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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Demonstration of thermal limit mean transverse energy from cesium antimonide photocathodes

The mean transverse energy (MTE) of electrons emitted from cathodes is a critical parameter that determines the brightness of electron beams for applications, such as x-ray free electron lasers, particle colliders, and ultrafast electron scattering experiments. Achieving a MTE close to the thermal limit is a key step toward realizing the full potential of electron sources in these applications. Cesium antimonide (Cs 3 Sb) is a technologically important material with a long history of use in photon detection and electron sources. The smallest MTE of electrons photoemitted from Cs 3 Sb has always been appreciably greater than the thermal limit and was attributed to surface non-uniformities. In this work, we present comprehensive measurements of the photoemission electron energy spectra (PEES), quantum efficiency, and MTE from Cs 3 Sb in a wide photoexcitation energy range from 1.5 to 2.3 eV. Our PEES measurements demonstrate a notably low photoemission threshold of around 1.5 eV, which is in contrast with the previously perceived threshold of 1.8–2.0 eV. Moreover, we show that the MTE at this threshold of 1.5 eV nearly converges to the thermal limit at 300 K. At 1.8 eV, the MTE measured is 40 meV, which is comparable to the previously reported value. Here, we conclude that this MTE value at 1.8 eV photon energy is not due to surface roughness effects as previously believed, but is a direct consequence of the excess energy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Modeling backgrounds for the majorana demonstrator

The MAJORANA DEMONSTRATOR is a neutrinoless double-beta decay (0?ß ß ) experiment containing ~30 kg of p-type point contact germanium detectors enriched to 88% in 76Ge and ~14 kg of natural germanium detectors. The detectors are housed in two electroformed copper cryostats and surrounded by a graded passive shield with active muon veto. An extensive radioassay campaign was performed prior to installation to insure the use of ultra-clean materials. The DEMONSTRATOR achieved one of the lowest background rates in the region of the 0?ß ß Q-value, 15.7 ± 1.4 cts/(FWHM t y) from the low-background configuration spanning most of the 64.5 kg-yr active exposure. Nevertheless this background rate is a factor of five higher than the projected background rate. This discrepancy arises from an excess of events from the 232Th decay chain. Background model fits aim to understand this deviation from assay-based projections, potentially determine the source(s) of observed backgrounds, and allow a precision measurement of the two-neutrino double-beta decay half-life. The fits agree with earlier simulation studies, which indicate the origin of the 232Th excess is not from a near-detector component and have informed design decisions for the next-generation LEGEND experiment. Recent findings have narrowed the suspected locations for the excess activity, motivating a final simulation and assay campaign to complete the background model.

Haufe, Christopher R.↗
DOE OSTI2023

Antibacterial and antioxidant activities of Streptomyces sp. strain FR7 isolated from forest soil

Abstract Actinomycetes produce secondary metabolites with many bioactivities such as antimicrobial, which can be useful as alternatives against resistant bacterial strains. Therefore, the screening of new habitats is likely to provide new strains with high potential. In this work, the antimicrobial capacity was used to select Streptomyces sp. strains isolated from Raf Raf forest (Tunisia). From the strain displaying higher activity, FR7, an ethyl acetate extract was prepared under optimized culturing conditions (10 days at 30°C in ISP2 medium with initial pH 8), showing significant antimicrobial activity against Micrococcus luteus and Staphylococcus aureus (MIC = 5 μg ml−1), and Listeria monocytogenes and Pseudomonas aeruginosa (MIC = 20 μg ml−1). The extract displayed strong DPPH radical scavenging activity (IC50 = 1.3 μg ml−1) and protection of yeast cells from H2O2-induced oxidative stress determined by flow cytometry with dichlorofluorescein diacetate. The crude extract showed the presence of polyketides, with methylsalicylic acid as moiety, a large and diverse group of secondary metabolites with a wide range of bioactivities, including antioxidant and antibacterial. Based on 16S RNA gene sequences, strain FR7 was identified as belonging to genus Streptomyces with high resemblance to S. iakyrus. Streptomyces sp. FR7 has great potential as a source of antibacterial and antioxidant metabolites.

