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At least 343 records · Page 19

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DOE OSTI2020

Effect of mammalian mesopredator exclusion on vertebrate scavenging communities

Carrion is a valuable resource used by facultative scavengers across the globe. Due to conficts with humans, many vertebrate scavengers have experienced population declines due to direct persecution or indirect efects of human activities. However, little is known about the implications of altered scavenger community composition on the fate and efciency of carrion removal within ecosystems. In particular, mammalian mesopredators are efcient scavengers that are often subjected to control, thus, it is important to understand how the reduction of this scavenger guild infuences the fate of carrion resources and efciency of carrion removal within ecosystems. We evaluated the infuence of the absence of mammalian mesopredators on vertebrate scavenging dynamics by comparing the efciency of carrion removal and species composition at carrion between sites where we experimentally manipulated mesopredator abundance and paired control sites. Overall scavenging rates were high, even within our mesopredator exclusion sites (79% of carcasses). Despite the exclusion of an entire guild of dominant scavengers, we saw little efect on scavenging dynamics due to the extensive acquisition of carrion by avian scavengers. However, we observed a slight reduction in vertebrate scavenging efciency in sites where mesopredators were excluded. Our results suggest vertebrate communities are highly efcient at carrion removal, as we saw a functional response by avian scavengers to increased carrion availability. These data provide insights into the impact of mesopredator control on food web dynamics, and build upon the growing body of knowledge investigating the role of vertebrate scavengers on ecosystem services provided through carrion removal.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Grain size and structure distortion characterization of α-MgAgSb thermoelectric material by powder diffraction

Nanostructuring, structure distortion and/or disorder are the main manipulation techniques to reduce the lattice thermal conductivity and improve the figure of merit of thermoelectric materials. A single-phase α-MgAgSb sample, MgAg 0.97 Sb 0.99 , with high thermoelectric performance in near room temperature region was synthesized through a high-energy ball milling with a hot-pressing method. In this work, we report the average grain size of 24-28 nm and the accurate structure distortion, which are characterized by high-resolution neutron diffraction and synchrotron X-ray diffraction with Rietveld refinement data analysis. Both the small grain size and the structure distortion have a contribution to the low lattice thermal conductivity in MgAg 0.97 Sb 0.99 .

36 MATERIALS SCIENCE↗

DOE OSTI2025

Autonomous platform for solution processing of electronic polymers

The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. We introduce Polybot, an artificial intelligence (AI) driven automated material laboratory designed to autonomously explore processing pathways for achieving high-conductivity, low-defect electronic polymers films. Leveraging importance-guided Bayesian optimization, Polybot efficiently navigates a complex 7-dimensional processing space. In particular, the automated workflow and algorithms effectively explore the search space, mitigate biases, employ statistical methods to ensure data repeatability, and concurrently optimize multiple objectives with precision. The experimental campaign yields scale-up fabrication recipes, producing transparent conductive thin films with averaged conductivity exceeding 4500 S/cm. Feature importance analysis and morphological characterizations reveal key design factors. This work signifies a significant step towards transforming the manufacturing of electronic polymers, highlighting the potential of AI-driven automation in material science.

Wang, Chengshi [Argonne National Laboratory (ANL),↗

DOE OSTI2021

Simplified feedback control system for scanning tunneling microscopy

A Scanning Tunneling Microscope (STM) is one of the most important scanning probe tools available to study and manipulate matter at the nanoscale. In a STM, a tip is scanned on top of a surface with a separation of a few Å. Often, the tunneling current between the tip and the sample is maintained constant by modifying the distance between the tip apex and the surface through a feedback mechanism acting on a piezoelectric transducer. This produces very detailed images of the electronic properties of the surface. The feedback mechanism is nearly always made using a digital processing circuit separate from the user computer. Here, we discuss another approach using a computer and data acquisition through the universal serial bus port. We find that it allows successful ultralow noise studies of surfaces at cryogenic temperatures. We show results on different compounds including a type II Weyl semimetal (WTe2), a quasi-two-dimensional dichalcogenide superconductor (2H–NbSe2), a magnetic Weyl semimetal (Co3Sn2S2), and an iron pnictide superconductor (FeSe).

