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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Charged particle detectors with active detector surface for partial energy deposition of the charged particles and related methods

A radiation detector is disclosed. The radiation detector comprises an active detector surface configured to generate charge carriers in response to charged particles associated with incident radiation. The active detector surface is further configured with a sufficient thickness for a partial energy deposition of the charged particles to occur and permit the charged particles to pass through the active detector surface. The radiation detector further comprises a plurality of voltage leads coupled to the active detector surface. The plurality of voltage leads is configured to couple to a voltage source to generate a voltage drop across the active detector surface and to separate the charge carriers into a plurality of electrons and holes for detection. The active detector surface may comprise one or more graphene layers. Timing data between active detector surfaces may be used to determine energy of the incident radiation. Other apparatuses and methods are disclosed herein.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Three dimensional low-mode areal-density non-uniformities in indirect-drive implosions at the National Ignition Facility

To achieve hotspot ignition, an inertial confinement fusion implosion must achieve high hotspot pressure that is inertially confined by a dense shell of DT fuel. This requires a symmetric implosion having high in-flight shell velocity and high areal density at stagnation. The size of the driver and scale of the capsule required can be minimized by maintaining a high efficiency of energy coupling from the imploding shell to the hotspot. Significant 3D low mode asymmetries, however, are commonly observed in indirect-drive implosions and reduce the coupling of shell kinetic energy to the hotspot. To better quantify the magnitudes and impacts of shell density asymmetries, we have developed new analysis techniques and analytic models [Hurricane et al., Phys. Plasmas 27(6), 062704 (2020)]. To build confidence in the underlying data, we have also developed an analytic neutron transport model to cross-compare two independent measurements of asymmetry, which shows excellent agreement across shots for mode-1 (ℓ = 1). This work also demonstrates that asymmetry can introduce potential sampling bias into down-scattered ratio measurements causing the solid-angle-average and uncertainty-weighted-average down-scattered ratios to differ significantly. Diagnosing asymmetries beyond mode-1 (ℓ > 1) presents significant challenges. Using new diagnostic instruments and analysis techniques, however, evidence of significant Legendre mode P2 (ℓ = 2, m = 0) and additional 3D asymmetries (ℓ > 1, m ≠ 0) are beginning to emerge from the high precision activation diagnostic data (real-time nuclear activation detectors) and down-scattered neutron imaging data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Weighted active space protocol for multireference machine-learned potentials

Multireference methods such as multiconfiguration pair-density functional theory accurately capture electronic correlation in systems with strong multiconfigurational character, but their cost precludes direct use in molecular dynamics. Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach. However, the sensitivity of multireference calculations to the choice of the active space complicates the consistent evaluation of energies and gradients across structurally diverse nuclear configurations. To overcome this limitation, we introduce the weighted active space protocol (WASP), a systematic approach to assign a consistent active space for a given system across uncorrelated configurations. By integrating WASP with MLPs and enhanced sampling techniques, we propose a data-efficient active learning cycle that enables the training of an MLP on multireference data. We demonstrated the approach on the TiC + -catalyzed C–H activation of methane, a reaction that poses challenges for Kohn–Sham density functional theory due to its significant multireference character. This framework enables accurate and efficient modeling of catalytic dynamics, establishing a paradigm for simulating complex reactive processes beyond the limits of conventional electronic-structure methods.

enhanced sampling↗
DOE OSTI2019

Formylglycine-generating enzyme binds substrate directly at a mononuclear Cu(I) center to initiate O 2 activation

The formylglycine-generating enzyme (FGE) is required for the posttranslational activation of type I sulfatases by oxidation of an active-site cysteine to C α -formylglycine. FGE has emerged as an enabling biotechnology tool due to the robust utility of the aldehyde product as a bioconjugation handle in recombinant proteins. Here, we show that Cu(I)–FGE is functional in O 2 activation and reveal a high-resolution X-ray crystal structure of FGE in complex with its catalytic copper cofactor. We establish that the copper atom is coordinated by two active-site cysteine residues in a nearly linear geometry, supporting and extending prior biochemical and structural data. The active cuprous FGE complex was interrogated directly by X-ray absorption spectroscopy. These data unambiguously establish the configuration of the resting enzyme metal center and, importantly, reveal the formation of a three-coordinate tris(thiolate) trigonal planar complex upon substrate binding as furthermore supported by density functional theory (DFT) calculations. Critically, inner-sphere substrate coordination turns on O 2 activation at the copper center. These collective results provide a detailed mechanistic framework for understanding why nature chose this structurally unique monocopper active site to catalyze oxidase chemistry for sulfatase activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Hydrogenase Activity of Mineral-Associated and Suspended Populations of Desulfovibrio desulfuricans Essex 6

