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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Defect-Limited Mobility and Defect Thermochemistry in Mixed A-Cation Tin Perovskites: (CH3NH3)1-xCsxSnBr3

Hybrid organic-inorganic semiconductors crystallizing in the perovskite structure present a significant opportunity for realizing defect-tolerant semiconductors. In this work, we examine the solid solution, (CH3NH3)1-xCsxSnBr3, and identify the thermochemistry dictating the intrinsic carrier concentrations and how local structural distortions influences this electronic behavior. This family of compounds exhibits the expected systematic trend in decreasing optical gap with the cesium to methylammonium A-site mixing ratio, x, in the visible region. However, the carrier mobility, as determined from time-resolved microwave conductivity measurements, trends opposite to that expected from first-principles calculations combined with Boltzmann scattering theory calculations of the carrier mobility. We propose that this is a result of increasing carrier scattering with x in (CH3NH3)1-xCsxSnBr3 due to a significant increase in the carrier density with x. By examining the dependence of the carrier density as a function of x, we infer the compositional-dependence of the average enthalpy and nonconfigurational entropy per defect. While diffraction reveals a cubic aristotypic perovskite structure as a function of x at room temperature, the pair distribution functions obtained from synchrotron X-ray total scattering from these materials are better described by symmetry-adapted displacement modes of the Pm3m crystal structure, which we attribute to a large degree of anharmonic dynamics of the atom positions. This analysis shows that CH3NH3+-rich compositions retain mostly linear Sn-Br-Sn bonding environments through the displacements, while Cs+-rich compositions lead to more significantly bent Sn-Br-Sn environments. We propose that these bent bonding arrangements in Cs-rich compositions yield a higher propensity for defect formation. This also provides a rationale for carrier trapping that gives rise to anomalous microwave transients. Together, these results provide insight into the structure-dynamics-properties relationships in this highly anharmonic system with high amplitude atomic motions and low defect formation energies.

defect thermochemistry↗
DOE OSTI2024

Consistent and reproducible computation of the glass transition temperature from molecular dynamics simulations

In many fields, from semiconductors for opto-electronic applications to ionic liquids (ILs) for separations, the glass transition temperature (Tg) of a material is a useful gauge for its potential use in practical settings. As a result, there is a great deal of interest in predicting Tg using molecular simulations. However, the uncertainty and variation in the trend shift method, a common approach in simulations to predict Tg, can be high. This is due to the need for human intervention in defining a fitting range for linear fits of density with temperature assumed for the liquid and glass phases across the simulated cooling. The definition of such fitting ranges then defines the estimate for the Tg as the intersection of linear fits. We eliminate this need for human intervention by leveraging the Shapiro–Wilk normality test and proposing an algorithm to define the fitting ranges and, consequently, Tg. Through this integration, we incorporate into our automated methodology that residuals must be normally distributed around zero for any fit, a requirement that must be met for any regression problem. Consequently, fitting ranges for realizing linear fits for each phase are statistically defined rather than visually inferred, obtaining an estimate for Tg without any human intervention. The method is also capable of finding multiple linear regimes across density vs temperature curves. We compare the predictions of our proposed method across multiple IL and semiconductor molecular dynamics simulation results from the literature and compare other proposed methods for automatically detecting Tg from density–temperature data. We believe that our proposed method would allow for more consistent predictions of Tg. We make this methodology available and open source through GitHub.

Chemistry↗
DOE OSTI2022

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Slant, Fan, and Narrow: The Response of Stellar Streams to a Tilting Galactic Disk

Stellar streams are sensitive tracers of the gravitational potential, which is typically assumed to be static in the inner Galaxy. However, massive mergers like Gaia-Sausage-Enceladus can impart torques on the stellar disk of the Milky Way that result in the disk tilting at rates of up to 10°–20° Gyr –1 . Here, we demonstrate the effects of disk tilting on the morphology and kinematics of stellar streams. Through a series of numerical experiments, we find that streams with nearby apocenters (r apo ≲ 20 kpc) are sensitive to disk tilting, with the primary effect being changes to the stream's on-sky track and width. Interestingly, disk tilting can produce both more diffuse streams and more narrow streams, depending on the orbital inclination of the progenitor and the direction in which the disk is tilting. Our model of Pal 5's tidal tails for a tilting rate of 15° Gyr –1 is in excellent agreement with the observed stream's track and width, and reproduces the extreme narrowing of the trailing tail. We also find that failure to account for a tilting disk can bias constraints on shape parameters of the Milky Way's local dark matter distribution at the level of 5%–10%, with the direction of the bias changing for different streams. Disk tilting could therefore explain discrepancies in the Milky Way's dark matter halo shape inferred using different streams.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1993