Martín-Vega, Francisco (ORCID:0000000333177833)↗

DOE OSTI2021

Cyber–Physical System Security of Distribution Systems

The Information and Communications Technology (ICT) for control and monitoring of power systems is a layer on top of the physical power system infrastructure. The cyber system and physical power system components form a tightly coupled Cyber–Physical System (CPS). Sources of vulnerabilities arise from the computing and communication systems of the cyber–power grid. Cyber intrusions targeting the power grid are serious threats to the reliability of electricity supply that is critical to society and the economy. In a typical Information Technology environment, numerous attack scenarios have shown how unauthorized users can access and manipulate protected information from a network domain. The need for cyber security has led to industry standards that power grids must meet to ensure that the monitoring, operation, and control functions are not disrupted by cyber intrusions. Cyber security technologies such as encryption and authentication have been deployed on the CPS. Intrusion or anomaly detection and mitigation tools developed for power grids are emerging. Furthermore, this survey paper provides the basic concepts of cyber vulnerabilities of distribution systems and CPS security. The important ICT subjects for distribution systems covered in this paper include Supervisory Control And Data Acquisition, Distributed Energy Resources, including renewable energy and smart meters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Revealing Site Occupancy in a Complex Oxide: Terbium Iron Garnet

Complex oxide films stabilized by epitaxial growth can exhibit large populations of point defects which have important effects on their properties. The site occupancy of pulsed laser-deposited epitaxial terbium iron garnet (TbIG) films with excess terbium (Tb) is analyzed, in which the terbium:iron (Tb:Fe)ratio is 0.86 compared to the stoichiometric value of 0.6. The magnetic properties of the TbIG are sensitive to site occupancy, exhibiting a higher compensation temperature (by 90 K) and a lower Curie temperature (by 40 K) than the bulk Tb 3 Fe 5 O 12 garnet. Data derived from X-ray core-level spectroscopy, magnetometry, and molecular field coefficient modeling are consistent with occupancy of the dodecahedral sites by Tb 3+ , the octahedral sites by Fe 3+ , Tb 3+ and vacancies, and the tetrahedral sites by Fe 3+ and vacancies. Energy dispersive X-ray spectroscopy in a scanning transmission electron microscope provides direct evidence of Tb Fe antisites. A small fraction of Fe 2+ is present, and oxygen vacancies are inferred to be present to maintain charge neutrality. In conclusion, variation of the site occupancies provides a path to considerable manipulation of the magnetic properties of epitaxial iron garnet films and other complex oxides, which readily accommodate stoichiometries not found in their bulk counterparts.

36 MATERIALS SCIENCE↗

DOE OSTI2020

TMS XTRRA experiments on NIF

The study of x-ray induced rapid heating and the resulting material responses - (thermomechanical shock (TMS) and thermo-structural response (TSR)) - is important to our understanding of material behavior in extreme environments. A series of high conversion efficiency (XRCE) x-ray sources have been developed for the NIF laser facility ranging in fluence and spectral content. In conjunction with source development, we have developed a new XTRRA (X-ray Transport and Radiation Response Analysis) test cassette to hold a set of samples, each at equal distance from target chamber center (TCC) where the x-ray source is placed. Design and performance details of the x-ray sources is discussed elsewhere. Here, we describe the development and use of this TMS XTRRA test cassette. The XTRRA test cassette is a snout mounted on a NIF Diagnostic Instrument Manipulator (DIM) designed to position six samples equidistant from the x-ray source to assure uniform irradiation of all samples. Photon Displacement interferometry (PDI) is used to measure the displacement of the rear surface of each sample resulting from x-ray exposure on the front of the sample. This will help determine the x-ray generated impulse on the sample. The samples are retrieved from the snout after the shot for inspection and post-shot analysis including the measurement of sample ablated mass and engineering tests examining changes in the material structure. The data from experiments are compared to predictions from LLNL’s ASC codes and used to inform models implemented in these codes. Thus, XRCE x-ray sources with the XTRRA snout at the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory [1,2] provide the ability to expose a broad range of material samples directly to high x-ray fluence, measure shock transits, and recover the sample for further analysis post-shot.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Thermo-Mechanical Shock, X-Ray Transport and Radiation Response Analysis Experiments on NIF

