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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

TOI-824 b: A New Planet on the Lower Edge of the Hot Neptune Desert

We report the detection of a transiting hot Neptune exoplanet orbiting TOI-824 (SCR J1448-5735), a nearby (d = 64 pc) K4V star, using data from the Transiting Exoplanet Survey Satellite. The newly discovered planet has a radius R {sub p} = 2.93 ± 0.20 R{sub ⊕} and an orbital period of 1.393 days. Radial velocity measurements using the Planet Finder Spectrograph and the High Accuracy Radial velocity Planet Searcher spectrograph confirm the existence of the planet, and we estimate its mass to be 18.47 ± 1.84 M{sub ⊕}. The planet’s mean density is ρ{sub p} = 4.03{sub −0.78}{sup +0.98} g cm{sup −3}, making it more than twice as dense as Neptune. TOI-824 b's high equilibrium temperature makes the planet likely to have a cloud-free atmosphere, and thus it is an excellent candidate for follow-up atmospheric studies. The detectability of TOI-824 b’s atmosphere from both ground and space is promising and could lead to the detailed characterization of the most irradiated small planet at the edge of the hot Neptune desert that has retained its atmosphere to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhancing grid reliability and resilience through novel DER control, total situational awareness and integrated distribution-transmission representation

High penetration of distributed energy resources (DERs) can lead to overvoltage and thermal violations, miscoordination of protection devices and potential adverse control interactions. The challenges are exacerbated by a lack of operator situational awareness of behind-the-meter DERs, and T&D interactions. Furthermore, the large attack surface of a DER environment creates significant cyber security challenges. The motivation is to address these barriers. The main goal is to enable extreme levels of DERs in distribution systems while simultaneously enhancing their reliability and resiliency. This is achieved by a data-driven approach for operation, planning and control of distribution systems with total situational awareness and real-time DER control enabled by a network of edge intelligent devices, a cloud-based analytical platform, and secure communications.

14 SOLAR ENERGY↗
DOE OSTI2023

Redox Mechanisms and Migration Tendencies in Earth-Abundant 0.7Li 2 MnO 3 ·0.3LiFeO 2 Cathodes: Coupling Spin-Resolved X-ray Absorption Near Edge and X-ray Absorption Fine Structure Spectroscopies

We report the use of iron 1s3p resonant X-ray emission processes to conduct spin-selective, high-energy resolution fluorescence detected X-ray absorption near-edge spectroscopy (HERFD-XANES) on an iron-containing, lithium- and manganese-rich, fully earth-abundant cathode material, Li 1.3 Mn 0.5 Fe 0.2 O 2 (0.7Li 2 MnO 3 ·0.3LiFeO 2 ). Coupling this technique with conventional Mn K-edge XANES and detailed extended X-ray absorption fine structure (EXAFS) analysis from both the Mn and Fe vantage points, we gain fundamental insights into the redox processes and migration tendencies of transition metals in this cathode material at the bulk level. We show that during the first charge, Fe 3+ undergoes oxidation to form Fe 4+ prior to the activation plateau. Toward the end of activation, a significant fraction of the iron is present as tetrahedral Fe 3+ . This observation reveals that iron migration from octahedral to tetrahedral sites and iron reduction are initiated during activation. Upon first discharge from the activated state, a continuous and overlapping reduction of both Fe and Mn is observed, with Fe largely restored back as an octahedrally coordinated Fe 3+ . The manganese local environment gradually changes to a distorted cooperative Jahn–Teller Mn 3+ structure during discharge, with the clear presence of two Mn–O as well as two Mn–Mn correlation distances at 2.0 V. The significant reduction of manganese in the very first discharge is distinctly different from that seen in typical nickel-based lithium-manganese-rich materials but is similar to that observed for pure Li 2 MnO 3 . In conclusion, these findings shed light on key structure–property correlations in the cathode material and point to a causative relationship between the redox mechanisms as well as structural changes endured by the material and relatively poor performance during extended electrochemical cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nanoscale Three-Dimensional Imaging of Integrated Circuits Using a Scanning Electron Microscope and Transition-Edge Sensor Spectrometer