The occultation of 28 Sgr by Titan

We present a comprehensive analysis of data obtained during the 1989 July 3 occultation of 28 Sgr by Titan. The data set includes 23 lightcurves from 15 separate stations, spanning wavelengths from 0.36 to 0.89 micron. A detailed model of the structure of Titan's atmosphere in the altitude range 250 to 450 km is developed, giving the distribution of temperature, pressure, haze optical depth, and zonal wind velocity as a function of altitude and latitude. Haze layers detected in Titan's stratosphere are about one scale height higher than inferred from Voyager data, and show a wavelength dependence indicative of particle sizes on the order of 0.1 micron. A marked north-south dichotomy in haze density is observed with a transition to lower density south of about -20 deg latitude. Zonal wind speeds are inferred from global distortions from spherical symmetry and are of the order of 100 m/s with significant increase toward higher latitudes. Titan's high atmosphere shows substantial axial symmetry; the position angle of the symmetry axis is equal to the position angle of Saturn's spin axis to within about 1 deg.

Hubbard, W. B.↗
NASA NTRS1994

A comparison of dynamical and molecular gas masses in very luminous infrared galaxies

Observations of the 2.3 micron bands of CO have been used to measure the central stellar velocity dispersions in NGC 1614 and IC 694. K-band images were used to constrain models of the stellar mass distribution. With these data and a spectrum of Arp 220 from the literature, we have determined the total mass within the central regions of all three galaxies. The central molecular gas masses inferred from (12)CO J = 1-0 fluxes are larger than the total masses determined from stellar kinematics. Subtraction of the likely stellar mass from the total mass yields upper limits for the H2 mass that are 4-10 times less than the previously reported masses. This result supports other arguments that the I(sub CO)/M(sub H2) ratio is not the same in ultraluminous galaxies as it is in Milky Way giant molecular clouds.

Shier, L. M.↗
NASA NTRS2004

Lattice Duality: The Origin of Probability and Entropy

Bayesian probability theory is an inference calculus, which originates from a generalization of inclusion on the Boolean lattice of logical assertions to a degree of inclusion represented by a real number. Dual to this lattice is the distributive lattice of questions constructed from the ordered set of down-sets of assertions, which forms the foundation of the calculus of inquiry-a generalization of information theory. In this paper we introduce this novel perspective on these spaces in which machine learning is performed and discuss the relationship between these results and several proposed generalizations of information theory in the literature.

Knuth, Kevin H.↗
NASA NTRS2013

Characterization of the Optical and X-ray Properties of the Northwestern Wisps in the Crab Nebula

We have studied the variability of the Crab Nebula both in the visible and in X -rays. Optical observations were obtained using the Nordic Optical Telescope in La Palma and X -ray observations were made with the Chandra X -Ray Observatory. We observe wisps forming and peeling off from the region commonly associated with the termination shock of the pulsar wind. We measure a number of properties of the wisps to the Northwest of the pulsar. We find that the exact locations of the wisps in the optical and in X-rays are similar but not coincident, with the X-ray wisp preferentially located closer to the pulsar. Our measurements and their implications are interpreted in terms of a MHD model. We find that the optical wisps are more strongly Doppler boosted than X-ray wisps, a result inconsistent with current MHD simulations. Indeed the inferred optical boosting factors exceed MHD simulation values by about one order of magnitude. These findings suggest that the optical and X-ray wisps are not produced by the same particle distribution, a result which is consistent with the spatial differences. Further, the X -ray wisps and optical wisps are apparently developing independently from each other, but every time a new X ]ray wisp is born so is an optical wisp, thus pointing to a possible common cause or trigger. Finally, we find that the typical wisp formation rate is approximately once per year, interestingly at about the same rate of production of the large gamma-ray flares.

