self-calibration of nonideal bolometers

An analytical method for determining the absorbed energy calibration of an IR bolometer from purely electrical measurements is presented. The technique is targeted at detectors with purely electrical nonlinearities. It is shown that the responsivity can be derived from the I-V plot if the limiting high-frequency impedance is measured. The electrical nonlinearity is then the difference between the impedance and the dc resistance. The model is used for designing a circuit for measuring the relative impedance parameters. The results are applicable to studies of IR sources and the detection of energy pulses with bolometers.

Mather, J. C.↗
DOE OSTI2021

A New Approach to Fundamental Mechanism Discovery in Polymer Upcycling

We present a new experimental methodology for detailed experimental investigations of depolymerization reactions over solid catalysts. This project aims to address a critical need in fundamental research on chemical upcycling of polymers – the lack of rapid, sensitive, isomerselective probing techniques for the detection of reaction intermediates and products. Our method combines a heterogeneous catalysis reactor for the study of multiphase (gas/polymer melt/solid) systems, coupled to a vacuum UV photoionization time-of-flight mass spectrometer. This apparatus draws on our expertise in probing complex gas-phase chemistry and enables highthroughput, detailed chemical speciation measurements of the gas phase above the catalyst, providing valuable information on the heterogeneous catalytic reactions. Using this approach, we investigated the depolymerization of high-density polyethylene (HDPE) over Ir-doped zeolite catalysts. We showed that the product distribution was dominated by low-molecular weight alkenes with terminal C=C double bonds and revealed the presence of many methyl-substituted alkenes and alkanes, suggesting extensive methyl radical chemistry. In addition, we investigated the fundamental reactivity of model oligomer molecules n-butane and isobutane over ZSM-5 zeolites. We demonstrated the first direct detection of methyl radical intermediates, confirming the key role of methyl in zeolite-catalyzed activation of alkanes. Our results show the potential of this experimental method to achieve deep insight into the complex depolymerization reactions and pave the way for detailed mechanistic studies, leading to increased fundamental understanding of key processes in chemical upcycling of polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Application of reversal electron attachment for ultrasensitive detection of thermal electron-attaching molecules - CCl4 and C6H5O2

A standard gas-dilution method was used to determine the selective response of the reversal electron attachment detector to carbon tetrachloride concentrations in nitrogen. Data are provided that determine the lowest concentration of sample detectable with the present instrumental configuration as being below 1.0 part per trillion by volume. The incorporation of a 90-deg electrostatic deflector with the quadrupole mass spectrometer is shown to be vital, and with it, negative-ion quadrupole mass spectrometry is used to characterize the ionization process. Observations are also made of the reversal electron attachment response to nitrobenzene. The analytical potential of reversal electron capture negative-ion mass spectrometry is examined, and areas for future development are discussed.

Bernius, Mark T.↗
DOE OSTI2024

Electrothermal vaporization as a new method for pre-inspection check samples

The use of electrothermal vaporization (ETV) has not been readily applied to nuclear safeguards or pre inspection check (PIC) sample analysis, even though the technique is ideally suited for low level (pg) isotopic quantification due to its high analyte transport efficiency. Here demonstrate the ETV method for PIC safeguard analysis. The ETV system is an automated, commercial of the shelf (COTS) technology, with the capability to introduce solid samples to a mass spectrometer platform. The system has been shown to simultaneously determine uranium assay, and the major isotopic ratios for uranium and plutonium. The ETV unit has demonstrated analysis up to 50 samples a day autonomously. The utilization of this ETV methodology provide a secondary option to the current PIC analysis and offers high throughput, enhanced sensitivity, and broader isotopic detection platform.

