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DOE OSTI2018

BigData Express: Toward Predictable, Schedulable, and High-Performance Data Transfer [Slides]

Big data has emerged as a driving force for scientific discoveries. Large scientific instruments (e.g., colliders, and telescopes) generate exponentially increasing volumes of data. To enable scientific discovery, science data must be collected, indexed, archived, shared, and analyzed, typically in a widely distributed and highly collaborative manner. Data transfer is now an essential function for science discoveries, particularly within big data environments. To support data transfer for big data science, there is a need for predictable, high performance, scalable, end-to-end, programmable networks that enable science applications to use network resources most efficiently. Software-Defined Networking (SDN) is a novel network architecture and technological approach that separates the network control and data planes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Chemical Analysis of Tantalum Thin Films compared to Niobium Thin Films using SIMS and XPS

Superconducting qubits are a leading platform for quantum computation. These circuits are typically made from superconducting materials like aluminum or niobium. However, the amorphous niobium oxide and aluminum oxide on the surface of these circuits introduce considerable RF loss due to the presence of two-level systems (TLS), which limits the maximum coherence times T1 to ~100 μs. Capping the niobium qubits with a tantalum layer leads to a 3- 5x improvement [Bal et al., 2024]. But even in this case, tantalum forms an amorphous surface oxide that introduces loss. In an effort to devise strategies to eliminate the presence of this oxide, we present a comprehensive study on the nature of Ta oxide using x-ray photoemission spectroscopy (XPS) and secondary ion mass spectrometry (ToF-SIMS) as a function of heat treatment. The thin films were annealed in ultra-high vacuum conditions and analyzed in situ to characterize the composition and evolution of the native tantalum oxide layer and oxide-metal interface. Our analysis reveals two critical differences between tantalum and niobium oxides: Nb2O5 completely dissolves at 400°C, while Ta2O5 persists even at 800°C. Additionally, tantalum oxide contains only a single suboxide (TaO), in contrast to niobium's two suboxides (NbO and NbO2). The suboxide of tantalum contributes minimally to the total oxide content and shows a relative increase with temperature. Understanding the oxide’s behavior will open new pathways for optimizing coherence times in tantalum qubits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Imaging of Unstained DNA Origami Triangles with Electron Microscopy

Imaging of scaffolded DNA and DNA origami nanostructures has been dominated by atomic force microscopy of samples immobilized on bulk substrates. Less commonly used for DNA imaging are electron microscopy techniques, which are typically carried out either after negative staining of DNA or by direct imaging using a bright field cryo-TEM. Here, direct imaging of unstained DNA origami nanostructures on thin electron-transparent substrates utilizing high angular annular dark field scanning transmission electron microscopy )(HAADFSTEM) is reported. This approach establishes a simple method for depositing and imaging intact DNA triangles with mass-thickness contrast, sufficient to measure the scaffold-to-scaffold distances and the length of the triangle’s seam. The signal-to-noise ratio (SNR) of the DNA supported on amorphous carbon as a function of the carbon thickness is measured on three types of commercially available TEM grids to analyze the image resolution. This allows for an edge detection of ~1 nm height DNA triangles on carbon substrates as thick as ~25 nm. Additional observations on the effect on SNR with the imaging modes are discussed. The effect of cation concentration used for pre-treating the grid surface on the image resolution is also explored. Our work presents proof-of-concept results demonstrating that electron microscopy can be utilized to resolve key elements of the DNA origami triangle, without staining or employing exceedingly complicated preparation protocols.

Londono-Calderon, Alejandro↗

DOE OSTI2023

Influence of the Graft Length on Nanocomposite Structure and Interfacial Dynamics

Both the dispersion state of nanoparticles (NPs) within polymer nanocomposites (PNCs) and the dynamical state of the polymer altered by the presence of the NP/polymer interfaces have a strong impact on the macroscopic properties of PNCs. In particular, mechanical properties are strongly affected by percolation of hard phases, which may be NP networks, dynamically modified polymer regions, or combinations of both. In this article, the impact on dispersion and dynamics of surface modification of the NPs by short monomethoxysilanes with eight carbons in the alkyl part (C 8 ) is studied. As a function of grafting density and particle content, polymer dynamics is followed by broadband dielectric spectroscopy and analyzed by an interfacial layer model, whereas the particle dispersion is investigated by small-angle X-ray scattering and analyzed by reverse Monte Carlo simulations. NP dispersions are found to be destabilized only at the highest grafting. The interfacial layer formalism allows the clear identification of the volume fraction of interfacial polymer, with its characteristic time. The strongest dynamical slow-down in the polymer is found for unmodified NPs, while grafting weakens this effect progressively. The combination of all three techniques enables a unique measurement of the true thickness of the interfacial layer, which is ca. 5 nm. Finally, the comparison between longer (C 18 ) and shorter (C 8 ) grafts provides unprecedented insight into the efficacy and tunability of surface modification. It is shown that C 8 -grafting allows for a more progressive tuning, which goes beyond a pure mass effect.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Microphysics in the Gamma-Ray Burst Central Engine

