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At least 1,747 records · Page 97

A study on dependence of the structural, optical and electrical properties of cadmium lead sulphide thin films on Cd/Pb ratio

Cadmium Lead Sulphide thin films with systematic variation in Cd/Pb ratio are prepared at 333K by CBD, adjusting the reagent-molarity, deposition time and pH. XRD exhibits crystalline-amorphous transition as Cd% exceeds Pb%. AFM shows agglomeration of crystallites of size ∼50±5 nm. EDAX assess the composition whereas XPS ascertains the ternary formation, with binding energies of Pb4f{sub 7/2} and 4f{sub 5/2}, Cd3d{sub 5/2} and 3d{sub 3/2} and S2p at 137.03, 141.606, 404.667, 412.133 and 160.218 eV respectively. The optical absorption spectra reveal the variance in the direct allowed band gaps, from 1.57eV to 2.42 eV as Cd/Pb ratio increases from 0.2 to 2.7, suggesting possibility of band gap engineering in the n-type films.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

OPTIMAL CORRELATION ESTIMATORS FOR QUANTIZED SIGNALS

Using a maximum-likelihood criterion, we derive optimal correlation strategies for signals with and without digitization. We assume that the signals are drawn from zero-mean Gaussian distributions, as is expected in radio-astronomical applications, and we present correlation estimators both with and without a priori knowledge of the signal variances. We demonstrate that traditional estimators of correlation, which rely on averaging products, exhibit large and paradoxical noise when the correlation is strong. However, we also show that these estimators are fully optimal in the limit of vanishing correlation. We calculate the bias and noise in each of these estimators and discuss their suitability for implementation in modern digital correlators.

79 ASTRONOMY AND ASTROPHYSICS↗

Optical variability of AGNs in the PTF/iPTF survey

We characterize the optical variability of quasars in the Palomar Transient Factory and intermediate Palomar Transient Factory (PTF/iPTF) surveys. We re-calibrate the r-band light curves for ∼28,000 luminous, broad-line active galactic nuclei from the SDSS, producing a total of ∼2.4 million photometric data points. We utilize both the structure function (SF) and power spectrum density (PSD) formalisms to search for links between the optical variability and the physical parameters of the accreting supermassive black holes that power the quasars. The excess variance (SF{sup 2}) of the quasar sample tends to zero at very short time separations, validating our re-calibration of the time-series data. We find that the the amplitude of variability at a given time-interval, or equivalently the timescale of variability to reach a certain amplitude, is most strongly correlated with luminosity with weak or no dependence on black hole mass and redshift. For a variability level of SF(τ) = 0.07 mag, the timescale has a dependency of τ∝L{sup 0.4}. This is broadly consistent with the expectation from a simple Keplerian accretion disk model, which provides τ∝L{sup 0.5}. The PSD analysis also reveals that many quasar light curves are steeper than a damped random walk. We find a correlation between the steepness of the PSD slopes, specifically the fraction of slopes steeper than 2.5, and black hole mass, although we cannot exclude the possibility that luminosity or Eddington ratio are the drivers of this effect. This effect is also seen in the SF analysis of the (i)PTF data, and in a PSD analysis of quasars in the SDSS Stripe 82.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of Second Target Station Target Removal Dose Rates

The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.

Transmutation↗

On numerical turbulence generation for test-particle simulations

A modified method is presented to generate artificial magnetic turbulence that is used for test-particle simulations. Such turbulent fields are obtained from the superposition of a set of wave modes with random polarizations and random directions of propagation. First, it is shown that the new method simultaneously fulfils requirements of isotropy, equal mean amplitude and variance for all field components, and vanishing divergence. Second, the number of wave modes required for a stochastic particle behavior is investigated by using a Lyapunov approach. For the special case of slab turbulence, it is shown that already for 16 wave modes the particle behavior agrees with that shown for considerably larger numbers of wave modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Improved Parametric Models for Explosion Pressure Signals Derived From Large Datasets

