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DOE OSTI2024

A soft departure from jamming: the compaction of deformable granular matter under high pressures

Here, the high-pressure compaction of three-dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by bonds. A simple multibody interaction is introduced to control Poisson's ratio and the arrangement of particles on the surface of a grain is varied to model both high- and low-frictional grains. At low pressures, the growth in packing fraction and coordination number follows the expected behavior near jamming and exhibit friction dependence. As the pressure increases, deviations from the low-pressure power-law scaling emerge after the packing fraction grows by approximately 0.1 and results from simulations with different friction coefficients converge. These results are compared to predictions from traditional discrete element method simulations which, depending on the definition of packing fraction and coordination number, may only differ by a factor of two. As grains deform under compaction, the average volumetric strain and asphericity, a measure of the change in the shape of grains, are found to grow as power laws and depend heavily on the Poisson's ratio of the constituent solid. Larger Poisson's ratios are associated with less volumetric strain and more asphericity and the apparent power-law exponent of the asphericity may vary. The elastic properties of the packed grains are also calculated as a function of packing fraction. In particular, we find the Poisson's ratio near jamming is 1/2 but decreases to around 1/4 before rising again as systems densify.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Diffusion of Brønsted acidic dopants in conjugated polymers

Many semiconductor devices (e.g., light emitting diodes and photovoltaics) utilize heterojunctions of doped and undoped layers or depend on gradients of electronic doping to control charge transport. Understanding of the formation and stability of gradients in doping requires an understanding of diffusion of dopants and the complex changes in polymer properties that arise during doping. Conjugated polymers can be electrically doped by strong acids, but the details of the reaction mechanism and subsequent stability are not understood. Here, we show a clear kinetic isotope effect in the doping of thin films of poly(3-hexylthiophene) (P3HT) by bis(trifluoromethane)sulfonimide (HTFSI) from solution indicating that this doping process is limited by proton transfer to the polymer. Complementary X-ray photoelectron spectroscopy and dynamic secondary ion mass spectrometry (DSIMS) depth profiling of dopant concentrations show definitive evidence of dopant enrichment at the P3HT surface. These surface-limited concentration profiles suggest that diffusivity of dopants vary inversely with dopant concentration due to doping-induced changes to the structure of the conjugated polymer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Unifying thermochemistry concepts in computational heterogeneous catalysis

Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange–correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Physics-based reward driven image analysis in microscopy

The rise of electron microscopy has expanded our ability to acquire nanometer and atomically resolved images of complex materials. The resulting vast datasets are typically analyzed by human operators, an intrinsically challenging process due to the multiple possible analysis steps and the corresponding need to build and optimize complex analysis workflows. We present a methodology based on the concept of a Reward Function coupled with Bayesian Optimization, to optimize image analysis workflows dynamically. The Reward Function is engineered to closely align with the experimental objectives and broader context and is quantifiable upon completion of the analysis. Here, cross-section, high-angle annular dark field (HAADF) images of ion-irradiated (Y, Dy)Ba 2 Cu 3 O 7–δ thin-films were used as a model system. The reward functions were formed based on the expected materials density and atomic spacings and used to drive multi-objective optimization of the classical Laplacian-of-Gaussian (LoG) method. These results can be benchmarked against the DCNN segmentation. This optimized LoG* compares favorably against DCNN in the presence of the additional noise. We further extend the reward function approach towards the identification of partially-disordered regions, creating a physics-driven reward function and action space of high-dimensional clustering. We pose that with correct definition, the reward function approach allows real-time optimization of complex analysis workflows at much higher speeds and lower computational costs than classical DCNN-based inference, ensuring the attainment of results that are both precise and aligned with the human-defined objectives.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

Evaluating Np(v) disproportionation: effect of Np concentration

The role of Np(V) concentration as a potential chemical driver of Np(V) disproportionation was investigated by probing Np redox chemistry in two different acid media using visible-near-infrared absorbance spectroscopy. In situ spectroscopy of chemically and electrochemically manipulated Np oxidation states at molar concentrations of Np underscores the difficulty in stabilizing pure Np(V), even in dilute acid. A Np(VI) component coexisting with the majority Np(V) component was observed in both HNO 3 and HCl. Electrochemical tuning and subsequent spectroscopic analysis of the Np(VI/V) ratio revealed neptunyl self-complexation as a key mechanism occurring in both acid media. Chemical reduction of the Np(VI) component and stabilization of a minor Np(IV) component in HNO 3 were observed; however, spectral data indicated that these two oxidation states were not observed to coexist, and pure Np(V) was stabilized only briefly. These findings demonstrate that high Np concentrations significantly affect the redox chemistry of Np in acidic solutions. Finally, the occurrence of Np(V) disproportionation could not be definitely determined by spectral data, but other mechanisms such as self-complexation and radiolysis, which potentially compete with disproportionation, must be considered.