We calculate the structure and evolution of a gamma-ray burst central engine where an accreting torus has formed around the newly born black hole. We study the general relativistic, MHD models and we self-consistently incorporate the nuclear equation of state. The latter accounts for the degeneracy of relativistic electrons, protons, and neutrons, and is used in the dynamical simulation, instead of a standard polytropic γ -law. The EOS provides the conditions for the nuclear pressure in the function of density and temperature, which evolve with time according to the conservative MHD scheme. We analyze the structure of the torus and outflowing winds, and compute the neutrino flux emitted through the nuclear reaction balance in the dense and hot matter. We also estimate the rate of transfer of the black-hole rotational energy to the bipolar jets. Finally, we elaborate on the nucleosynthesis of heavy elements in the accretion flow and the wind, through computations of the thermonuclear reaction network. We discuss the possible signatures of the radioactive element decay in the accretion flow. We suggest that further detailed modeling of the accretion flow in the GRB engine, together with its microphysics, may be a valuable tool to constrain the black-hole mass and spin. It can be complementary to the gravitational wave analysis if the waves are detected with an electromagnetic counterpart.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

StOKeDMD: Streaming Occupation kernel dynamic mode decomposition

Dynamic mode decomposition (DMD) has become a common technique for constructing surrogate models for dynamical systems from observed system states. The Occupation Kernel DMD (OKDMD) method proposed in (Rosenfeld et al., 2022) and (Rosenfeld et al., 2024) is a Liouville operator based method that builds surrogate models from system state trajectories. Here, this paper proposes an extension of OKDMD to the case when the system states are observed in a streaming fashion, i.e., only a small fraction of the state trajectory is available at a given time. The developed method, Streaming Occupation Kernel DMD (StOKeDMD), accommodates the streaming data input by leveraging properties of specific choices of kernel functions and occupation kernels. We apply the StoKeDMD method as a compression method for streaming data, analyze the memory complexity, and demonstrate the performance of StoKeDMD in the compression of streaming data generated from a Lorenz system and a fluid flow simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Demonstrating SolarPILOT's Python API Through Heliostat Optimal Aimpoint Strategy Use Case: Preprint

SolarPILOT is a software package that generates heliostat field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL's System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application's graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called "LK." This paper presents a new, full-featured Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT's capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instances with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layout; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying heliostat field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating heliostat field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed tower CSP analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot's functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize CSP tower research.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2024

Addressing Failures in Molten Salt Thermal Energy Storage Tank for Central Receiver Concentrating Solar Power Plants

The thermal energy storage (TES) system is a critical component in concentrated solar power (CSP) plants that increases the plant's capacity factor and economic competitiveness by reducing the levelized cost of energy (LCOE) while simultaneously increasing the value of the delivered energy. Failures including molten-salt leaks and diverse localized cracking after several months to a few years of operation have been reported in hot tanks for CSP plants operating around the world. A model of a molten salt thermal energy storage tank was developed and validated to analyze the impact of different tank design features on the temperature and stress distributions as a function of typical plant operation conditions. Design features included the floor plate thicknesses, friction coefficients between the tank floor and the foundation, and the sparger ring location. Maximum stresses in the tank floor frequently surpassed the yield point of the material during operation, leading to a detriment of the tank's lifetime. Recommendations on design features to improve the reliability of new molten salt tanks for CSP plants are provided.

concentrating solar power↗

DOE OSTI2017

Brownian motion of a plasma crystal

The dynamics of a plasma crystal under the action of random external forces is considered. The pair correlation functions of the particle displacements are calculated in the harmonic approximation by using the Langevin equations. The case of a planar hexagonal lattice is analyzed in more detail. Analogues of the Van Hove singularities in the spectral densities are discovered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗

DOE OSTI2022

Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those new security components into different groups according to their purpose and deployment scope. We propose to analyze them in the context of existing 5G architectures using two different approaches. First, using model checking techniques, we will evaluate the probability of an attacker to be successful against each security solution. Second, using analytical models, we will analyze the impact of these security mechanisms in terms of delay, throughput consumption, and reliability. Finally, we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture. Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced, dedicated non-native mechanisms could only guarantee secure URLLC with a probability of ~55%.

