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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗
DOE OSTI2023

The star-formation history in the last 10 billion years from CIB cross-correlations

ABSTRACT The cosmic infrared background (CIB) traces the emission of star-forming galaxies throughout all cosmic epochs. Breaking down the contribution from galaxies at different redshifts to the observed CIB maps would allow us to probe the history of star formation. In this paper, we cross-correlate maps of the CIB with galaxy samples covering the range z ≲ 2 to measure the bias-weighted star-formation rate (SFR) density 〈bρSFR〉 as a function of time in a model independent way. This quantity is complementary to direct measurements of the SFR density ρSFR, giving a higher weight to more massive haloes, and thus provides additional information to constrain the physical properties of star formation. Using cross-correlations of the CIB with galaxies from the DESI Legacy Survey and the extended Baryon Oscillation Spectroscopic Survey, we obtain high signal-to-noise ratio measurements of 〈bρSFR〉, which we then use to place constraints on halo-based models of the star-formation history. We fit halo-based SFR models to our data and compare the recovered ρSFR with direct measurements of this quantity. We find a qualitatively good agreement between both independent data sets, although the details depend on the specific halo model assumed. This constitutes a useful robustness test for the physical interpretation of the CIB, and reinforces the role of CIB maps as valuable astrophysical probes of the large-scale structure. We report our measurements of 〈bρSFR〉 as well as a thorough account of their statistical uncertainties, which can be used to constrain star-formation models in combination with other data.

Astronomy & Astrophysics↗
DOE OSTI2023

An empirical approach to model selection: weak lensing and intrinsic alignments

ABSTRACT In cosmology, we routinely choose between models to describe our data, and can incur biases due to insufficient models or lose constraining power with overly complex models. In this paper, we propose an empirical approach to model selection that explicitly balances parameter bias against model complexity. Our method uses synthetic data to calibrate the relation between bias and the χ2 difference between models. This allows us to interpret χ2 values obtained from real data (even if catalogues are blinded) and choose a model accordingly. We apply our method to the problem of intrinsic alignments – one of the most significant weak lensing systematics, and a major contributor to the error budget in modern lensing surveys. Specifically, we consider the example of the Dark Energy Survey Year 3 (DES Y3), and compare the commonly used non-linear alignment (NLA) and tidal alignment and tidal torque (TATT) models. The models are calibrated against bias in the Ωm–S8 plane. Once noise is accounted for, we find that it is possible to set a threshold Δχ2 that guarantees an analysis using NLA is unbiased at some specified level Nσ and confidence level. By contrast, we find that theoretically defined thresholds (based on, e.g. p-values for χ2) tend to be overly optimistic, and do not reliably rule out cosmological biases up to ∼1–2σ. Considering the real DES Y3 cosmic shear results, based on the reported difference in χ2 from NLA and TATT analyses, we find a roughly $30{{\ \rm per\ cent}}$ chance that were NLA to be the fiducial model, the results would be biased (in the Ωm–S8 plane) by more than 0.3σ. More broadly, the method we propose here is simple and general, and requires a relatively low level of resources. We foresee applications to future analyses as a model selection tool in many contexts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Distribution function of nuclei from $\mathcal{e}^±$ scattering in the presence of a strong primordial magnetic field

The amplitude of the primordial magnetic field (PMF) is constrained from observational limits on primordial nuclear abundances. Within this constraint, it is possible that nuclear motion is regulated by Coulomb scattering with electrons and positrons (e ± s), while e ± s are affected by a PMF rather than collisions. For example, at a temperature of 10 9 K, thermal nuclei typically experience ~ 10 21 scatterings per second that are dominated by very small angle scattering leading to minuscule changes in the nuclear kinetic energy of order $\mathcal{O}$(1) eV. In this paper the upper limit on the effects of a possible discretization of the e ± momenta by the PMF on the nuclear momentum distribution is estimated under the extreme assumptions that the momentum of the e ± is relaxed before and after Coulomb scattering to Landau levels, and that during Coulomb scattering the PMF is neglected. This assumption explicitly breaks the time reversal invariance of Coulomb scattering, and the Maxwell-Boltzmann distribution is not a trivial steady state solution of the Boltzmann equation under these assumptions. Here we numerically evaluate the collision terms in the Boltzmann equation, and show that the introduction of a special direction in the e ± distribution by the PMF generates no directional dependence of the collisional destruction term of nuclei. Large anisotropies in the nuclear distribution function are then constrained from big bang nucleosynthesis. Ultimately, we conclude that a PMF does not significantly affect the isotropy or big bang nucleosynthesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Thoughts on Analyzing Neutron Multiplicity Data

