SEARCH · Search NASA

Results for “analyzable function”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Black hole horizon edge partition functions

We extend a formula for 1-loop black hole determinants by Denef, Hartnoll, and Sachdev (DHS) to spinning fields on any (d + 1)-dimensional static spherically symmetric black hole. By carefully analyzing the regularity condition imposed on the Euclidean eigenfunctions, we reveal an unambiguous bulk-edge split in the 1-loop Euclidean partition function for tensor fields of arbitrary integer spin: the bulk part captures the “renormalized” thermal canonical partition function recently discussed in [1]; the edge part is related to quasinormal modes (QNMs) that fail to analytically continue to a subset of Euclidean modes with enhanced fall-offs near the origin. Since the edge part takes the form of a path integral on S d–1 , this suggests that these are associated with degrees of freedom living on the bifurcation surface in the Lorentzian two-sided black hole geometry. For massive higher spin on static BTZ and massive vector on Nariai black holes, we find that the edge partition function is related to the QNMs with lowest overtone numbers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Evaluation of assumptions made by Hygroscopic Tandem Differential Mobility Analyzer inversion routines

The Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) measures the hygroscopicity of atmospheric particles, and many atmospheric processes that change this hygroscopicity also change the atmospheric size distribution. Two assumptions made during H-TDMA inversion create spurious hygroscopic trends as a function of the changing inlet size distribution. These two assumptions—that the particles exiting the first Differential Mobility Analyzer (DMA1) are singly charged and that the inlet size distribution has a slope of zero (flat)— generate Multi-Charge Dispersion (MCD) bias and Slope bias, respectively. First, we use a model, named TAO, to show that the inlet size distribution could theoretically change the measured ammonium sulfate hygroscopicity by 10%–20% as a function of diameter or experimental time with no change in relative humidity. Secondly, we show experimentally that aerosol emitted from the flaming combustion of grass creates MCD bias. Here, in this experiment, we measure the CPC response of the first three charges and invert these responses using a new routine named Junior. Junior's inversion of each charge shows that one growth factor distribution describes all measured diameters (no growth dependence on diameter). As in the modeling study above, previous publications of this aerosol system, using traditional inversion assumptions, report a decrease in hygroscopicity as DMA1 diameter increases. Unlike traditional inversions, Junior's inversion does not assume the particles are singly charged nor does it make the flat inlet size distribution assumption. Instead, both the inlet size distribution and each charge's CPC response are measured quantities. Thus, the discrepancy between our inversion results and previous publications is likely due to the traditional inversion routine assumptions. This underscores the importance for accounting for Slope and MCD bias during inversions. Experimental results should be carefully analyzed when reporting hygroscopic trends with respect to diameter or experimental time when using the traditional inversion assumptions.

42 ENGINEERING↗

DOE OSTI2019

FTIR and Raman Spectroscopy of Reduced Graphene Oxide Carbon Nanoribbons and Graphene Oxide on Copper (Cu)

In the past couple of decades, carbon nanomaterials produced from graphene and graphite have emerged as one of the more important recently discovered substances. These carbon nanomaterials have been found to exhibit high levels of mechanical strength, thermal resistance, and electrical conductivity, thus having a multitude of applications. Therefore, it is important to identify and analyze their traits in order to maximize their effectiveness. Two spectroscopic techniques employed for such analyses of these materials are Fourier-Transform Infrared (FTIR) and Raman Spectroscopy. The advantages of FTIR and Raman include nondestructive analysis, relatively quick measurements under normal atmospheric conditions, and enhanced sensitivity with high resolution capacity. FTIR Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the functionality groups of a carbon nanomaterial. Raman Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the intensity of the disorder peak, which is greater in intensity if the carbon nanomaterial exhibits greater amounts of functionalities or defects in the graphitic material. There were two sample types which were analyzed with both FTIR and Raman Spectroscopy for the research project: graphene nanoribbons and graphene oxide. The m-grade graphene nanoribbons (GNRs) were produced from m-grade carbon nanotubes (CNTs) via Tour's method. The graphene oxide (GO) was produced from graphene via Tour's method, sonicated and centrifuged, dip-coated onto Copper (Cu) foil, and then photoreduced under a UV light source. FTIR measurements and analyses were conducted using a Jasco FTIR Spectrometer. Raman measurements and analyses were conducted using a Jasco Laser Raman Spectrometer. Tasks and techniques for this project included photoreduction, dip-coating, corrosion testing, FTIR and Raman data collection and analysis, and improvement of data collection for the Raman Spectrometer. GNRs exfoliated and reduced (deoxygenation) at 270 deg. C in air showed a significant decrease in O functionalities according to FTIR. However, Raman revealed that a large increase in graphene planar and edge defects are present as indicated by the disorder band at 1340 cm-1. Further optimization could be performed by thermal exfoliation at lower temperatures assuming a need for fewer structural defects. Graphene oxide coatings showed clear reduction with an increase with photoreduction time. Raman revealed that the reduced graphene oxide films had less disruption in the planar phonon lattice vibrations which indicates that the structure is returning to sp2 hybridization of pristine graphene without adding structural defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Social support and cognitive function in Chinese older adults who experienced depressive symptoms: is there an age difference?