Weslati, Imen↗
DOE OSTI2023

Modelling populations of kilonovae

Abstract The 2017 detection of a kilonova coincident with gravitational-wave emission has identified neutron star mergers as the major source of the heaviest elements and dramatically constrained alternative theories of gravity. Observing a population of such sources has the potential to transform cosmology, nuclear physics, and astrophysics. However, with only one confident multi-messenger detection currently available, modelling the diversity of signals expected from such a population requires improved theoretical understanding. In particular, models that are quick to evaluate and are calibrated with more detailed multi-physics simulations are needed to design observational strategies for kilonovae detection and to obtain rapid-response interpretations of new observations. We use grey-opacity models to construct populations of kilonovae, spanning ejecta parameters predicted by numerical simulations. Our modelling focuses on wavelengths relevant for upcoming optical surveys, such as the Rubin Observatory Legacy Survey of Space and Time (LSST). In these simulations, we implement heating rates that are based on nuclear reaction network calculations. We create a Gaussian-process emulator for kilonova grey opacities, calibrated with detailed radiative transfer simulations. Using recent fits to numerical relativity simulations, we predict how the ejecta parameters from binary neutron star (BNS) mergers shape the population of kilonovae, accounting for the viewing-angle dependence. Our simulated population of BNS mergers produce peak i-band absolute magnitudes of −20 ≤ Mi ≤ −11. A comparison with detailed radiative transfer calculations indicates that further improvements are needed to accurately reproduce spectral shapes over the full light curve evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Casimir Light in Dispersive Nanophotonics

Time-varying optical media, whose dielectric properties are actively modulated in time, introduce a host of novel effects in the classical propagation of light, and are of intense current interest. In the quantum domain, time-dependent media can be used to convert vacuum fluctuations (virtual photons) into pairs of real photons. Here, we refer to these processes broadly as “dynamical vacuum effects” (DVEs). Despite interest for their potential applications as sources of quantum light, DVEs are generally very weak, presenting many opportunities for enhancement through modern techniques in nanophotonics, such as using media which support excitations such as plasmon and phonon polaritons. Here, we present a theory of weakly modulated DVEs in arbitrary nanostructured, dispersive, and dissipative systems. A key element of our framework is the simultaneous incorporation of time-modulation and “dispersion” through time-translation-breaking linear response theory. As an example, we use our approach to propose a highly efficient scheme for generating entangled surface polaritons based on time-modulation of the optical phonon frequency of a polar insulator.

42 ENGINEERING↗
DOE OSTI2022

Wavelength Scaling of Widely-Tunable Terahertz Quantum-Cascade Metasurface Lasers

Terahertz (THz) external-cavity lasers based on quantum-cascade (QC) metasurfaces are emerging as widely-tunable, single-mode sources with the potential to cover the 1--6 THz range in discrete bands with milliwatt-level output power. By operating on an ultra-short cavity with a length on the order of the wavelength, the QC vertical-external-cavity surface-emitting-laser (VECSEL) architecture enables continuous, broadband tuning while producing high quality beam patterns and scalable power output. The methods and challenges for designing the metasurface at different frequencies are discussed. As the QC-VECSEL is scaled below 2 THz, the primary challenges are reduced gain from the QC active region, increased metasurface quality factor and its effect on tunable bandwidth, and larger power consumption due to a correspondingly scaled metasurface area. At frequencies above 4.5 THz, challenges arise from a reduced metasurface quality factor and the excess absorption that occurs from proximity to the Reststrahlen band. The results of four different devices — with center frequencies 1.8 THz, 2.8 THz, 3.5 THz, and 4.5 THz — are reported. Each device demonstrated at least 200 GHz of continuous single-mode tuning, with the largest being 650 GHz around 3.5 THz. The limitations of the tuning range are well modeled by a Fabry-Pérot cavity which accounts for the reflection phase of the metasurface and the effect of the metasurface quality factor on laser threshold. Lastly, the effect of different output couplers on device performance is studied, demonstrating a significant trade-off between the slope efficiency and tuning bandwidth.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Characterization of Noise in CMOS Ring Oscillators at Cryogenic Temperatures

Allan deviation provides a means to characterize the time-dependence of noise in oscillators and potentially identify the source characteristics. Measurements on a 130 nm, 7-stage ring oscillator show that the Allan deviation declines from 300 K to 150 K as expected, but surprisingly increases from 150 K to 11 K. At low temperatures, the measured Allan deviation can be well fit using a few random telegraph noise (RTN) sources over the range of a few kilohertz to a few gigahertz. Further, the RTN characteristics evolve to reveal an enhanced role in low-frequency noise at lower temperatures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Model-Free Probabilistic Forecasting of Nodal Voltages in Distribution Systems