The study of x-ray induced rapid heating and the resulting material responses - (thermomechanical shock (TMS) and thermo-structural response (TSR)) - is important to our understanding of material behavior in extreme environments. A series of high conversion efficiency (XRCE) x-ray sources have been developed for the NIF laser facility ranging in fluence and spectral content. In conjunction with source development, we have developed a new XTRRA (X-ray Transport and Radiation Response Analysis) test cassette to hold a set of samples, each at equal distance from target chamber center (TCC) where the x-ray source is placed. Design and performance details of the x-ray sources is discussed elsewhere. Here, we describe the development and use of this TMS XTRRA test cassette. The XTRRA test cassette is a snout mounted on a NIF Diagnostic Instrument Manipulator (DIM) designed to position six samples equidistant from the x-ray source to assure uniform irradiation of all samples. Photon Displacement interferometry (PDI) is used to measure the displacement of the rear surface of each sample resulting from x-ray exposure on the front of the sample. This will help determine the x-ray generated impulse on the sample. The samples are retrieved from the snout after the shot for inspection and post-shot analysis including the measurement of sample ablated mass and engineering tests examining changes in the material structure. The data from experiments are compared to predictions from LLNL’s ASC codes and used to inform models implemented in these codes. Thus, XRCE x-ray sources with the XTRRA snout at the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory provide the ability to expose a broad range of material samples directly to high x-ray fluence, measure shock transits, and recover the sample for further analysis post-shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Data for "Discovery, Characterization, and Application of Chromosomal Integration Sites in the Hyperthermophilic Archaeon Sulfolobus islandicus"

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

AI/ML↗

DOE OSTI2023

Advancing wildlife connectivity in land use planning: a case study with four-toed salamanders

Stable habitat connections that wildlife can safely traverse are essential to biodiversity conservation and healthy ecosystems. We developed high-resolution landscape connectivity models to predict resistance to movement by a threatened wetland-obligate amphibian, the four-toed salamander ( Hemidactylium scutatum ), and identified priority management areas on the 13,000-ha Department of Energy Oak Ridge Reservation (ORR) from 2019 to 2022. We developed a resistance surface based on aerial light detection and ranging data (LiDAR), >30 years of field-based mapping of forest, hydrologic, and geologic features, and contemporary population surveys, alongside derived predictors at <1-m resolution. We then modeled predicted movement corridors using a circuit theory-based modeling approach. We worked closely with land management and natural resources personnel to integrate ecological modeling with broader land use priorities, monetary costs, and feasibility. We identified important terrestrial and aquatic areas on ORR and simulated management scenarios to promote stable connections for four-toed salamanders. This approach allowed us to narrow down a list of 438 potential habitat manipulation sites to 10 sites where open-bottomed culverts and buffers could be implemented. This smaller-scale restoration approach produced a similar increase in landscape connectivity while costing <20% of a larger-scale approach based on barrier removal. We successfully identified feasible, cost-effective management strategies that integrated knowledge from a variety of sources. In conclusion, we offer a strategy that permitted integration of wildlife management goals into infrastructure upgrades wherein wildlife was not an initial consideration.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

TEMPEST3 surface runoff water chemistry and organic matter composition

Coastal flooding, driven by storm surges and sea level rise, can mobilize organic matter (OM) via runoff, while introducing compositionally distinct OM (e.g., estuarine OM) into the system. To understand event-scale OM dynamics, we monitored source waters and surface runoff during an ecosystem-scale field manipulation experiment, TEMPEST (Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments), in June 2024. The TEMPEST experiment is part of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales – Field, Measurements, and Experiments) project and designed to investigate biogeochemical and ecological impacts of freshwater and seawater flooding on coastal terrestrial-aquatic interface ecosystems by simulating freshwater and seawater storm events in two 2000m2 coastal upland forest plots (freshwater and brackish seawater plots). The temporal coverage of this dataset is during the TEMPESTⅢ event (June 11-13, 2024). This dataset contains: - Surface runoff discharge measured by flumes - Sensor data (specific conductivity, salinity, dissolved oxygen, and temperature) - Particle size distribution - Total suspended sediment concentrations (TSS), particulate and dissolved organic carbon (POC, DOC) concentrations, total nitrogen and total dissolved nitrogen (TN, TDN) concentrations - Bulk particulate and dissolved OM compositions (stable C and N isotopes of particulates and optical measurements of chromophoric dissolved OM) - High resolution mass spectrometry analysis data - Water isotope data All data files are plain-text CSV (comma-separated value), and no special software is required to read them.