The interactions between sulfate-reducing microorganisms and iron oxides influence a number of important redox-sensitive biogeochemical processes including the formation of iron sulfides. Enzymes, such as hydrogenase which catalyze the reversible oxidation of molecular hydrogen, are known to mediate electron transfer to metals and may contribute to the formation and speciation of ferrous sulfides formed at the cell–mineral interface. In the present study, we compared the whole cell hydrogenase activity of Desulfovibrio desulfuricans strain Essex 6 growing as biofilms on hematite (hematite-associated) or as suspended populations using different metabolic pathways. Hematite-associated cells exhibited significantly greater hydrogenase activity than suspended populations during sulfate respiration but not during pyruvate fermentation. The enhanced activity of the hematite-associated, sulfate-grown cells appears to be dependent on iron availability rather than a general response to surface attachment since the activity of glass-associated cells did not differ from that of suspended populations. Hydrogenase activity of pyruvate-fermenting cells was stimulated by addition of iron as soluble Fe(II)Cl2 and, in the absence of added iron, both sulfate-reducing and pyruvate-fermenting cells displayed similar rates of hydrogenase activity. These data suggest that iron exerts a stronger influence on whole cell hydrogenase activity than either metabolic pathway or mode of growth. The location of hydrogenase to the cell envelope and the enhanced activity at the hematite surface in sulfate-reducing cells may influence the redox conditions that control the species of iron sulfides on the mineral surface.

58 GEOSCIENCES↗
DOE OSTI2017

CACUL1/CAC1 attenuates p53 activity through PML post-translational modification

Promyelocytic leukaemia (PML) is a tumor suppressor protein covalently conjugated with SUMO family proteins, leading to the formation of PML nuclear bodies (NBs). PML-NBs provide a platform for efficient posttranslational modification of targets and protein-protein interaction, contributing to the adjustment of gene expression and chromatin integrity. Although PML SUMOylation is thought to play important roles in diverse cellular functions, the control mechanisms of adequate modification levels have remained unsolved. Here, we report that Cullin-related protein CACUL1/CAC1 (CACUL1) inhibits PML posttranslational modification. CACUL1 interacts with PML and suppresses PML SUMOylation, leading to the regulation of PML-NB size in the nucleus. We also found that Ubc9, a SUMO-conjugating enzyme, binds to CACUL1 and antagonizes the interaction between CACUL1 and PML. Furthermore, CACUL1 attenuates p53 transcriptional activity. These data suggest that CACUL1 is a novel regulator that negatively controls p53 activity through the regulation of PML SUMOylation. - Highlights: • CACUL1 suppresses PML SUMOylation. • CACUL1 regulates PML-NBs size. • CACUL1 attenuates p53 transcriptional activity.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Statistical change detection of building energy consumption: Applications to savings estimation

The surge in interval meter data availability and associated activity in energy data analytics has inspired new interest in advanced methods for building efficiency savings estimation. Statistical and machine learning approaches are being explored to improve the energy baseline models used to measure and verify savings. One outstanding challenge is the ability to identify and account for operational changes that may confound savings estimates. In the measurement and verification (M&V) context, ‘non-routine events’ (NREs) cause changes in building energy use that are not attributable to installed efficiency measures, and not accounted for in the baseline model’s independent variables. In the M&V process NREs must be accounted for as ‘adjustments’ to appropriately attribute the estimated energy savings to the specific efficiency interventions that were implemented. Currently this is a manual and custom process, conducted using professional judgment and engineering expertise. As such it remains a barrier in scaling and standardizing meter-based savings estimation. Here in this work, a data driven methodology was developed to (partially) automate, and therefore streamline the process of detecting NREs in the post-retrofit period and making associated savings adjustments. The proposed NRE detection algorithm is based on a statistical change point detection method and a dissimilarity metric. The dissimilarity metric measures the proximity between the actual time series of the post-retrofit energy consumption and the projected baseline, which is generated using a statistical baseline model. The suggested approach for NRE adjustment involves the NRE detection algorithm, the M&V practitioner, and a regression modeling algorithm. The performance of the detection and adjustment algorithm was evaluated using a simulation-generated test data set, and two benchmark algorithms. Results show a high true positive detection rate (75%-100% across the test cases), higher than ideal false positive detection rates (20%-70%), and low errors in energy adjustment (<0.7%). These results indicate that the algorithm holds for helping M&V practitioners to streamline the process of handling NREs. Moreover, the change point algorithm and underlying statistical principles could prove valuable for other building analytics applications such as anomaly detection and fault diagnostics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Investigation of optical and electrical properties of amorphous Se{sub 95−x}S{sub x}Zn{sub 5}(x=0.2, 2, 5 and 10) thin films