Hexel, Cole↗
DOE OSTI2025

A scalable and autoclavable oxygen nanosensor platform for metabolic monitoring of Saccharomyces cerevisiae in a bioreactor and other in situ systems

Polymer-encapsulated dye nanoparticle sensors are a valuable approach to achieving in situ analyte measurements with luminescence; however, typical emulsion-based nanosensors are poorly suited for large-scale biological samples due to limitations of synthesis scalability and stability. Branched polyethylenimine (PEI) is a versatile polymer scaffold ideal for constructing nanoparticles with various covalently conjugated moieties due to their high density of reactive primary amines, high water solubility, and biological stability. In this work, we used branched polyethylenimine as a scaffold-based approach for making a stable and scalable ratiometric oxygen sensor. Pt (II) tetracarboxyporphine was used as an oxygen-sensing dye and coumarin 343 as a reference dye, all covalently linked to the PEI scaffold producing a product that could withstand sterilization procedures and easily be scaled. To minimize toxicity from the PEI scaffold, we conjugated it with 2000 MW PEG. The applicability of the sensors was demonstrated in a 200 mL Saccharomyces cerevisiae yeast culture, using orthogonal luminescent and electrochemical oxygen measurements to validate sensor response and measure the metabolic activity of the yeast in our culture. Further, this approach was able to match the sensitivity of our electrochemical measurements while improving upon drawbacks of other luminescent methods of oxygen detection, demonstrating effective monitoring for at least 20 h. Our scaffold-based approach is a modular and easily translatable technology that could be useful in various biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Probing individual single atom electrocatalyst sites by advanced analytical scanning transmission electron microscopy

Single atom electrocatalysts (SAEs) are promising next-generation materials for promoting a variety of important reactions, such as the oxygen reduction, nitrogen reduction, and CO 2 reduction reactions. While bulk characterization techniques such as X-ray absorption spectroscopy and Mössbauer spectroscopy have significantly enhanced our understanding of these catalysts, direct probing of individual single metal atom sites at the atomic scale is necessary to understand local variations in the properties of these sites and accelerate design and synthesis of improved SAEs. Aberration-corrected scanning transmission electron microscopy (STEM) has become a powerful tool for providing this type of atomic-scale information about SAE metal sites. These sites are typically unstable under the electron beam, however, which, in combination with conventional acquisition methods and detectors, has limited the type and quantity of information obtainable by spectroscopic STEM techniques. Here, we map multiple individual SAE metal sites in a nitrogen-doped carbon containing atomically dispersed Fe and Re (FeReNC) at the atomic scale by direct electron detection electron energy-loss spectroscopy (EELS). Direct electron detection provides an improved signal-to-noise ratio over conventional scintillator-based detectors and enables detection and real space localization of weak signals. In addition, we demonstrate an automated method for identification of metal atom positions, placement of the probe on these sites, and simultaneous EELS and energy dispersive X-ray spectroscopic (EDS) signal acquisition. This simultaneous acquisition of EELS and EDS provides access to the composition and bonding of a wide range of SAE metal sites. In this study, focusing the probe directly on the metal sites also increases the relevant data acquisition rate by more than an order of magnitude over two-dimensional mapping, enabling improved statistical measurements of site properties. The versatility, sensitivity, and speed that these techniques provide enhances our ability to probe the local elemental and chemical environment of a large number of individual SAE metal site structures at the atomic scale, enabling an improved understanding of the variations in the local properties of these electrocatalysts to be gained. As a result, significantly increased information about individual metal sites will be available to future electrochemical studies through these techniques, accelerating the development of advanced SAEs.

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

Ring Formation in Protoplanetary Disks Driven by an Eccentric Instability

We find that, under certain conditions, protoplanetary disks may spontaneously generate multiple, concentric gas rings without an embedded planet through an eccentric cooling instability. Using both linear theory and nonlinear hydrodynamics simulations, we show that a variety of background states may trap a slowly processing, one-armed spiral mode that becomes unstable when a gravitationally stable disk rapidly cools. The angular momentum required to excite this spiral comes at the expense of nonuniform mass transport that generically results in multiple rings. For example, one long-term hydrodynamics simulation exhibits four long-lived, axisymmetric gas rings. We verify the instability evolution and ring-formation mechanism from first principles with our linear theory, which shows remarkable agreement with the simulation results. Dust trapped in these rings may produce observable features consistent with observed disks. Additionally, direct detection of the eccentric gas motions may be possible when the instability saturates, and any residual eccentricity left over in the rings at later times may also provide direct observational evidence of this mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