Weisskopf, M. C.↗
NASA NTRS2003

Mineralogy and Petrology of Amoeboid Olivine Inclusions in CO3 Chondrites: Relationship to Parent-Body Aqueous Alteration

Petrographic and mineralogic studies of amoeboid olivine inclusions (AOIs) in CO3 carbonaceous chondrites reveal that they are sensitive indicators of parent-body aqueous and thermal alteration. As the petrologic subtype increases from 3.0 to 3.8, forsteritic olivine (Fa(sub 0-1)) is systematically converted into ferroan olivine (Fa(sub 60-75)). We infer that the Fe, Si and O entered the assemblage along grain boundaries, forming ferroan olivine that filled fractures and voids. As temperatures increased, Fe(+2) from the new olivine exchanged with Mg(+2) from the original AOI to form diffusive haloes around low-FeO cores. Cations of Mn(+2), Ca(+2) and Cr(+3) were also mobilized. The systematic changes in AOI textures and olivine compositional distributions can be used to refine the classification of CO3 chondrites into subtypes. In subtype 3.0, olivine occurs as small forsterite grains (Fa(sub 0-1)), free of ferroan olivine. In petrologic subtype 3.2, narrow veins of FeO-rich olivine have formed at forsterite grain boundaries. With increasing alteration, these veins thicken to form zones of ferroan olivine at the outside AOI margin and within the AOI interior. By subtype 3.7, there is a fairly broad olivine compositional distribution in the range Fa(sub 63-70), and by subtype 3.8, no forsterite remains and the high-Fa peak has narrowed, Fa(sub 64-67). Even at this stage, there is incomplete equilibration in the chondrite as a whole (e.g., data for coarse olivine grains in Isna (CO3.8) chondrules and lithic clasts show a peak at Fa(sub39)). We infer that the mineral changes in A01 identified in the low petrologic types required aqueous or hydrothermal fluids whereas those in subtypes greater than or equal to 3.3 largely reflect diffusive exchange within and between mineral grains without the aid of fluids.

Chizmadia, Lysa J.↗
DOE OSTI2025

Statistical inference of collision frequencies from x-ray Thomson scattering spectra

Thomson scattering spectra measure the response of plasma particles to incident radiation. In warm dense matter, which is opaque to visible light, x-ray Thomson scattering (XRTS) enables a detailed probe of the electron distribution and has been used as a diagnostic for electron temperature, density, and plasma ionization. In this work, we examine the sensitivities of inelastic XRTS signatures to modeling details, including the dynamic collision frequency and the electronic density of states. Applying verified Monte Carlo inversion methods to dynamic structure factors obtained from time-dependent density functional theory, we assess the utility of XRTS signals as a way to inform the dynamic collision frequency, especially its direct-current limit, which is directly related to the electrical conductivity.

Collision frequency↗
DOE OSTI2020

Flow-based likelihoods for non-Gaussian inference

We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particular, we suggest using the optimization targets of flow-based generative models, a class of models that can capture complex distributions by transforming a simple base distribution through layers of nonlinearities. We call these flow-based likelihoods (FBL). We analyze the accuracy and precision of the reconstructed likelihoods on mock Gaussian data, and show that simply gauging the quality of samples drawn from the trained model is not a sufficient indicator that the true likelihood has been learned. We nevertheless demonstrate that the likelihood can be reconstructed to a precision equal to that of sampling error due to a finite sample size. We then apply FBLs to mock weak lensing convergence power spectra, a cosmological observable that is significantly non-Gaussian (NG). We find that the FBL captures the NG signatures in the data extremely well, while other commonly used data-driven likelihoods, such as Gaussian mixture models and independent component analysis, fail to do so. This suggests that works that have found small posterior shifts in NG data with data-driven likelihoods such as these could be underestimating the impact of non-Gaussianity in parameter constraints. By introducing a suite of tests that can capture different levels of NG in the data, we show that the success or failure of traditional data-driven likelihoods can be tied back to the structure of the NG in the data. Here, unlike other methods, the flexibility of the FBL makes it successful at tackling different types of NG simultaneously. Because of this, and consequently their likely applicability across datasets and domains, we encourage their use for inference when sufficient mock data are available for training.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Empirical radius formulas for canonical neutron stars from bidirectionally selecting features of equations of state in extended Bayesian analyses of observational data