5G networks↗

DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗

DOE OSTI2017

Measurement of double-differential cross sections for top quark pair production in pp collisions at $\sqrt{s} = 8$ $\,\text {TeV}$ and impact on parton distribution functions

Normalized double-differential cross sections for top quark pair ( $\mathrm{t}\overline{\mathrm{t}}$ ) production are measured in pp collisions at a centre-of-mass energy of 8 $\,\text {TeV}$ with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 19.7 $\,\text {fb}^{-1}$ . The measurement is performed in the dilepton $\mathrm {e}^{\pm }\mu ^{\mp }$ final state. The $\mathrm{t}\overline{\mathrm{t}}$ cross section is determined as a function of various pairs of observables characterizing the kinematics of the top quark and $\mathrm{t}\overline{\mathrm{t}}$ system. The data are compared to calculations using perturbative quantum chromodynamics at next-to-leading and approximate next-to-next-to-leading orders. They are also compared to predictions of Monte Carlo event generators that complement fixed-order computations with parton showers, hadronization, and multiple-parton interactions. Overall agreement is observed with the predictions, which is improved when the latest global sets of proton parton distribution functions are used. The inclusion of the measured $\mathrm{t}\overline{\mathrm{t}}$ cross sections in a fit of parametrized parton distribution functions is shown to have significant impact on the gluon distribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Investigation of Transport Parameters of Graphene-Based Nanostructures

The paper presents results of computer simulation of the main transport parameters of nanostructures obtained through the row-by-row removal of carbon atoms from graphene ribbon. Research into the electrical parameters is carried out within the density functional theory using the non-equilibrium Green functions in the local-density approximation. Virtual NanoLab based on Atomistix ToolKit is used to construct structures and analyze simulation results. Current-voltage characteristics, differential conductivity and transmittance spectra of nanostructures are calculated at different values of bias voltage. It is found that there is a large region of negative differential resistance in current-voltage characteristics of nanostructures caused by resonant tunneling of quasi-particles. Differential (dI/dV) characteristic also has similar changes. The obtained results can be useful for building novel electronic devices in the field of nanoelectronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Use of vibrational spectroscopy to identify the formation of neptunyl–neptunyl interactions: a paired density functional theory and Raman spectroscopy study

Actinyl–Actinyl interactions (AAIs) occur in pentavalent actinide systems, particularly for neptunium (Np), and lead to complex vibrational signals that are challenging to analyze and interpret. Previous studies have focused on neptunyl–neptunyl dimeric species, but trimers and tetramers have been identified as the primary motif for extended topologies observed in solid-state materials. Our hypothesis is that trimeric and tetrameric AAIs lead to the additional signals in the vibrational spectra, but this has yet to be explored systematically. Herein, we investigate three different neptunyl–neptunyl subunits (dimeric, trimeric, tetrameric) and determine the vibrational frequencies of the O=Np=O stretches using both computational and experimental approaches. Density Functional Theory (DFT) was used to identify distinct vibrational motions related to specific neptunyl oligomers and compared to previous literature precedent from Np(V) in HClO 4 and HCl systems. The vibrational behavior of Np(V) in HNO 3 was then evaluated via Raman spectroscopy. As the solution evaporated signals were linked to trimeric and tetrameric models. Solid phases produced in the evaporation include (NpO 2 ) 2 (NO 3 ) 2 (H 2 O) 5 and newly identified crystalline phase, Na(NpO 2 )(NO 3 ) 2 ·4H 2 O (NpNa). Furthermore, the combined computational studies and vibrational analysis provide evidence for unique observable vibrational bands for each polymerized subunit, allowing us to assign spectral features to trimeric and tetrameric models within three different simple anionic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Fire affects the taxonomic and functional composition of soil microbial communities, with cascading effects on grassland ecosystem functioning

Fire is a crucial event regulating the structure and functioning of many ecosystems. Yet few studies have focused on how fire affects taxonomic and functional diversities of soil microbial communities, along with changes in plant communities and soil carbon (C) and nitrogen (N) dynamics. Here, we analyze these effects in a grassland ecosystem 9 months after an experimental fire at the Jasper Ridge Global Change Experiment site in California, USA. Fire altered soil microbial communities considerably, with community assembly process analysis showing that environmental selection pressure was higher in burned sites. However, a small subset of highly connected taxa was able to withstand the disturbance. In addition, fire decreased the relative abundances of most functional genes associated with C degradation and N cycling, implicating a slowdown of microbial processes linked to soil C and N dynamics. In contrast, fire stimulated above- and belowground plant growth, likely enhancing plant-microbe competition for soil inorganic N, which was reduced by a factor of about 2. To synthesize those findings, we performed structural equation modeling, which showed that plants but not microbial communities were responsible for significantly higher soil respiration rates in burned sites. Together, our results demonstrate that fire 'reboots' the grassland ecosystem by differentially regulating plant and soil microbial communities, leading to significant changes in soil C and N dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Improving the Field Portability of Neutron and Gamma Counting Techniques