In this study, we reported that the optical and electrical analysis of amorphous Se{sub 90-x}S{sub x}Zn{sub 5} (x=0.2, 2, 5, 10) thin films. Bulk samples of the investigated material were prepared by melt quenching technique. Thin films of ~ 300nm thickness were deposited on cleaned glass substrates by thermal evaporation technique. The morphological study of the investigated material in powder form carried out by scanning electron microscopy (SEM) confirms the disorder of the material increases at lower sulfur doping (up to 5%) whereas at higher (S) doping (10%) the defects of the material decreases. The optical parameters were estimated from optical absorption spectra data measured from UV-Vis-spectrophotometer in the wavelength range 200-900 nm. It was found that the value of optical band gap (E{sub g}) of the investigated thin films decreases up to lower S doping and increases at higher (S) doping. The other optical parameters such as absorption coefficient (α) and extinction coefficient (K) increases up to lower S doping and decreases at higher S doping. This remarkable change in the values of optical parameters was interpreted on the basis of model proposed by Davis and Mott. Electrical parameters of the investigated thin films were carried out in the temperature range 309-370 K. Analysis of data shows activation energy decreases with the increase of concentration of (S) increases up to 5% and at 10% it increases again.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Arctic Sea Ice Classification Using Microwave Scatterometer and Radiometer Data During 2002-2017

Temporal and spatial variation of sea ice type in the Arctic is an indicator of regional and global change. Arctic sea ice can be classified into two major categories: multiyear ice (MYI) and first-year ice. In this paper, classification method based on machine learning is established and applied to produce daily sea ice classification data set during the winter (November–April) from 2002 to 2017 using active microwave data from QuikSCAT and Advanced Scatterometer as well as passive microwave data from Advanced Microwave Scanning Radiometer for EOS, Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2 radiometer. First, the open water area is flagged out using brightness temperature (Tb) from the passive microwave sensor. Then, K-means algorithm is applied to identify the clusters of the two ice types in the Tb/backscatter parameter space and finally assign pixels to each class. Two optimization methods based on the movement of MYI and marginal ice zone are used to correct the misclassification of MYI. The results have shown a decrease of MYI in winter from 2002 to 2017, especially in 2008 and 2013 with a remarkable recovery in 2014. The classifications are consistent with results by visual interpretation from synthetic aperture radar images in the Canadian Arctic Archipelago with overall classification accuracy over 93%. Comparison with classifications from previous studies and products shows that our method could reflect more differences in MYI declining trend interannually and less anomalous fluctuations in certain years.

58 GEOSCIENCES↗
DOE OSTI2024

Integrated Off-Gas System Tests on the DM1200 Melter with RPP-WTP LAW Sub-Envelope C1 Simulants (Final Report)

The report documents melter and off-gas performance results obtained on the DM1200 during processing of LAW Sub-Envelope Cl feed. The principal objectives of the DM1200 melter testing were to demonstrate suitable processing and production rates for LAW Cl feed; characterize the glass product for elemental composition, the presence of organic compounds, and TCLP response for metals; and measure destruction and removal efficiencies (DREs) for organic compounds across the melter and off-gas treatment components. The feed was spiked with organic compounds for part of the testing duration. Data were collected for both process engineering needs and to support regulatory activities. The data needed for regulatory support were collected using EPA methods and independent data analyses and data checking were performed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Dynamically reassigning a connected node to a block of compute nodes for re-launching a failed job