Objective This study examined the moderating effect of overall social support and the different types of social support on cognitive functioning in depressed older adults. We also investigated whether the moderating effect varied according to age. Methods A total of 2,500 older adults (≥60 years old) from Shanghai, China were enrolled using a multistage cluster sampling method. Weighted linear regression and multiple linear regression was utilized to analyze the moderating effect of social support on the relationship between depressive symptoms and cognitive function and to explore its differences in those aged 60–69, 70–79, and 80 years and above. Results After adjusting for covariates, the results indicated that overall social support (β = 0.091, p = 0.043) and support utilization (β = 0.213, p < 0.001) moderated the relationship between depressive symptoms and cognitive function. Support utilization reduced the possibility of the cognitive decline in depressed older adults aged 60–69 years (β = 0.310, p < 0.001) and 80 years and above (β = 0.199, p < 0.001), while objective support increased the possibility of cognitive decline in depressed older people aged 70–79 years (β = −0.189, p < 0.001). Conclusion Our findings highlight the buffering effects of support utilization on cognitive decline in depressed older adults. We suggest that age-specific measures should be taken when providing social support to depressed older adults in order to reduce the deterioration of cognitive function.

Jing, Yurong↗

DOE OSTI2020

Clustering of LRGs in the DECaLS DR8 Footprint: Distance Constraints from Baryon Acoustic Oscillations Using Photometric Redshifts

A photometric redshift sample of luminous red galaxies (LRGs) obtained from the DECam Legacy Survey (DECaLS) is analyzed to probe cosmic distances by exploiting the wedge approach of the two-point correlation function. Although the cosmological information is highly contaminated by the uncertainties existing in the photometric redshifts from the galaxy map, an angular diameter distance can be probed at the perpendicular configuration in which the measured correlation function is minimally contaminated. An ensemble of wedged correlation functions selected up to a given threshold based on having the least contamination was studied in previous work (Sridhar & Song 2019) using simulations, and the extracted cosmological information was unbiased within this threshold. Furthermore, we apply the same methodology for analyzing the LRG sample from DECaLS, which will provide the optical imaging for targeting two-thirds of the Dark Energy Spectroscopic Instrument footprint and measure the angular diameter distances at z = 0.69 and z = 0.87 to be D A (0.697) = (1529 ± 73 Mpe)(r d /r d.fid ) and D A (0.874) = (1674 ± 102 Mpe)(r d /r d.fid ) with a fractional error of 4.77% and 6.09%, respectively. We obtain a value of H 0 = 66.58 ± 5.31 km s -1 Mpc -1 , which supports the H 0 measured by all other baryon acoustic oscillation results and is consistent with the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Statistically Rigorous Uncertainty Quantification for Physical Parameter Model Calibration with Functional Output

In experiments conducted on the Z-machine at Sandia National Laboratories, dynamic material properties cannot be analyzed using traditional analytic methods, necessitating solving an inverse problem. Bayesian model calibration is a statistical framework for solving an inverse problem to estimate parameters input into a computational model in the presence of multiple uncertainties. Disentangling input parameter uncertainty and model misspecification is often poorly identified problem. When using computational models for physical parameter estimation, the issue of parameter identifiability must be carefully considered to obtain accurate and precise estimates of physical parameters. Additionally, in dynamic material properties applications, the experimental output is a function, velocity over time. While we can sample an arbitrarily large number of points from the measured velocity, these curves only contain a finite amount of information about the calibration parameters. In this report, we propose modifications to the Bayesian model calibration framework to simplify and improve the estimation of physical parameters with functional outputs. Specifically, we propose scaling the likelihood function by an effective sample size rather than modeling the discrepancy function; and modularizing input nuisance parameters with weakly identified parameters. We evaluate the performance of these proposed methods using a statistical simulation study and then apply these methods to estimate parameters of the tantalum equation of state. We conclude that these proposed methods can provide simple, fast, and statistically valid alternatives to the full Bayesian model calibration procedure; and that these methods can be used to estimate parameters of the equation of state for tantalum.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