Accurate recording and characterization of explosion-induced pressure signals are key components of the forensic analysis of explosion events in the atmosphere. Parametric overpressure models based on several key waveform features (peak overpressure, positive pulse duration, and impulse) are widely used to estimate explosion energy in terms of trinitrotoluene equivalent yield. However, those models are often developed by a limited dataset, including only a few events or recordings at relatively short propagation distances. Here, we develop empirical waveform-parameter models based on a regression analysis of a large set of data curated from four chemical explosion experiments including 16 detonations. We measured peak overpressure and impulse for positive and negative phases from 1000 pressure signals recorded at local ranges (<20 km) with scaled distance up to 8000 m/kg 1/3 . Additionally, the measured waveform parameters showed large variation with respect to observing distances indicating the effects of atmospheric propagation. In this study, a second-order polynomial model was used in a least-squares regression to account for those propagation effects and to improve data fitting. In addition to model parameters for waveform features, we also determined range-dependent model uncertainties based on data variance. The model uncertainty represents the prediction error of our models and can be critical to evaluating the uncertainty of yield estimate.

58 GEOSCIENCES↗

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing

Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 4 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in situ biology. Differences accumulating during an overnight rest (18 hours) would confound relevant biologic variance related to many underlying disease states.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization of Thermal Conductance at Interfaces Using Machine Learning Algorithms

We report optimization of thermal transport across the interface of two different materials is critical to micro-/nanoscale electronic, photonic, and phononic devices. Although several examples of compositional intermixing at the interfaces having a positive effect on interfacial thermal conductance (ITC) have been reported, an optimum arrangement has not yet been determined because of the large number of potential atomic configurations and the significant computational cost of evaluation. On the other hand, computation-driven materials design efforts are rising in popularity and importance. Yet, the scalability and transferability of machine learning models remain as challenges in creating a complete pipeline for the simulation and analysis of large molecular systems. In this work we present a scalable Bayesian optimization framework, which leverages dynamic spawning of jobs through the Message Passing Interface (MPI) to run multiple parallel molecular dynamics simulations within a parent MPI job to optimize heat transfer at the silicon and aluminum (Si/Al) interface. We found a maximum of 50% increase in the ITC when introducing a two-layer intermixed region that consists of a higher percentage of Si. Because of the random nature of the intermixing, the magnitude of increase in the ITC varies. We observed that both homogeneity/heterogeneity of the intermixing and the intrinsic stochastic nature of molecular dynamics simulations account for the variance in ITC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A chemical TROMPE-L’ŒIL: No iron spread in the globular clusteR M22

We present the analysis of high-resolution spectra obtained with UVES and UVES-FLAMES at the Very Large Telescope of 17 giants in the globular cluster (GC) M22, a stellar system suspected to have an intrinsic spread in iron abundance. We find that when surface gravities are derived spectroscopically (in order to obtain the same iron abundance from Fe i and Fe ii lines) the [Fe/H] distribution spans ∼0.5 dex, according to previous analyses. However, the gravities obtained in this way correspond to unrealistically low stellar masses (0.1–0.5 M{sub ⊙}) for most of the surveyed giants. Instead, when photometric gravities are adopted, the [Fe ii/H] distribution shows no evidence of spread, in variance with the [Fe i/H] distribution. This difference has been recently observed in other clusters and could be due to non-local thermodynamical equilibrium effects driven by over-ionization mechanisms that mainly affect the neutral species (thus providing lower [Fe i/H]), but leave [Fe ii/H] unaltered. We confirm that the s-process elements show significant star-to-star variations and their abundances appear to be correlated with the difference between [Fe i/H] and [Fe ii/H]. This puzzling finding suggests that the peculiar chemical composition of some cluster stars may be related to effects able to spuriously decrease [Fe i/H]. We conclude that M22 is a GC with no evidence of intrinsic iron spread, ruling out that it has retained the supernovae ejecta in its gravitational potential well.