Gilson, Sara E. [Oak Ridge National Laboratory (OR↗

DOE OSTI2020

Resilient distribution system leveraging distributed generation and microgrids: a review

With the aging of electricity transmission and distribution infrastructures and increasing intensity of extreme weather events, the aggravated vulnerability of electric distribution systems to extreme weather events has motivated the study of resilient distribution systems. This study presents a review of the state-of-the-art research on distribution grid resilience. First, the definition and quantifying metrics of resilience in the electrical distribution system are summarised. Second, the long-term and short-term measures to enhance the distribution system resilience are discussed. In particular, the recent studies on distributed generation and microgrid-assisted resilience enhancements are reviewed. Finally, recommendations for future research are presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Clustering of CODEX clusters

The clustering of galaxy clusters links the spatial nonuniformity of dark matter halos to the growth of the primordial spectrum of perturbations. The amplitude of the clustering signal is widely used to estimate the halo mass of astrophysical objects. The advent of cluster mass calibrations enables using clustering in cosmological studies. Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the ROentgen SATellite All-Sky Survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the Sloan Digital Sky Survey. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations. Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the 0.1 < z < 0.3 and 0.3 < z < 0.5 redshift bins. We compared the bias in the measured correlation function with values obtained in numerical simulations using a similar cluster mass range. Results. By fitting a power law, we measured a correlation length r 0 = 18.7 ± 1.1 and slope γ = 1.98 ± 0.14 for the correlation function in the full redshift range. By fixing the other cosmological parameters to their nine-year Wilkinson Microwave Anisotropy Probe values, we reproduced the observed shape of the correlation function under the following cosmological conditions: Ω m0 = $0.22_{-0.03}^{+0.04}$ and S 8 = σ 8 (Ω m0 /0.3)0.5 = $0.85_{-0.08}^{+0.10}$ with estimated additional systematic errors of σ Ω m0 = 0.02 and σS 8 = 0.20. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving Ωm = 0.25 ± 0.01 and σ 8 = $0.81_{-0.02}^{+0.01}$ with an estimated additional systematic error of σ Ω m0 = 0.07 and σ σ8 = 0.04. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

ConKer: An algorithm for evaluating correlations of arbitrary order

Context. High order correlations in the cosmic matter density have become increasingly valuable in cosmological analyses. However, computing these correlation functions is computationally expensive. Aims. We aim to circumvent these challenges by developing a new algorithm called ConKer for estimating correlation functions. Methods. This algorithm performs convolutions of matter distributions with spherical kernels using FFT. Since matter distributions and kernels are defined on a grid, it results in some loss of accuracy in the distance and angle definitions. We study the algorithm setting at which these limitations become critical and suggest ways to minimize them. Results. ConKer is applied to the CMASS sample of the SDSS DR12 galaxy survey and corresponding mock catalogs, and is used to compute the correlation functions up to correlation order n = 5. We compare the n = 2 and n = 3 cases to traditional algorithms to verify the accuracy of the new algorithm. We perform a timing study of the algorithm and find that three of the four distinct processes within the algorithm are nearly independent of the catalog size N , while one subdominant component scales as O ( N ). The dominant portion of the calculation has complexity of O ( N c 4/3 log N c ), where N c is the of cells in a three-dimensional grid corresponding to the matter density. Conclusions. We find ConKer to be a fast and accurate method of probing high order correlations in the cosmic matter density, then discuss its application to upcoming surveys of large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Candidate cosmic filament in the GJ526 field, mapped with the NIKA2 camera