NOx speciation from copper dissolution in nitric acid/water solutions using FTIR spectroscopy

The speciation of NO 2 , NO, and N 2 O gases formed from the dissolution of copper in nitric acid is measured and characterized using Fourier-transform infrared (FTIR) spectroscopy. This study describes analysis of the gas phase species formed and ingrowths of their concentrations as a function of time. Acid concentrations range from 14 to 4 M and the NO 2 , NO, and N 2 O are analyzed using FTIR between 1585 and 2209 wavenumbers. The concentrations of the gases range from 0 to 230 ppm and change over time and as a function of acid concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A Compton transmission polarimeter for DC and SRF electron photo-injectors

The production of high-current and intense spin polarized electron beams is of great importance in electron-based facilities. Tests are planned to produce such beams in 2023 using GaAs-based photocathodes installed in the Brookhaven National Lab RHIC Coherent electron Cooling superconducting radiofrequency (SRF) photogun [1]. A fast and efficient electron polarimeter operating in the MeV energy range is required to measure the beam spin polarization. While Mott polarimeters provide larger measured asymmetries, a Compton Transmission polarimeter is well suited in the few MeV energy range. In this work, we report on a relatively compact and cost-effective Compton transmission polarimeter which has been built and calibrated at Jefferson Lab (JLab). First, we present the design of the polarimeter radiator, polarized target analyzing magnet, BGO detector assembly and data acquisition system. Next, results of a two-week commissioning study performed at the JLab Upgraded Injector Test Facility will be described. Here, a well-known polarized electron beam produced from a bulk GaAs photocathode in a dc high-voltage photogun was first measured in a 180 keV Mott scattering polarimeter, then used to characterize and calibrate the Compton transmission polarimeter as a function of the polarized target magnetization and beam properties. Finally, we report an effective analyzing power of the Compton polarimeter and compare experimental results with those produced via Geant4 simulations.

Blume, G.↗

DOE OSTI2023

A Compton transmission polarimeter for DC and SRF electron photo-injectors

Blume, G.↗

DOE OSTI2019

Toward practical approaches for ergodicity analysis

It is of importance to perform hydrological forecast using a finite hydrological time series. Most time series analysis approaches presume a data series to be ergodic without justifying this assumption. To our knowledge, there are no methods available for test of ergodicity to date. As such, this paper presents a practical approach to analyze the mean ergodic property of hydrological processes by means of augmented Dickey Fuller test, Mann-Kendall trend test, a radial basis function neural network, and the assessment methods derived from the definition of ergodicity. The mean ergodicity of precipitation processes at Newberry, MI, USA, is analyzed using the proposed approach. The results indicate that the precipitations of January, May, and July in Newberry are highly likely to have ergodic property, the precipitations of February, and October through December have tendency toward mean ergodicity, and the precipitations of all the other months are non-ergodic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Notes on resonances and unitarity from celestial amplitudes

We study the celestial description of the O(N) sigma model in the large N limit as introduced by Coleman, Jackiw and Politzer. Focusing on three dimensions, we analyze the implications of a UV complete, all-loop order 4-point amplitude of pions in terms of correlation functions defined on the celestial circle. We find these retain many key features from the previously studied tree-level case, such as their relation to Generalized Free Field theories and crossing-symmetry, but also incorporate new properties such as IR/UV softness and S-matrix metastable states. In particular, to understand unitarity, we propose a form of the optical theorem that controls the imaginary part of the correlator based solely on the presence of these resonances. We also explicitly analyze the conformal block expansions and factorization of four-point functions into three-point functions. We find that summing over resonances is key for these factorization properties to hold. We end with some topics for future study.

1/N expansion↗

DOE OSTI2022

Pectin methyltransferase QUASIMODO2 functions in the formation of seed coat mucilage in Arabidopsis

