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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
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 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↗
DOE OSTI2016

Chloromethane to olefins over H-SAPO-34: Probing the hydrocarbon pool mechanism

In this paper, by means of in situ FTIR and ex situ 13 C NMR studies, the initial periods of the chloromethane-to-olefins (CTO) reaction over SAPO-34 were probed in order to investigate the activation period of the reaction and to elucidate the formation of the catalyst active site. A methylated benzene species has been observed to form during the initial activation period of the reaction, and a direct positive correlation was constructed between the formation of this species and the catalytic activity. The data thus indicate that these methylated benzene species contribute to the formation of active sites within SAPO-34 for the CTO reaction. This is the first known report identifying a direct semi-quantitative correlation between the catalyst activity and growth of a methylated benzene active species, during the activation period of the chloromethane to olefins reaction. Finally, the findings here in correspond well to those reported for the methanol to olefins reaction, suggesting that a similar ‘hydrocarbon pool’ mechanism may be responsible for the formation of light olefins in CTO chemistry as well.

13C NMR↗
DOE OSTI2012

The RCSB Protein Data Bank: new resources for research and education

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher’s PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Receptor-mediated dimerization of JAK2 FERM domains is required for JAK2 activation

Cytokines and interferons initiate intracellular signaling via receptor dimerization and activation of Janus kinases (JAKs). How JAKs structurally respond to changes in receptor conformation induced by ligand binding is not known. Here, we present two crystal structures of the human JAK2 FERM and SH2 domains bound to Leptin receptor (LEPR) and Erythropoietin receptor (EPOR), which identify a novel dimeric conformation for JAK2. This 2:2 JAK2/receptor dimer, observed in both structures, identifies a previously uncharacterized receptor interaction essential to dimer formation that is mediated by a membrane-proximal peptide motif called the ‘switch’ region. Mutation of the receptor switch region disrupts STAT phosphorylation but does not affect JAK2 binding, indicating that receptor-mediated formation of the JAK2 FERM dimer is required for kinase activation. These data uncover the structural and molecular basis for how a cytokine-bound active receptor dimer brings together two JAK2 molecules to stimulate JAK2 kinase activity.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2020

A dynamic interaction between CD19 and the tetraspanin CD81 controls B cell co-receptor trafficking

CD81 and its binding partner CD19 are core subunits of the B cell co-receptor complex. While CD19 belongs to the extensively studied Ig superfamily, CD81 belongs to a poorly understood family of four-pass transmembrane proteins called tetraspanins. Tetraspanins play important physiological roles by controlling protein trafficking and other processes. Here, we show that CD81 relies on its ectodomain to traffic CD19 to the cell surface. Moreover, the anti-CD81 antibody 5A6, which binds selectively to activated B cells, recognizes a conformational epitope on CD81 that is masked when CD81 is bound to CD19. Mutations of CD81 in this interface suppress its CD19 export activity. These data indicate that the CD81 - CD19 interaction is dynamically regulated upon B cell activation and this dynamism can be exploited to regulate B cell function. These results are not only valuable for understanding B cell biology, but also have important implications for understanding tetraspanin function generally.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

INTERFUEL / FedFleet: FAST Status Update [PowerPoint]

This presentation presents a brief overview of the current status of the Federal Automotive Statistical Tool (FAST), a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles. The presentation covers current status and in-progress data collection activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Thermodynamic Properties of Magnesium-Boron Binary Alloys Determined Using Solid-State Electrochemical Measurements

This study provides the thermodynamic properties of the Mg-B binary alloys. Experiments were performed to measure the electromotive force (emf) as a function of temperature (773 K to 873 K) using a solid-state electrochemical cells that can be represented as (−)Pt,Ar/{Mg+CaF_2⋅MgF_2}∥CaF{sub 2}∥{Mg(alloy)+CaF_2⋅MgF_2}/Ar,Pt(+)The activities of Mg in Mg-B alloys were calculated from the experimental emf data. The activity coefficients of Mg in Mg-B alloys were also determined. The integral Gibbs energies of formation (∆G{sub f}{sup °}) of alloys were calculated from the activities of the Mg using tangent rule. The integral Gibbs energies of formation (∆G{sub f}{sup °}) of MgB{sub 2}, MgB{sub 4}, and MgB{sub 7} are − 15.48, − 22.03, and − 15.89 kJ/mol-atoms at 873 K.

36 MATERIALS SCIENCE↗
DOE OSTI2013

A cluster expansion model for predicting activation barrier of atomic processes

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.

97 MATHEMATICS AND COMPUTING↗