Bayesian methods offer many advantages for analyzing neutron multiplicity data. Ideally one would make nonparametric estimates of the the posterior distributions, the probabilities - given the data - for unknowns to take on particular values. Once one has the posterior, uncertainty quantification is very natural. We describe how different ways of formulating the statistical theory of fission chains are mathematically equivalent. When confronted with actual data and the burden of finite statistics, different methods of expressing the theory offer advantages for understanding the underlying source parameters from an information theory standpoint.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Evaluating Space Object Conjunction Probabilities Using Characteristic Function Inversion

This report discusses an approach to computing the probability of a conjunction between two space objects in the short-term encounter scenario. A conjunction is defined here as an event where the miss distance between the objects is less than some specified value. The scenario assumptions are that the motion of the objects is linear, their positions are Gaussian distributed, and their velocities are known and constant. Under these assumptions, the squared-miss distance is shown to have the generalized chi-square distribution. An established statistical technique called characteristic function inversion is employed to evaluate the distribution and obtain conjunction probabilities. The method is closely related to a recent approach based on moment generating function inversion, and a qualitative comparison of the approaches is provided. Last, the method is tested on several benchmark test cases where it agrees with numerical integration on the cases with conjunction probabilities above 10 –12 . However, the exact probability in these cases is usually not needed and this probability can be bounded above using an independent Gaussian approximation. Overall, the report shows how to compute conjunction probabilities using a standard statistical method, though numerical integration seems to perform equally well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Results from the Muon g-2 experiment at Fermilab

The goal of the Muon g-2 experiment at Fermilab is to measure the muon magnetic momentanomaly with a final accuracy of 140 parts per billion (ppb). The experiment has published tworesults based on the data collected in 2018 (Run-1) and 2019-2020 (Run-2/3), respectively. These results confirm the previous measurement performed 20 years ago at Brookhaven National Laboratory, and their combination reaches the unprecedented uncertainty of 200 ppb. This proceeding presents a brief overview of the Standard Model prediction for the muon g-2. It then summarizes the experimental measurement technique and the Run-1 and Run-2/3 measurements, detailing the improvements in their systematic and statistical uncertainties. Finally, it illustrates the comparison between theory and experiment and discusses future prospects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Chemical and Structural Changes in Corn Stover After Ensiling: Influence on Bioconversion

Production of biofuels, bioproducts, and bioenergy requires a well-characterized, stable, and reasonably uniform biomass supply and well-established supply chains for shipping biomass from farm fields to biorefineries, while achieving year-round production targets. Preserving and stabilizing biomass feedstock during storage is a necessity for cost-effective and sustainable biofuel production. Ensiling is a common storage method used to preserve and even improve forage quality; however, the impact of ensiling on biomass physical and chemical properties that influence bioconversion processes has been variable. Our objective in this work was to determine the effects of ensiling on lignocellulosic feedstock physicochemical properties and how that influences bioconversion requirements. We observed statistically significant decreases (p < 0.05) in the content of two major structural carbohydrates (glucan and xylan) of 5 and 8%, respectively, between the ensiled and non-ensiled materials. We were unable to detect differences in sugar yields from structural carbohydrates after pretreatment and enzymatic hydrolysis of the ensiled materials compared to non-ensiled controls. Based on this work, we conclude that ensiling the corn stover did not change the bioconversion requirements compared to the control samples and incurred losses of structural carbohydrates. At the light microscopy level, ensiled corn stover exhibited little structural change or relocation of cell wall components as detected by immunocytochemistry. However, more subtle structural changes were revealed by electron microscopy, as ensiled cell walls exhibit ultrastructural characteristics such as wall delimitation intermediate between non-ensiled and dilute-acid-pretreated cell walls. These findings suggest that alternative methods of conversion, such as deacetylation and mechanical refining, could take advantage of lamellar defects and may be more effective than dilute acid or hot water pretreatment for biomass conversion of ensiled materials.