Methods, systems, and products for dynamically reassigning a connected node to a block of compute nodes for re-launching a failed job that include: identifying that a job failed to execute on the block of compute nodes because connectivity failed between a compute node assigned as at least one of the connected nodes for the block of compute nodes and its supporting I/O node; and re-launching the job, including selecting an alternative connected node that is actively coupled for data communications with an active I/O node; and assigning the alternative connected node as the connected node for the block of compute nodes running the re-launched job.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Development of activity pencil beam algorithm using measured distribution data of positron emitter nuclei generated by proton irradiation of targets containing {sup 12}C, {sup 16}O, and {sup 40}Ca nuclei in preparation of clinical application

Purpose: The purpose of this study is to develop a new calculation algorithm that is satisfactory in terms of the requirements for both accuracy and calculation time for a simulation of imaging of the proton-irradiated volume in a patient body in clinical proton therapy. Methods: The activity pencil beam algorithm (APB algorithm), which is a new technique to apply the pencil beam algorithm generally used for proton dose calculations in proton therapy to the calculation of activity distributions, was developed as a calculation algorithm of the activity distributions formed by positron emitter nuclei generated from target nuclear fragment reactions. In the APB algorithm, activity distributions are calculated using an activity pencil beam kernel. In addition, the activity pencil beam kernel is constructed using measured activity distributions in the depth direction and calculations in the lateral direction. {sup 12}C, {sup 16}O, and {sup 40}Ca nuclei were determined as the major target nuclei that constitute a human body that are of relevance for calculation of activity distributions. In this study, ''virtual positron emitter nuclei'' was defined as the integral yield of various positron emitter nuclei generated from each target nucleus by target nuclear fragment reactions with irradiated proton beam. Compounds, namely, polyethylene, water (including some gelatin) and calcium oxide, which contain plenty of the target nuclei, were irradiated using a proton beam. In addition, depth activity distributions of virtual positron emitter nuclei generated in each compound from target nuclear fragment reactions were measured using a beam ON-LINE PET system mounted a rotating gantry port (BOLPs-RGp). The measured activity distributions depend on depth or, in other words, energy. The irradiated proton beam energies were 138, 179, and 223 MeV, and measurement time was about 5 h until the measured activity reached the background level. Furthermore, the activity pencil beam data were made using the activity pencil beam kernel, which was composed of the measured depth data and the lateral data including multiple Coulomb scattering approximated by the Gaussian function, and were used for calculating activity distributions. Results: The data of measured depth activity distributions for every target nucleus by proton beam energy were obtained using BOLPs-RGp. The form of the depth activity distribution was verified, and the data were made in consideration of the time-dependent change of the form. Time dependence of an activity distribution form could be represented by two half-lives. Gaussian form of the lateral distribution of the activity pencil beam kernel was decided by the effect of multiple Coulomb scattering. Thus, the data of activity pencil beam involving time dependence could be obtained in this study. Conclusions: The simulation of imaging of the proton-irradiated volume in a patient body using target nuclear fragment reactions was feasible with the developed APB algorithm taking time dependence into account. With the use of the APB algorithm, it was suggested that a system of simulation of activity distributions that has levels of both accuracy and calculation time appropriate for clinical use can be constructed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Incorporating polar field data for improved solar flare prediction

In this paper, we consider incorporating data associated with the sun’s north and south polar field strengths to improve solar flare prediction performance using machine learning models. When used to supplement local data from active regions on the photospheric magnetic field of the sun, the polar field data provides global information to the predictor. While such global features have been previously proposed for predicting the next solar cycle’s intensity, in this paper we propose using them to help classify individual solar flares. We conduct experiments using HMI data employing four different machine learning algorithms that can exploit polar field information. Additionally, we propose a novel probabilistic mixture of experts model that can simply and effectively incorporate polar field data and provide on-par prediction performance with state-of-the-art solar flare prediction algorithms such as the Recurrent Neural Network (RNN). Our experimental results indicate the usefulness of the polar field data for solar flare prediction, which can improve Heidke Skill Score (HSS2) by as much as 10.1%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Detailed Statistical Models of Host-Based Data for Detection of Malicious Activity