Savannah River National Laboratory (SRNL) puts science to work by developing techniques that better meet customers needs for in-situ measurements. There is high demand for laboratory quality measurements in field situations, improving the cost and speed for first responders and environmental monitoring. This work focused on two improvements (1) reading a signal from a neutron detector using a Raspberry Pi (2) testing the Peak-to-Valley method for determining the depth of a source in soil contamination measurements. A Raspberry Pi is a cheap, compact computer. This affordable, compact computer is able to do simple tasks that a desktop computer is able to do, like spreadsheets, browse the internet, play games and even program a simple robot. Additionally, a Raspberry Pi can run off of a battery, so it could be deployed for long term measurements in adverse conditions like neutron monitors deployed in a shipping port. Using the Raspberry Pi and libraries easily accessible on the internet, a code was written in Python that allows the Pi to keep track of how many times a button is pushed. This work will be used with the future goal of creating low power-budget neutron detectors. 1) Make sure Python was correctly installed on the Raspberry Pi. 2) Write a code that will keep track of how many times a button connected to the Pi is pressed. A code was written to use the Raspberry Pi to count the number of times the button was pushed. Moving forward the Raspberry Pi will be tested with a neutron counter. Ideally, each signal from the neutron pulse will be equivalent of 'push the button' and be counted. In the characterization of a soil contamination area both the location and the depth of the source is important. Attenuation of the source by the soil can make determining its depth challenging, particularly for monoenergetic radionuclides like Cs-137. To address this issue, a method of calculating the 'peak-to-valley' ratio of the gamma count spectra is implemented to help calculate the known depth of the source. 1) Determine the 'peak-to-valley' ratio of a Cs-137 source at different depths. 2) Find an appropriate function to serve as a model for the peak-to-valley ratio as a function of depth. Several Petri dishes, filled with sand, were stacked with one containing a Cs-137 source. The individual Petri dishes allowed for the source to be placed at different depths. A bucket was placed over the sand and source, to keep the detector at a consistent height. A Petri dish containing a Eu-155 source, which acted as an internal calibration standard, was placed on top of the bucket. A NaI detector was place on top of the Eu-155 source and the assembly was surrounded by a tungsten shield. Count times were 20 minutes and the data was analyzed using PeakEasy. Data was recorded for Cs-137 at a series of depths in sand. Both exponential and logarithmic functions provided a reasonable fit to the data. The experimental data showed a decreasing 'peak-to-valley' ratio as the depth was increased. The next steps for this project involves determining the optimum fit function and combining the results from sand to different soil types to get a better representation of the soil found at SRS. Eventually, the peak-to-valley ratio will be used to estimate the depth of contamination in field measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Designing Imidazolium Poly(amide-amide) and Poly(amide-imide) Ionenes and Their Interactions with Mono- and Tris(imidazolium) Ionic Liquids

Here we introduce the synthesis and thermal properties of a series of sophisticated imidazolium ionenes with alternating amide-amide or amide-imide backbone functionality, and investigate the structural effects of mono(imidazolium) and unprecedented tris(imidazolium) ionic liquids (ILs) in these ionenes. The new set of poly(amide-amide) (PAA) and poly(amide-imide) (PAI) ionenes represent the intersection of conventional high-performance polymers with the ionene archetype–presenting polymers with alternating functional and ionic elements precisely sequenced along the backbone. The effects of polymer composition on the thermal properties and morphology were analyzed. Five distinct polymer backbones were synthesized and combined with a stoichiometric equivalent of the IL 1-benzyl-3-methylimidazolium bistriflimide ([Bnmim][Tf 2 N]), which were studied to probe the self-assembly, structuring, and contributions of intermolecular forces when IL is added. Furthermore, three polyamide (PA) or polyimide (PI) ionenes with simpler xylyl linkages were interfaced with [Bnmim][Tf 2 N] as well as a novel amide-linked tris(imidazolium) IL, to demonstrate the structural changes imparted by the inclusion of functional, ionic additives dispersed within the ionene matrix. This work highlights the possibilities for utilizing concepts from small molecules which exhibit supramolecular self-assembly to guide creative design and manipulate the structuring of ionenes.

36 MATERIALS SCIENCE↗