Distinctive large-scale structures have been identified in the spatial distribution of optical galaxies up to redshift z ~ 1. In the more distant universe, the relationship between the dust-obscured population of star-forming galaxies observed at millimetre wavelengths and the network of cosmic filaments of dark matter apparent in all cosmological hydrodynamical simulations is still under study. Using the NIKA2 dual-band millimetre camera, we mapped a field of ~90 arcmin 2 in the direction of the star GJ526 simultaneously in its 1.15-mm and 2.0-mm continuum wavebands to investigate the nature of the quasi-alignment of five sources found ten years earlier with the MAMBO camera at 1.2 mm. We find that these sources are not clumps of a circumstellar debris disc around this star as initially hypothesized. Rather, they must be dust-obscured star-forming galaxies, or sub-millimetre galaxies (SMGs), in the distant background. The new NIKA2 map at 1.15 mm reveals a total of seven SMGs distributed in projection on the sky along a filament-like structure crossing the whole observed field. Furthermore, we show that the NIKA2 and supplemental Herschel photometric data are compatible with a model of the spectral energy distributions (SEDs) of these sources when a common redshift of 2.5 and typical values of the dust parameters for SMGs are adopted. Hence, we speculate that these SMGs might be located in a filament of the distant ‘cosmic web’. The length of this candidate cosmic filament crossing the whole map is at least 4 cMpc (comoving), and the separations between sources are between 0.25 cMpc and 1.25 cMpc at this redshift, in line with expectations from cosmological simulations. Nonetheless, further observations to determine the precise spectroscopic redshifts of these sources are required to definitively support this hypothesis of SMGs embedded in a cosmic filament of dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field

Size is a fundamental parameter for measuring the growth of galaxies and the role of the environment on their evolution. However, the conventional size definitions used for this purpose are often biased and miss the diffuse, outermost signatures of galaxy growth, including star formation and gas accretion. We address this issue by examining low surface brightness truncations or galaxy ‘edges’ as a physically motivated tracer of size based on star formation thresholds. Our total sample consists of ∼900 galaxies with stellar masses ranging from 10 5 M ⊙ < M ⋆ < 10 11 M ⊙ . This sample of nearby cluster, group satellite, and nearly isolated field galaxies was compiled using multi-band imaging from the Fornax Deep Survey, deep IAC Stripe 82, and Dark Energy Camera Legacy Surveys. We find that the edge radii scale as R edge ∝ M ⋆ 0.42 , with a very small intrinsic scatter (∼0.07 dex). The scatter is driven by the morphology and environment of galaxies. In both the cluster and field, early-type dwarfs are systematically smaller by approximately 20% compared to late-type dwarfs. However, galaxies in the Fornax cluster are the most impacted. At a fixed stellar mass, edges in the cluster can be found at about 50% smaller radii, and the average stellar surface density at the edges is a factor of two higher, ∼1 M ⊙ /pc 2 . Our findings support the rapid removal of loosely bound neutral hydrogen (H I ) in hot, crowded environments, which truncates galaxies outside-in earlier, preventing the formation of more extended sizes and lower density edges. Our results highlight the importance of deep imaging surveys to the study of low surface brightness imprints of the large-scale structure and environment on galaxy evolution.

Astronomy & Astrophysics↗

DOE OSTI2025

Infalling ultra-faint dwarfs as emissaries of the Axiverse

Recent discoveries of ultra-faint dwarf galaxies (UFDs) infalling onto the Milky Way, namely Leo K & M at r ≃ 450 kpc, considerably strengthens the case that UFDs constitute a distinct galaxy class that is inherently smaller and fainter, and metal-poorer than the classical dwarf spheroidals (dSph). This distinction is at odds with the inherent continuity of galaxy halo masses formed under scale-free gravity for any standard dark-matter (DM) model. Here, we show that distinct galaxy classes do evolve in cosmological simulations of multiple light bosons representing the “Axiverse” proposal of string theory, where a discrete mass spectrum of axions is generically predicted to span many decades in mass. In this context, the observed UFD class we show corresponds to a relatively heavy boson of 3 × 10 −21 eV, including Leo K & M, whereas a lighter axion of 10 −22 eV comprises the bulk of DM in all larger galaxies including the dSphs. Although Leo M is larger in size than Leo K, we predict its velocity dispersion to be smaller ( ≃ 1.7 km/s) than that of Leo K ( ≃ 4.5 km/s) because of the inverse de Broglie scale dependence on momentum. This scenario can be definitively tested using millisecond pulsars close to the Galactic center, where the Compton frequencies of the heavy and light bosons imprint monotone timing residuals that may be detected by the Square Kilometre Array (SKA) on timescales of approximately one week and four months, respectively.

dark matter↗

DOE OSTI2021

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Kubernetes for the Deep Underground Neutrino Experiment Data Acquisition