79 ASTRONOMY AND ASTROPHYSICS↗

Tree cover shows strong sensitivity to precipitation variability across the global tropics

Abstract Aim Vegetation is sensitive to mean annual precipitation (MAP), but the sensitivity of vegetation to precipitation variability (PV) is less clear. Tropical ecosystems are likely to experience increased PV in the future. Here we assessed the importance, magnitude and mechanism of PV effects on tree cover in the context of covarying environmental drivers such as fire, temperature and soil properties. Location Tropical land. Time period 2000–2010. Major taxa studied Trees. Methods We compiled climate, soil and remotely‐sensed tree cover data over tropical land. We then comprehensively assessed the contribution of PV at different time‐scales to tropical tree cover variations and estimated the sensitivity of tree cover to PV changes by conducting rolling‐window regression and variance decomposition analyses. We further adopted a mechanistic modelling approach to test whether water competition between trees and grasses can explain the observed effect of PV. Results We find that PV contributes 33–56% to the total explained spatial variation (65–79%) in tree cover. The contribution of PV depends on MAP and is highest under intermediate MAP (500–1,500 mm). Tree cover generally increases with rainy day frequency and wet season length but shows mixed responses to inter‐annual PV. Based on the estimated sensitivity, tropical tree cover can decrease by 3–5% overall and by up to 20% in Amazonia under a 20% decrease in rainy days. Mechanistic modelling analysis reproduced the continental differences in tree cover along an MAP gradient. Main conclusions Under intermediate rainfall regimes (500–1,500 mm), PV can be a more important determinant of tropical tree cover than conventionally proposed drivers such as MAP and fire. The effect of PV likely results from the sensitivity of tree–grass competition to the temporal distribution of water resources. These results show that climate variability can strongly shape the biosphere.

Xu, Xiangtao↗

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mu*STAR ADSR Fuel Conversion Facility Evaluation and Cost Analysis

The purpose of the reported effort is the development of a conceptual process for conversion of used nuclear fuel (UNF) from light water reactors (LWRs) to a fluoride salt form to facilitate its use for power generation in a Mu*STAR Accelerator-driven Subcritical Reactor (ADSR). This document evaluates potential processes for converting UNF into a fluoride salt, evaluates the costs/benefits of using enriched lithium in the carrier salt, and analyzes comparable costs of similar facilities to make a rough order of magnitude estimate for the cost to design, construct, and commission a Mu*STAR ADSR fuel conversion facility. This document also makes a high-level comparison of the Mu*STAR ADSR fuel cycle with other important fuel cycles. The results of the cost analysis show that the Mu*STAR ADSR fuel conversion facility will cost more than $100M, possibly up to around $1B, to design and construct. The cost will depend on the size of the hot cell required, which will depend on the processing options chosen for converting the UNF to a molten salt. Operations and maintenance of the facility will be on the order of $10M per year. The design, fabrication, and installation of the remote process equipment to support the fuel conversion will be an additional cost of more than $50M. Cost surveys of Department of Energy hot cell designs and previous Department of Energy hot cell construction suggest that the cost variance may be large, and the risk of escalating costs may be high in the regulation-mandated atmosphere of nuclear facility design and construction. The molten salt for the Mu*STAR ADSR contains all of the nonvolatile isotopes in the UNF, and there is never a separation of the plutonium from the fission products. This makes this conversion process much more proliferation resistant than the reprocessing options used for other closed fuel cycles. When normalized to the amount of electricity produced, the Mu*STAR ADSR fuel cycle’s expected cost might be less than any reprocessing fuel cycle and possibly less than the once-through cycle now used. Simulations show that once the conversion to fluoride is made, that up to seven times as much energy can be extracted from the UNF than was produced by the LWR while making it [Bowman, 2010]. Using once-only, on-site conversion to fluoride means no mining, no enrichment, no manufacturing of fuel rods, and no transportation costs. Typically, the UNF was produced over a 40-year period in an LWR; it can potentially be used for 280 years in Mu*STAR, producing the same power as the LWR did, ultimately requiring disposal of approximately the same volume of material as the LWR generated. Mu*STAR burns most of the higher actinides, which could reduce both the cost of disposal and significantly reduce the longevity of its radiotoxicity. Mu*STAR ADSR’s ability to demonstrate unique and valuable peripheral benefits are additional arguments for this technology, including (1) turning UNF into a valuable commodity (thus, its disposal will not be such an immediate problem, so continued operation of existing LWRs will be more acceptable); (2) burning fissile or fertile fuel including excess weapons-grade plutonium in subcritical mode; and (3) providing high-temperature process heat to convert natural gas to synthetic diesel fuel, water to hydrogen, or for other process-heat applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance the technology-based treatment standard specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. In FY24, a list of the 132 reasonably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds spanning the identified properties were tested using sorption and leachate tests. These compounds were subject to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The tests have been completed and analysis is underway but as yet currently unavailable. The analytical results (and conclusions) will be included in a forthcoming revision to this report as soon as they are available