COMPASS-FME↗

DOE OSTI2025

GCAM Regional Tuning: A framework to tune GCAM parameters

GCAM assumptions typically generate scenarios that are designed to be internally consistent and globally coherent. The gcamdata tool which facilitates the compilation of data sets and user assumptions is not well suited to tailoring to specific country or regional realities, sponsor requirements, or perform harmonization for model intercomparison needs. As described in this report, the GCAM Regional Tuning project develops a computational framework that enables users to adjust GCAM parameters, so model outputs match targeted outcomes at user-defined spatial, temporal, and sectoral resolutions. The framework integrates GCAM, gcamdata, and gcamwrapper with a set of flexible “tuning directives” and an iterative numerical solver. Users can define targets (e.g., technology shares in power generation, BEV uptake, sectoral service demands), select tuners that manipulate relevant GCAM parameters (e.g., share weights, cost adders, elasticities), and export tuned parameters as reusable GCAM XML inputs for future runs. We demonstrate the approach and document usage, diagnostics, and known limitations, and we outline potential future directions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Evaluating Variable-Impedance Magnetically-Insulated Transmission Lines as a Risk-Mitigation Measure for Next-Generation Pulsed Power

This project has produced the first detailed characterizations of power flow resulting from applying the “variable-impedance MITL” concept to real-life systems in Sandia’s pulsed power program (Z and next-generation pulsed power (NGPP)). We present simulation results and analyses for constant-impedance versions of both Z and NGPP and survey the operational viability of several variable-impedance re-designs in the parameter space of linear tapers. Circuit modeling (SCREAMER/Bertha) was used to pinpoint promising candidate designs, and EM-PIC (Empire) simulations were used to evaluate these candidates more rigorously. This approach was particularly successful in the Z regime which resulted in the identification of several viable variable-impedance MITL designs for each level. The approach was more challenged in the operating space NGPP occupies, producing data points that speak to a more restrictive design space due to anode plasma turn-on. In the end, we were able to converge on one viable variable-impedance design for the highest inductance line (level “F”) and one for the highest current line (level “A”). Altogether, the body of simulation evidence presented in this report suggest there does exist flexibility in operating space for magnetically-insulated transmission lines (MITLs) having variable geometric impedance to be a potential enabling technology for safely increasing current delivery (and potentially lowering stack voltage) in pulsed-power drivers by manipulating electron losses; however, operating points for a particular design must be carefully screened. Circuit and EM-PIC modeling provided consistent verdicts in safe operating regimes for operational viability, but additional physics such as anode plasma turn-on which is included in Empire but not in SCREAMER/Bertha was found to be a critical factor affecting power flow that lead to different assessments between the codes. It is not always the case that the occurrence of anode plasma caused a design to fail (some designs turned on anode plasma yet still delivered load currents meeting design targets); the details matter such as how early in the pulse anode surfaces break down (and how large a region). However, in every case that it did fail it was found that the feedback from anode plasma was the cause (i.e., turning off the anode plasma model in Empire restored agreement with the circuit model prediction). As circuit simulations represent an efficient and practical means of surveying design space compared to more computationally-expensive approaches such as EM-PIC, it could be prudent to invest in the research and development of models to include the effects of anode plasma such as ion emission in circuit codes. The variable-impedance MITL design is a new concept that enables controlled manipulation of the initial electron losses in the outer MITL and can be tested on Z today. We encourage follow-on work to explore further optimization (including alternative variable-impedance profiles, e.g., having constant dZ/dR), and to confirm the major findings presented in this report by fielding test hardware on actual Z shots.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