Significant advancement in Bayesian inference of nuclear equation of state (EOS) from gravitational wave and x-ray observations of neutron stars (NSs) has been made by the nuclear astrophysics community especially since GW170817. By extending the traditional Bayesian analysis which normally ends at presenting the marginalized posterior probability distribution functions (PDFs) of individual EOS parameters and their correlations (or sometimes only the Pearson correlation coefficients which are only reliably useful when the variables are linearly correlated while they are actually often not), we search for a data-driven and robust empirical formula for the radius 𝑅 1.4 of canonical NSs in terms of the characteristic EOS parameters (features). We also identify the single most important but currently poorly known EOS parameter for determining the 𝑅 1.4 . Using three regression-model-building methodologies: bidirectional stepwise feature selection, least absolute shrinkage selection operator (LASSO) regression, and neural network regression on a large set of posterior EOSs and the corresponding 𝑅 1.4 values inferred from earlier comprehensive Bayesian analyses of NS observational data, we systematically and rigorously develop the most probable 𝑅 1.4 formulas with varying statistical accuracy and technical complexity. Here, the most important EOS parameters for determining 𝑅 1.4 are found consistently in each of the feature selection processes to be (in order of decreasing importance): curvature 𝐾 sym , slope 𝐿, skewness 𝐽 sym of nuclear symmetry energy, skewness 𝐽 0 , incompressibility 𝐾 0 of symmetric nuclear matter, and the magnitude 𝐸 sym ⁡(𝜌 0 ) of symmetry energy at the saturation density 𝜌 0 of nuclear matter.

Bayesian methods↗
DOE OSTI2022

Physics-Informed Sparse Gaussian Process for Probabilistic Stability Analysis of Large-Scale Power System with Dynamic PVs and Loads

This work proposes a physics-informed sparse Gaussian process (SGP) for probabilistic stability assessment of large-scale power systems in the presence of uncertain dynamic PVs and loads. The differential and algebraic equations considering uncertainties from dynamic PVs and loads are reformulated to a nonlinear mapping relationship that allows the application of SGP. Thanks to the nonparametric characteristic of Gaussian process, the proposed framework does not require distributions of uncertain inputs and this distinguishes it from existing approaches. As the original Gaussian process is not scalable to large-scale systems with high dimensional uncertain inputs, this paper develops the SGP with a stochastic variational inference technique. It leads to approximately two orders of complex reduction. A data pre-processing step is also introduced to tackle the coexistence of stable and unstable cases by sample clustering and constructing separate SGPs. The probabilistic transient stability index is analyzed to assess system stability under different uncertain dynamics loads and PVs. Comparisons are performed with the sampling-based, the polynomial chaos expansion-based, and traditional Gaussian process-based methods on the modified IEEE 118-bus and Texas 2000-bus systems under various scenarios, including different levels of uncertainties and the existence of nonlinear correlations among dynamic PVs. The impacts of data quality and quantity issues are also investigated. It is shown that the proposed SGP achieves significantly improved computational efficiency while maintaining high accuracy with a limited number of data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Applying the core-satellite species concept: Characteristics of rare and common riverine dissolved organic matter