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

2006 NASA Range Safety Annual Report

Throughout 2006, Range Safety was involved in a number of exciting and challenging activities and events, from developing, implementing, and supporting Range Safety policies and procedures-such as the Space Shuttle Launch and Landing Plans, the Range Safety Variance Process, and the Expendable Launch Vehicle Safety Program procedures-to evaluating new technologies. Range Safety training development is almost complete with the last course scheduled to go on line in mid-2007. Range Safety representatives took part in a number of panels and councils, including the newly formed Launch Constellation Range Safety Panel, the Range Commanders Council and its subgroups, the Space Shuttle Range Safety Panel, and the unmanned aircraft systems working group. Space based range safety demonstration and certification (formerly STARS) and the autonomous flight safety system were successfully tested. The enhanced flight termination system will be tested in early 2007 and the joint advanced range safety system mission analysis software tool is nearing operational status. New technologies being evaluated included a processor for real-time compensation in long range imaging, automated range surveillance using radio interferometry, and a space based range command and telemetry processor. Next year holds great promise as we continue ensuring safety while pursuing our quest beyond the Moon to Mars.

TenHaken, Ron↗

Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate

The declared linear density of 238 U and 235 U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar - Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of 235 U (the response) in order to estimate model parameters of the nonlinear Parte equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This article compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. Here, we find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Jet classification using high-level features from anatomy of top jets

Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to less interpretable models, emphasizing the need to understand the decision-making process and to identify the high-level features (HLFs) crucial for explaining jet classification. To address this, we consider the top jet tagging problems and introduce an analysis model (AM) that analyzes selected HLFs designed to capture important features of top jets. Our AM mainly consists of the following three modules: a relation network analyzing two-point energy correlations, mathematical morphology and Minkowski functionals for generalizing jet constituent multiplicities, and a recursive neural network analyzing subjet constituent multiplicity to enhance sensitivity to subjet color charges. We demonstrate that our AM achieves performance comparable to the Particle Transformer (ParT) while requiring fewer computational resources in a comparison of top jet tagging using jets simulated at the hadronic calorimeter angular resolution scale. Furthermore, as a more constrained architecture than ParT, the AM exhibits smaller training uncertainties because of the bias-variance tradeoff. We also compare the information content of AM and ParT by decorrelating the features already learned by AM. Lastly, we briefly comment on the results of AM with finer angular resolution inputs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Localization of infrasonic sources via Bayesian back projection

SUMMARY A Bayesian framework is investigated for event-specific localization of infrasonic sources using back projection ray tracing. Direction-of-arrival information from array-based detection analysis is used to initialize a back projection ray path originating from the detecting array location and quantifying propagation characteristics from hypothetical source locations. The Fisher statistic, computed from the array’s beam coherence, is mapped into uncertainty in the launch angles of the ray path. Auxiliary parameters previously introduced for solving the Transport equation to compute geometric spreading along ray paths are used to map uncertainty in the ray launch angles into spatial and temporal uncertainties in the ray path. An atmospheric ensemble approach is applied to account for atmospheric uncertainty, and the relation between uncertainties in the atmospheric state and confidence in estimated localization are evaluated using several ensembles with specified variances. The method is evaluated using a synthetic event in the western United States constructed via forward propagation simulations as well as a single-station, multi-arrival detection from a surface explosion in the western United States. Localization results using this event-specific approach are more accurate and exhibit improved precision than existing Bayesian localization methods that leverage generalized, pre-computed propagation statistics.

58 GEOSCIENCES↗

A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