Pectin, cellulose, and hemicelluloses are major components of primary cell walls in plants. In addition to cell adhesion and expansion, pectin plays a central role in seed mucilage. Seed mucilage contains abundant pectic rhamnogalacturonan-I (RG-I) and lower amounts of homogalacturonan (HG), cellulose, and hemicelluloses. Previously, accumulated evidence has addressed the role of pectin RG-I in mucilage production and adherence. However, less is known about the function of pectin HG in seed coat mucilage formation. In this study, we analyzed a novel mutant, designated things fall apart2 (tfa2), which contains a mutation in HG methyltransferase QUASIMODO2 (QUA2). Etiolated tfa2 seedlings display short hypocotyls and adhesion defects similar to qua2 and tumorous shoot development2 (tsd2) alleles, and show seed mucilage defects. Here, the diminished uronic acid content and methylesterification degree of HG in mutant seed mucilage indicate the role of HG in the formation of seed mucilage. Cellulosic rays in mutant mucilage are collapsed. The epidermal cells of seed coat in tfa2 and tsd2 display deformed columellae and reduced radial wall thickness. Under polyethylene glycol treatment, seeds from these three mutant alleles exhibit reduced germination rates. Together, these data emphasize the requirement of pectic HG biosynthesis for the synthesis of seed mucilage, and the functions of different pectin domains together with cellulose in regulating its formation, expansion, and release.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Bosonic field digitization for quantum computers

Quantum simulation of quantum field theory is a flagship application of quantum computers that promises to deliver capabilities beyond classical computing. The realization of quantum advantage will require methods that can accurately predict error scaling as a function of the resolution and parameters of the model and that can be implemented efficiently on quantum hardware. In this paper, we address the representation of lattice bosonic fields in a discretized field amplitude basis, develop methods to predict error scaling, and present efficient qubit implementation strategies. A low-energy subspace of the bosonic Hilbert space, defined by a boson occupation number cutoff, can be represented with exponentially good accuracy by a low-energy subspace of a finite-size Hilbert space. The finite representation construction and the associated errors are directly related to the accuracy of the Nyquist-Shannon sampling and the finite Fourier transforms of the boson number states in the field and the conjugate-field bases. We analyze the relation between the boson mass, the discretization parameters used for wave function sampling, and the finite representation size. Numerical simulations of small size Φ 4 problems demonstrate that the boson mass optimizing the sampling of the ground state wave function is a good approximation to the optimal boson mass yielding the minimum low-energy subspace size. However, we find that accurate sampling of general wave functions does not necessarily result in accurate representation. Finally, we develop methods for validating and adjusting the discretization parameters to achieve more accurate simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Density-Functional Tight-Binding for Platinum Clusters and Bulk: Electronic vs Repulsive Parameters

We present a general purpose Pt-Pt density-functional tight-binding (DFTB) parameter for Pt clusters as well as bulk, using a genetic algorithm (GA) to automatize the parameterization effort. First we quantify the improvement possible by only optimizing the repulsive potential alone, and second we investigate the effect of improving the electronic parameter as well. During both parameterization efforts we employed our own training set and test sets, with one set containing ~20,000 spin-polarized DFT structures. We analyze the performance of our two DFTB Pt-Pt parameter sets against density functional theory (DFT) as well as an earlier DFTB Pt-Pt parameters. Our study sheds light on the role of both repulsive and electronic parameters with regards to DFTB performance.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Expanding Structural Space for Immunomodulatory Nucleic Acid Nanoparticles via Spatial Arrangement of Their Therapeutic Moieties

Different therapeutic nucleic acids (TNAs) can be unified in a single structure by their elongation with short oligonucleotides designed to self-assemble into nucleic acid nanoparticles (NANPs). With this approach, therapeutic cocktails with precisely controlled composition and stoichiometry of active ingredients can be delivered to the same diseased cells for enhancing pharmaceutical action. In this study, an additional nanotechnology-based therapeutic option that enlists a biocompatible NANP-encoded platform for their controlled patient-specific immunorecognition is explored. For this, a set of representative functional NANPs is extensively characterized in vitro, ex vivo, and in vivo and then further analyzed for immunostimulation of human peripheral blood mononuclear cells freshly collected from healthy donor volunteers. The results of the study present the advancement of the current TNA approach toward personalized medicine and offer a new strategy to potentially address top public health challenges related to drug overdose and safety through the biodegradable nature of the functional platform with immunostimulatory regulation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Characterizing quantum circuits with qubit functional configurations

Abstract We develop a systematic framework for characterizing all quantum circuits with qubit functional configurations. The qubit functional configuration is a mathematical structure that can classify the properties and behaviors of quantum circuits collectively. Major benefits of classifying quantum circuits in this way include: 1. All quantum circuits can be classified into corresponding types; 2. Each type characterizes important properties (such as circuit complexity) of the quantum circuits belonging to it; 3. Each type contains a huge collection of possible quantum circuits allowing systematic investigation of their common properties. We demonstrate the theory’s application to analyzing the hardware-efficient ansatzes of variational quantum algorithms. For potential applications, the functional configuration theory may allow systematic understanding and development of quantum algorithms based on their functional configuration types.

97 MATHEMATICS AND COMPUTING↗