09 BIOMASS FUELS↗
NASA NTRS1980

Modeling a maintenance simulation of the geosynchronous platform

A modeling technique used to conduct a simulation study comparing various maintenance routines for a space platform is dicussed. A system model is described and illustrated, the basic concepts of a simulation pass are detailed, and sections on failures and maintenance are included. The operation of the system across time is best modeled by a discrete event approach with two basic events - failure and maintenance of the system. Each overall simulation run consists of introducing a particular model of the physical system, together with a maintenance policy, demand function, and mission lifetime. The system is then run through many passes, each pass corresponding to one mission and the model is re-initialized before each pass. Statistics are compiled at the end of each pass and after the last pass a report is printed. Items of interest typically include the time to first maintenance, total number of maintenance trips for each pass, average capability of the system, etc.

Kleiner, A. F., Jr.↗
NASA NTRS1991

Statistics of premixed flame cells

The statistics of random cellular patterns in premixed flames are analyzed. Agreement is found with a variety of topological relations previously found for other networks, namely, Lewis's law and Aboav's law. Despite the diverse underlying physics, flame cells are shown to share a broad class of geometric properties with other random networks-metal grains, soap foams, bioconvection, and Langmuir monolayers.

Noever, David A.↗
NASA NTRSDate not supplied

Time-History Statistics of Soot Formation in A Model Gas Turbine Combustor

Soot formation is a complex dynamic and intermittent process determined by properties of the fuel, combustor design, and combustor operation. Although the major steps in soot formation (i.e., formation of precursors, inception, growth and evolution) are similar for a variety of carbonaceous fuels, applications, and operating conditions, it remains unclear when the temporal transition between these steps occurs. An engineering prediction tool coupled with computational fluid physics (CFD), therefore needs to accurately model all these complex steps. To develop such a model, we propose the time-history concept for understanding the time dependency of soot formation as a function of local properties (i.e., temperature, velocity, local fuel air ratio, etc.). We continue our previous work with modeling the DLR aero-combustor [1] with our updated in-house CFD code, Open National Combustion Code (OpenNCC), that now includes a Multiple Time-Scale Flamelet Progress Variable approach and a the semi-empirical two-equation soot model. We injected massless tracer particles upstream of the injector region of the combustor to collect time-history statistics of the solution variables. The correlations between the collected statistics with respect to the experimental soot volume fraction data showed that time-history effect of certain flow variables, including turbulent kinetic energy (TKE), and multiple species is indeed important for soot formation. We then conducted a time-history based correlation analysis to determine the key species and the concentration ranges critical for soot formation (C6H5-based nucleation, acetylene-based surface growth, and oxidation with OH and O2). Based on the time-history correlation coefficient (THCC) analysis, we propose possible modifications to improve the current two-equation model.

LES↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Predicting fusion ignition at the National Ignition Facility with physics-informed deep learning

Here, an inertial confinement fusion experiment, carried out at the National Ignition Facility, has achieved ignition by generating fusion energy exceeding the laser energy that drove the experiment. Prior to the experiment, a generative machine learning model that combines radiation hydrodynamics simulations, deep learning, experimental data, and Bayesian statistics was used to predict, with a probability greater than 70%, that ignition was the most likely outcome for this shot.

Spears, Brian K. [Lawrence Livermore National Labo↗
NASA NTRS1989

Collisional rate coefficients of C3H2 and the determination of physical conditions in molecular clouds

Collisional excitation rates for C3H2, calculated using the coupled states approximation at temperatures of 10-30 K, are presented. C3H2 produces a number of spectral line pairs whose members are close together in frequency but arise from levels with different excitation energies. The rates are used in statistical equilibrium calculations to illustrate the excitation properties and density-dependent behavior of various C3H2 line ratios.