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino experiment based in the USA which is expected to start taking data in 2029. DUNE aims to precisely measure neutrino oscillation parameters by detecting neutrinos from the LBNF beamline (Fermilab) at the Far Detector, 1,300 kilometres away, in South Dakota at the Sanford Underground Research Facility. The Far Detector will consist of four cryogenic Liquid Argon Time Projection Chamber detectors of 17 kT, each producing more than 1 TB/sec of data. The main requirements for the data acquisition system are the ability to run continuously for extended periods of time, with a 99% up-time requirement, and the functionality to record both beam neutrinos and low energy neutrinos from the explosion of a neighbouring supernova, should one occur during the lifetime of the experiment. The key challenges are the high data rates that the detectors generate and the deep underground environment, which places constraints on power and space. To overcome these challenges, DUNE plans to use a highly optimised C++ software suite and a server farm of about 110 nodes continuously running about two hundred multicore processes located close to the detector, 1.5 kilometres underground. Thirty nodes will be at the surface and will run around two hundred processes simultaneously. DUNE is studying the use of the Kubernetes framework to manage containerised workloads and take advantage of its resource definitions and high up-time services to run the DAQ system. Progress in deploying these systems at the CERN neutrino platform on the prototype DUNE experiments is reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Cost Analysis of Annual and Monthly Net Zero Energy Performance for Multifamily Buildings in the United States

As the United States continues its progress toward sustainable construction, net zero building design is becoming an increasingly important and popular topic. Two definitions of net zero energy performance, monthly and annual, provide different levels of energy autonomy and efficiency within a building. This article analyzes the viability and incremental cost for two-, three-, and four-story multifamily apartment buildings to reach both annual and monthly net zero energy performance throughout four climate zones in the United States using baseline reference buildings that represent current construction practices. Building size plays a large role in determining the capability for a building model to reach annual or monthly net zero. Two-story buildings are capable of reaching annual net zero with an increase in construction cost of about 4.4–5.6%. Three-story buildings in warmer climates can achieve annual net zero with an increase of about 5.1%, but models in colder climates cannot reach annual net zero performance. Four-story buildings cannot achieve net zero, owing to insufficient building area for solar arrays to produce electricity. Monthly net zero energy performance was significantly harder to achieve, with the only case reaching this goal being the two-story Houston based model, at an added cost of 8.2%. Generally speaking, only small buildings in warm climates will be able to achieve monthly net zero without vastly oversizing photovoltaic systems and increasing costs without adequate payback.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗

DOE OSTI2020

Nonlinear coupling of electromagnetic and electron acoustic waves in multi-species degenerate astrophysical plasma

Nonlinear wave-coupling is studied in a multispecies degenerate astrophysical plasma consisting of two electron species (at different temperatures): a highly degenerate main component plus a smaller classical relativistic flow immersed in a static neutralizing ion background. It is shown that the high frequency electromagnetic waves through their strong nonlinear interactions with the electron-acoustic waves [sustained by a multielectron component (degenerate) plasma surrounding a compact astrophysical object] can scatter to lower frequencies so that the radiation observed faraway will be spectrally shifted downward. It is also shown that, under definite conditions, the electromagnetic waves could settle into stationary solitonic states. It is expected that the effects of such structures may persist as detectable signatures in forms of modulated micropulses in the radiation observed far away from the accreting compact object. Both these effects will advance our abilities to interpret the radiation coming out of the compact objects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Theory of ignition and burn propagation in inertial fusion implosions

A detailed analytic model is presented here to investigate the physics of burn propagation in inertially confined plasmas. The onset of ignition and burn propagation occurs when alpha heating of the hot spot causes rapid ablation of shell mass into the hot spot. This allows large energy gains to be achieved since most of the fuel mass is located in the shell. Here, we first present a comprehensive review of previous analytic models that have been used to describe the physics of hot-spot evolution and ignition; we then show that a proper description of a propagating burn wave requires a comprehensive model of hot spot and shell evolution that includes proper mass conservation in the shell, fusion reactivity, and fuel depletion. The analytic theory is in good agreement with detailed radiation-hydrodynamic simulations that predict the onset of burn propagation as occurring when the yield enhancement caused by alpha heating is between 15- and 25-fold, $f_α$ ~ 1.4, where $f_α$ = alpha energy deposited/hot-spot energy at bang time, and the hot-spot burnup fraction is approximately 2%. We show that the definition of ignition is not sensitive to the alpha-particle stopping power nor asymmetries provided that the absorbed fraction of alpha particles $θ_α$ is correctly accounted for. Finally, we use the results of 2-D simulations to show that even when $θ_α$ is small and unknown (as is true in hot spots with mid modes that have significant leakage of alpha particles into the surrounding cold bubbles), one can still relate the experimentally measureable parameter $\chi^{53}_α$ to the yield amplification and the burning-plasma parameter $Q^{\text{hs}}_α$ = alpha energy deposited/total input work delivered to the hot spot

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