Introduction: Dissolved organic matter (DOM) composition varies over space and time, with a multitude of factors driving the presence or absence of each compound found in the complex DOM mixture. Compounds ubiquitously present across a wide range of river systems (hereafter termed core compounds) may differ in chemical composition and reactivity from compounds present in only a few settings (hereafter termed satellite compounds). Here, we investigated the spatial patterns in DOM molecular formulae presence (occupancy) in surface water and sediments across 97 river corridors at a continental scale using the “Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems—WHONDRS” research consortium. Methods: We used a novel data-driven approach to identify core and satellite compounds and compared their molecular properties identified with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results: In this work, we found that core compounds clustered around intermediate hydrogen/carbon and oxygen/carbon ratios across both sediment and surface water samples, whereas the satellite compounds varied widely in their elemental composition. Within surface water samples, core compounds were dominated by lignin-like formulae, whereas protein-like formulae dominated the core pool in sediment samples. In contrast, satellite molecular formulae were more evenly distributed between compound classes in both sediment and water molecules. Core compounds found in both sediment and water exhibited lower molecular mass, lower oxidation state, and a higher degree of aromaticity, and were inferred to be more persistent than global satellite compounds. Higher putative biochemical transformations were found in core than satellite compounds, suggesting that the core pool was more processed. Discussion: The observed differences in chemical properties of core and satellite compounds point to potential differences in their sources and contribution to DOM processing in river corridors. Overall, our work points to the potential of data-driven approaches separating rare and common compounds to reduce some of the complexity inherent in studying riverine DOM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Design and calibration of a coherent lidar for measurement of atmospheric backscatter

This paper discusses the background requirements for, and the design and calibration of a coherent Doppler lidar which is oriented specifically toward the measurement of low values of atmospheric backscatter at a wavelength of 10.6 microns. The lidar is a compact, continuous wave system which can operate in two modes, multiple particle scattering and single particle scattering. In the multiple scattering mode, the lidar employs an extended focal volume and utilizes a technique similar to Dicke switching to achieve measurement of the volume backscatter. In the single scattering mode, the focal volume is reduced to ensure a high probability of single particle scattering. Measurement of the single particle backscatter as a function of time leads to the formation of signal histogram from which the volume backscatter can be inferred. In addition to providing the atmospheric backscatter value, appropriate data processing algorithms and focal volume calibration allow the single particle mode to yield information on the atmospheric aerosol scattering cross-section distribution.

Jones, W. D.↗
NASA NTRS1984

Association between energetic particle bursts and Birkeland currents in the geomagnetic tail

IMP 8 observations in the geomagnetic tail of energetic particles at hundreds of keV and of the magnetic field are examined for a substorm period from 1700 to 1800 UT on Mar. 3, 1976. For this interval, it is found that bursts of energetic protons detected at a downstream distance of about 37 earth radii in the midnight tail region are accompanied by east-west magnetic field perturbations indicative of Birkeland current sheets. The magnitude of the magnetic field perturbations range from about 1 to 12 nT, corresponding to current densities of 1 to 9 mA/m when integrated over the current sheet thickness. These values are comparable to previous observations of Birkeland currents in the near-earth tail (X greater than -20 earth radii) and with the auroral-arc-associated Birkeland current densities at low altitudes scaled out to the tail region. The favorable comparison suggests that the closure of small-scale Birkeland current systems, at least in these instances, lies tailward of about 40 earth radii. The observed Birkeland current system and the magnitude of current densities are found to be consistent with ion tearing instability in the tail. The inferred wavelength of the tearing mode along the tail axis is about 2 to 17 earth radii. In the context of the tearing model, the presence of Birkeland currents and the occasional isotropic distribution of energetic electrons (of more than 0.22 MeV) suggest that the energetic particle events in this study occur on closed magnetic field lines, even though strong tailward streaming dominates the particle anisotropy in these events.

Lui, A. T. Y.↗
NASA NTRS1991

The influence of polar heterogeneous processes on reactive chlorine at middle latitudes - Three dimensional model implications

Three-dimensional model calculations with the NASA/GSFC chemistry and transport model have been designed to consider the impact of heterogeneous processes occurring on polar stratospheric clouds (PSCs) in the Arctic vortex on the HCl distribution. By examining the HCl concentration for a calculation with PSCs relative to a calculation with gas phase chemistry only, the impact of polar processing on reactive chlorine species at middle latitudes is inferred. Results from the chemistry and transport model reproduce basic features of the ClO measurements (Toohey et al., 1991), which were made on the ferry flights of the ER-2 from Stavanger, Norway to Moffett Field, California via Wallops Island, Virginia on February 20 and 21, 1989. The model indicates that perturbed air which is contained within the polar vortex during winter is not homogeneously mixed, and that the ferry flights were made through air with the largest conversion of HCl to reactive chlorine that is seen at middle latitudes.

Douglass, Anne R.↗