Avery, L. W.↗
NASA NTRS2004

Physics of Galaxy Clusters and How it Affects Cosmological Tests

The main activities in 2004 were focused on completion of the new 400 square degrees ROSAT PSPC survey for distant galaxy clusters. We observed and reduced optical spectra for all X-ray candidates and now we have complete identification for a statistically complete sample of distant 283 clusters. The papers describing the cluster catalog and first science results are in preparation and will be submitted in early 2005. We also completed a project to measure temperature and density profiles at large radii using Chandra observations of a 11 well exposed low-redshift clusters. We were able to demonstrate that the density, temperature, and total mass profiles are self-similar at large radii. This analysis has led to significant improvements in determination of the cluster baryon fraction as well as cosmologically important scaling relations, such as Mtot-T. The paper describing these results is submitted to ApJ in November, 2004. We continued to study evolution of the cluster scaling relations at high redshifts using Chandra and XMM data. We developed code for image and spectral deconvolution of the XMM observations. This code was used to reconstruct the distribution of baryons and total mass from observations of distant clusters which suffer from the finite size of the XMM PSF. This study allowed us to derive a high-redshift relation between cluster temperature and mass and compare it with the local relation obtained. The paper describing the first results is submitted to the ApJ. However, the project is still on-going as more distant cluster observations enter XMh4 and Chandra public data archives. We continued our work on improving techniques for accurate measurements of the cluster mass function and obtaining cosmological constraints from such observations. We published (ApJ, 601, 610) a study in which we derived the baryon mass function for a complete sample of low-redshift clusters. These papers argued that it was an excellent proxy for the total mass function. The baryon mass function can be used to constrain the amplitude and slope of the density fluctuation power spectrum on cluster scales. This method does not use observational determinations of the total mass and thus bypasses major uncertainties in the traditional analyses based on the X-ray temperature function. We derived the measurements for the amplitude of density perturbations, sigma8 = 0.72 +/- 0.04 and the shape parameter Omega*h = 0.l3 +/- 0.07, in good agreement with a number of independent methods.

Oliversen, Ronald J.↗
DOE OSTI2023

An over-approximation of entropy for elemental multiconfigurational ground state electronic structures

The ability to predict the chemical and physical properties of a material is directly related to the structure and interactions of its electrons. For materials comprised of f-block elements (the lanthanides and actinides found in the last two rows of the periodic table), the complexity of electronic structure has presented great difficulty in understanding, modeling, and predicting material properties. The complexity of multiconfigurational ground state electronic structures is illustrated herein by the combinatorics of electron permutations within individual and cumulative occupancy configurations. A non-integer orbital occupancy representation of multiconfigurational ground states is described for superposition mixing between multiple near-energy degenerate occupancy configurations and generalized in such a way that established ground states are returned by approximation for elements with less-complex electronic structures. By considering the occupancy configurations as statistical mechanics macrostates, and the permutations of electrons as statistical mechanics microstates within those macrostates, an over-approximation of entropy for multiconfigurational elemental ground state electronic structures has been calculated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2023

Multiyear Dry Periods in Southern Africa

Characteristics and physical features related to low precipitation across many years in Southern Africa that lead to societal disruptions are diagnosed using observed analyses and an ensemble of historical coupled climate model simulations during 1921 to 2014. Four regions are evaluated, as identified through a hierarchical clustering algorithm applied to the Standardized Precipitation Index (SPI) during the October–April precipitation season. Although dryness spanning many October–April occurs periodically in each region, they seldom occur simultaneously, consistent with largely insignificant SPI cross-correlations between them. However, characteristics relevant to low precipitation across many years are generalizable between the four regions, including the serial persistence of October–April precipitation, the likelihood of consecutive dry October–April, and the likelihood of dry October–April in temporal extents of up to 10 consecutive such 7-month seasons. Systematic precipitation persistence is not a feature in any of the four Southern Africa regions, as serial correlations of October–April SPI are not statistically significant at any time lags. It follows that there is an exponential-folding decay in the likelihood of consecutive October–April for various SPI thresholds and that there is a large spread in the likelihood of low October–April SPI across many years. In terms of physical features, low October–April SPI in each Southern Africa region is closely related to local atmospheric circulations; however, they are not as closely related to sea surface temperatures (SSTs). These results suggest that dryness spanning many years is determined primarily by persistent local circulations related to atmospheric variability and to a lesser extent variability related to SST anomalies, including the El Niño–Southern Oscillation.

subtropical Indian Ocean dipole↗