As the penetration of distributed energy resources (DERs) into distribution systems increases, so does the interest in forecasting relevant system variables to help mitigate the associated challenges. One such challenge is the more frequent occurrence of excessive voltages in distribution systems with higher shares of DERs. Accurate and reliable estimates together with forecasts of system states (i.e., nodal voltages) will therefore play a key role in improving the utilization of these variable and uncertain sources while mitigating potential operational risks. Whilst recent literature has explored machine learning (ML) methods for voltage estimation and their extrapolation for a short-time period into the future, few have taken uncertainty quantification into account, and these methods have not yet been translated into operations. This paper discusses the advantages offered by probabilistic voltage forecasts and proposes a non-parametric Bayesian method suitable for forecasting nodal voltages at short-term time horizons while accounting for uncertainties in load and distributed photovoltaic (PV) generation. We demonstrate the value of the proposed Gaussian process (GP) model for a case study using historical forecasts and observation data.

distribution system↗
DOE OSTI2026

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗
DOE OSTI2021

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗
DOE OSTI2022

Synthesis of mesoporous silica using a mineral silica source

Abstract Mesoporous silica has been applied in catalysis, separations, and drug delivery. It has generally been made using organosilicon precursors such as tetraethyl orthosilicate. For sustainability, it is necessary to find readily accessible mineral sources for making mesoporous silica. In this work, we demonstrate the successful synthesis of mesoporous silica with 10 nm average pore size using the mineral forsterite (Mg 2 SiO 4 ) as a silica source, providing a potentially cheaper and more Earth‐friendly route to making technologically important porous silica materials. Pure forsterite was synthesized by a solid‐state chemistry route at 1000°C and underwent dissolution–reprecipitation in aqueous hydrochloric acid containing the soft template surfactant, Pluronic P123. Variations of initial reaction pH (−0.2 to 0.6), reaction time (12–24 h), reaction temperature (50 to 90°C), and silica precursor (forsterite and fumed silica) were performed. The mesoporous silica aged at 70°C for 24 h had the highest porosity, with a surface area of 735 m 2 /g and a pore volume of 1.4 ml/g, comparable to mesoporous silica made using conventional starting materials. This novel geomimetic synthesis route supports the possibility of analogous formation of structured (mesoporous or zeolitic) silica in nature under abiotic or prebiotic conditions.

Materials Science↗
DOE OSTI2025

RB-TnSeq elucidates dicarboxylic-acid-specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive data set of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly barcoded transposon sequencing (RB-TnSeq). We identified four β-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon source and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of β-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. In addition, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short-chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Ralstonia produced 0.56 ± 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastic wastes to products derived from tricarboxylic acid (TCA) cycle intermediates. IMPORTANCE: Upcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastic waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our data set is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

Pearson, Allison N↗
DOE OSTI2024

Bioproduction of cerium-bearing magnetite and application to improve carbon-black supported platinum catalysts

Biogeochemical processing of metals including the fabrication of novel nanomaterials from metal contaminated waste streams by microbial cells is an area of intense interest in the environmental sciences. Here we focus on the fate of Ce during the microbial reduction of a suite of Ce-bearing ferrihydrites with between 0.2 and 4.2 mol% Ce. Cerium K-edge X-ray absorption near edge structure (XANES) analyses showed that trivalent and tetravalent cerium co-existed, with a higher proportion of tetravalent cerium observed with increasing Ce-bearing of the ferrihydrite. The subsurface metal-reducing bacterium Geobacter sulfurreducens was used to bioreduce Ce-bearing ferrihydrite, and with 0.2 mol% and 0.5 mol% Ce, an Fe(II)-bearing mineral, magnetite (Fe(II)(III) 2 O 4 ), formed alongside a small amount of goethite (FeOOH). At higher Ce-doping (1.4 mol% and 4.2 mol%) Fe(III) bioreduction was inhibited and goethite dominated the final products. During microbial Fe(III) reduction Ce was not released to solution, suggesting Ce remained associated with the Fe minerals during redox cycling, even at high Ce loadings. In addition, Fe L 2,3 X-ray magnetic circular dichroism (XMCD) analyses suggested that Ce partially incorporated into the Fe(III) crystallographic sites in the magnetite. The use of Ce-bearing biomagnetite prepared in this study was tested for hydrogen fuel cell catalyst applications. Platinum/carbon black electrodes were fabricated, containing 10% biomagnetite with 0.2 mol% Ce in the catalyst. The addition of bioreduced Ce-magnetite improved the electrode durability when compared to a normal Pt/CB catalyst. Different concentrations of Ce can inhibit the bioreduction of Fe(III) minerals, resulting in the formation of different bioreduction products. Bioprocessing of Fe-minerals to form Ce-containing magnetite (potentially from waste sources) offers a sustainable route to the production of fuel cell catalysts with improved performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Single-pixel reconstructive mid-infrared micro-spectrometer

Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO 2 ). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF 2 ) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

NEWTS Integrated Dataset (version 1.0)

The National Energy Water Treatment and Speciation (NEWTS) Integrated Dataset v1.0 provides water researchers, community leaders, and regulators with a unified and standardized energy-related wastewater stream database. This resource is derived from 27 state and federal entities, and scientific publications, and contains more than 400,000 sample records, many of which also provide geospatial information. The dataset includes data for several different energy-related wastewater types including produced water, other oil and gas wastewaters, mine drainage, coal ash leachate, and power plant wastewater. The NEWTS Integrated Dataset was built to support environmentally prudent decision-making, explore treatment opportunities, and identify potential critical mineral sources. A subset of this novel resource is also featured on NETL NEWTS State-Level Database Dashboard. Additional data can be found in the NEWTS EDX Group and the NEWTS Federal Database Dashboard.

abandoned mine drainage↗
DOE OSTI2026

NEWTS Integrated Dataset (version 2.0)

The National Energy Water Treatment and Speciation (NEWTS) Integrated Dataset v2.0 provides water researchers, community leaders, regulators, and industry stakeholders with a unified and standardized energy-process wastewater chemistry database. This resource is derived from 39 state and federal entities, and scientific publications, and contains more than 700,000 sample records, many of which also provide geospatial information. The dataset includes chemistry data for several different energy-process wastewater types including produced water, other oil and gas wastewaters, mine drainage, coal ash leachate, power plant wastewater, and geothermal fluids. The NEWTS Integrated Dataset was built to support prudent decision-making, characterization of potential critical mineral sources, and modeling of treatment and valorization options. A subset of this novel resource is also featured on the NEWTS State-Level Database Dashboard. Additional data can be found in the NEWTS EDX Group and the NEWTS Federal Database Dashboard.

AMD↗
DOE OSTI2020

Field-Emission Electron Source Embedded in a Field-Enhanced Conduction-Cooled Superconducting RF Cavity

We present simulations and experimental progress toward the development of a high-current electron source with the potential to deliver high charge electron bunches at GHz-level repetition rates. To achieve these goals electrons are generated through field-emission and the cathode is immersed in a conduction-cooled superconducting 650-MHz RF cavity. The field-emitters consist of microscopic silicon pyramids and have a typical enhancement factor of about 500. To trigger field-emission, the peak field inside the RF cavity of about 6 MV/m is further enhanced by placing the field-emitters on the top of a superconducting Nb rod inserted in the RF cavity. So far, we cannot control the duration of the electron bunches which is of the order of RF period. Also, the present cryo-cooler power of about 2 W limits the beam current to microamp level.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Round 3 Update of Stress Testing Results for Organic Light-Emitting Diode Panels and Luminaires

Organic light-emitting diode (OLED) sources are a potential solid-state lighting technology for use in indoor lighting applications. Some of the advantages offered by OLEDs include thin profiles, low glare, diffuse lighting, and unique form factors. The U.S. Department of Energy (DOE) has released six technical reports focused on OLED technologies to provide information and analysis to the lighting industry. These reports include the evaluation of two different field deployment sites, a market analysis, a tear-down analysis, and two independent assessments of the performance of select commercially available OLED products. This report builds on earlier DOE efforts with OLED technology by updating information about previously benchmarked commercial OLED products. Specifically, this report provides updated findings about the robustness and reliability of commercial OLED products.

42 ENGINEERING↗