GRIP: Constraint-based Explanation of Missing Answers for Graph Queries

Abstract: A useful feature in graph query engines is to clarify “Why certain entities (nodes, attribute values or edges) are missing” in query answers. This task is even more challenging when the relevant data is already missing in the underlying data source. Missing data, on the other hand, can be inferred by enforcing data constraints for graphs. We demonstrate GRIP, a system that exploits data constraints to clarify missing answers for graph queries. (1) Constraint-based ex- planation. Given a desired yet missing entity in the query answer, GRIP ensures to generate finite and minimal sequences of data con- strains (an “explanation”) that should be consecutively enforced to ?? to ensure its occurrence for the same query. (2) Answering “why” and“how” questions. Users can query GRIP with both“Why”(“Why” the element is missing) and “How” questions (“How” to refine the graph to include the missing answer). GRIP engine supports run- time generation of explanations by incrementally maintaining a set of bi-directional search trees. (3) Interactive exploration. GRIP provides a user-friendly GUI to support interactive ad visual exploration of explanations, including both automated generation and step-by-step inspection of graph manipulations.

graphs↗

DOE OSTI2025

X-ray spectroscopy of multi-temperature plasmas using the differential emission measure formalism

We present a theoretical construct that nominally underlies spectroscopic data analysis of multi-temperature plasmas, known as the differential emission measure (DEM). From a data analytic perspective, the DEM formalism is used to derive temperature distributions from line spectra that are formed in the presence of temperature gradients and by time integrations of evolving plasmas. From a modeling perspective, DEMs are convenient intermediaries between radiation hydrodynamics simulations and spectroscopic measurements acquired in the laboratory. The DEM concept and its associated methodologies were originally developed by spectroscopists working with astrophysical data. We borrow from these earlier investigations. In this manuscript, intended primarily as a tutorial, we discuss the basic concepts, but also augment various aspects of the theory by the way of extension and example, including a detailed treatment of various weighting and averaging schemes, intended to mitigate ambiguities that often arise when reporting temperature information. We focus on high-temperature plasmas that are not in local thermodynamic equilibrium and the x-ray spectra that they produce, although the core ideas presented here are applicable to spectroscopy in other energy bands. A few examples involving the derivation and manipulation of model DEMs in simple geometries are provided.

Liedahl, Duane A. [Lawrence Livermore National Lab↗

DOE OSTI2021

High signal-to-noise ratio differential conductance spectroscopy

The scanning tunneling microscope (STM) has enabled manipulation and interrogation of surfaces with atomic-scale resolution. Electronic information about a surface is obtained by combining the imaging capability of the STM with scanning tunneling spectroscopy, i.e., measurement of current-voltage (I/V) characteristics of the surface. We propose a change in the STM feedback loop that enables capturing a higher quality dI/dV image. A high frequency dither voltage is added to the bias voltage of the sample, and the fundamental frequency component of the resulting current is demodulated. The in-phase component of this signal is then plotted along with the X and Y position data, constructing the dI/dV image. Here, we show that by incorporating notch filters in the STM feedback loop, we may utilize a high-amplitude dither voltage to significantly improve the quality of the obtained dI/dV image.

42 ENGINEERING↗

DOE OSTI2022

A knock-on deuteron imager for measurements of fuel and hotspot asymmetry in direct-drive inertial confinement fusion implosions (invited)

A knock-on deuteron imager (KoDI) has been implemented to measure the fuel and hotspot asymmetry of cryogenic inertial confinement fusion implosions on OMEGA. Energetic neutrons produced by D–T fusion elastically scatter (“knock on”) deuterons from the fuel layer with a probability that depends on ρR. Deuterons above 10 MeV are produced by near-forward scattering, and imaging them is equivalent to time-integrated neutron imaging of the hotspot. Deuterons below 6 MeV are produced by a combination of side scattering and ranging in the fuel, and encode information about the spatial distribution of the dense fuel. Here, the KoDI instrument consists of a multi-penumbral aperture positioned 10–20 cm from the implosion using a ten-inch manipulator and a detector pack at 350 cm from the implosion to record penumbral images with magnification of up to 35×. Range filters and the intrinsic properties of CR-39 are used to distinguish different charged-particle images by energy along the same line of sight. Image plates fielded behind the CR-39 record a 10 keV x-ray image using the same aperture. A maximum-likelihood reconstruction algorithm has been implemented to infer the source from the projected penumbral images. The effects of scattering and aperture charging on the instrument point-spread function are assessed. Synthetic data are used to validate the reconstruction algorithm and assess an appropriate termination criterion. Significant aperture charging has been observed in the initial experimental dataset, and increases with aperture distance from the implosion, consistent with a simple model of charging by laser-driven EMP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