The cybersecurity research community has focused primarily on the analysis and automation of intrusion detection systems by examining network traffic behaviors. Expanding on this expertise, advanced cyber defense analysis is turning to host-based data to use in research and development to produce the next generation network defense tools. The ability to perform deep packet inspection of network traffic is increasingly harder with most boundary network traffic moving to HTTPS. Additionally, network data alone does not provide a full picture of end-to-end activity. These are some of the reasons that necessitate looking at other data sources such as host data. We outline our investigation into the processing, formatting, and storing of the data along with the preliminary results from our exploratory data analysis. In writing this report, it is our goal to aid in guiding future research by providing foundational understanding for an area of cybersecurity that is rich with a variety of complex, categorical, and sparse data, with a strong human influence component. Including suggestions for guiding potential directions for future research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Moisture Monitoring at Area G, Technical Area 54, Los Alamos National Laboratory

Hydrological characterization and moisture monitoring activities provide data required for evaluating the transport of subsurface contaminants in the unsaturated and saturated zones beneath Area G, and for the Area G Performance Assessment and Composite Analysis. These activities have been ongoing at Area G, Technical Area 54 of the Los Alamos National Laboratory since waste disposal operations began in 1957. This report summarizes the hydrological characterization and moisture monitoring activities conducted at Area G. It includes moisture monitoring data collected from 1986 through 2014 from numerous boreholes and access tubes with neutron moisture meters, as well as data collected by automated dataloggers for water content measurement sensors installed in a waste disposal pit cover, and buried beneath the floor of a waste disposal pit. This report is an update of the Jennings and French (2009) moisture monitoring report and includes all data from Jennings and French (2009) and the Draft 2010 Addendum moisture monitoring report (Jennings and French, 2010). For this updated report, all neutron logging data, including neutron probe calibrations, were investigated for quality and pedigree. Some data have been recalculated using more defensible calibration data. Therefore, some water content profiles are different from those in the Jennings and French (2009) report. Monitoring and characterization data generally indicate that some areas of the Area G vadose zone are consistent with undisturbed conditions, with water contents of less than five percent by volume in the top two layers of the Bandelier tuff at Area G. These data also indicate that other areas of the vadose zone are affected by waste disposal activities that have been ongoing at Area G since 1957, a period of nearly 60 years. In some areas, water content profiles indicate increases in water content to depths of tens of meters, especially in areas covered by asphalt and structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Moisture Monitoring at Area G, Technical Area 54, Los Alamos National Laboratory, 2016 Status Report

Hydrological characterization and moisture monitoring activities provide data required for evaluating the transport of subsurface contaminants in the unsaturated and saturated zones beneath Area G, and for the Area G Performance Assessment and Composite Analysis. These activities have been ongoing at Area G, Technical Area 54 of the Los Alamos National Laboratory since waste disposal operations began in 1957. This report summarizes the hydrological characterization and moisture monitoring activities conducted at Area G. It includes moisture monitoring data collected from 1986 through 2016 from numerous boreholes and access tubes with neutron moisture meters, as well as data collected by automated dataloggers for water content measurement sensors installed in a waste disposal pit cover, and buried beneath the floor of a waste disposal pit. This report is an update of a nearly identical report by Levitt et al., (2015) that summarized data collected through early 2015; this report includes additional moisture monitoring data collected at Pit 31 and the Pit 38 extension through December, 2016. It also includes information from the Jennings and French (2009) moisture monitoring report and includes all data from Jennings and French (2009) and the Draft 2010 Addendum moisture monitoring report (Jennings and French, 2010). For the 2015 version of this report, all neutron logging data, including neutron probe calibrations, were investigated for quality and pedigree. Some data were recalculated using more defensible calibration data. Therefore, some water content profiles are different from those in the Jennings and French (2009) report. All of that information is repeated in this report for completeness. Monitoring and characterization data generally indicate that some areas of the Area G vadose zone are consistent with undisturbed conditions, with water contents of less than five percent by volume in the top two layers of the Bandelier tuff at Area G. These data also indicate that other areas of the vadose zone are affected by waste disposal activities that have been ongoing at Area G since 1957, a period of nearly 60 years. In some areas, water content profiles indicate increases in water content to depths of tens of meters, especially in areas covered by asphalt and structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