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO 2 integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Outburst of the Young Star Gaia19bey

We report photometry and spectroscopy of the outburst of the young stellar object Gaia19bey. We have established the outburst light curve with archival Gaia “G,” ATLAS “Orange,” Zwicky Transient Facility r-band, and Pan-STARRS “rizy”-filter photometry, showing an outburst of ~4 yr duration, longer than typical EX Lupi objects but shorter than FU Orionis objects. Its pre-outburst spectral energy distribution shows a flat far-infrared spectrum, confirming the early evolutionary state of Gaia19bey and its similarity to other deeply embedded young stars experiencing outbursts. A lower limit to the peak outburst luminosity is ~182 L{sub ⊙} at an assumed distance of 1.4 kpc, the minimum plausible distance. Infrared and optical spectroscopy near maximum light show an emission line spectrum, including H i lines, strong red Ca ii emission, other metal emission lines, infrared CO bandhead emission, and a strong infrared continuum. Toward the end of the outburst, the emission lines have all but disappeared and the spectrum has changed into an almost pure continuum spectrum. This indicates a cessation of magnetospheric accretion activity. The near-infrared colors have become redder as Gaia19bey has faded, indicating a cooling of the continuum component. Near the end of the outburst, the only remaining strong emission lines are forbidden shock-excited emission lines. Adaptive optics integral-field spectroscopy shows the H{sub 2} 1–0 S(1) emission with the morphology of an outflow cavity and the extended emission in the [Fe ii] line at 1644 nm with the morphology of an edge-on disk. However, we do not detect any large-scale jet from Gaia19bey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Carbon nanospikes have improved sensitivity and antifouling properties for adenosine, hydrogen peroxide, and histamine

Carbon nanospikes (CNSs) are a new nanomaterial that has enhanced surface roughness and surface oxide concentration, increasing the sensitivity for dopamine detection. However, CNS-modified electrodes (CNSMEs) have not been characterized for other neurochemicals, particularly those with higher oxidation potentials. The purpose of this study was to evaluate CNSMEs for the detection of adenosine, hydrogen peroxide (H 2 O 2 ), and histamine. The sensitivity increased with CNSs, and signals at CNSMEs were about 3.3 times higher than CFMEs. Normalizing for surface area differences using background currents, CNSMEs show an increased signal of 4.8 times for adenosine, 1.5 times for H 2 O 2 , and 2 times for histamine. CNSMEs promoted the formation of secondary products for adenosine and histamine, which enables differentiation from other analytes with similar oxidation potentials. Furthermore, CNSs also selectively enhance the sensitivity for adenosine and histamine compared to H 2 O 2 . A scan rate test reveals that adenosine is more adsorption-controlled at CNS electrodes than CFMEs. CNSMEs are antifouling for histamine, with less fouling because the polymers formed after histamine electrooxidation do not adsorb due to an elevated number of edge planes. CNSMEs were useful for detecting each analyte applied in brain slices. Because of the hydrophilic surface compared to CFMEs, CNSMEs also have reduced biofouling when used in tissue. Therefore, CNSMEs are useful for tissue measurements of adenosine, hydrogen peroxide, and histamine with high selectivity and low fouling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Visualizing interaction-driven restructuring of quantum Hall edge states

Many topological phases host gapless boundary modes that can be dramatically modified by electronic interactions. Even for the long-studied edge modes of quantum Hall phases, forming at the boundaries of two-dimensional (2D) electron systems, the nature of such interaction-induced changes has been elusive. Despite advances made using local probes, key experimental challenges persist: the lack of direct information about the internal structure of edge states on microscopic scales, and complications from edge disorder. Here, we use scanning tunneling microscopy (STM) to image pristine electrostatically defined quantum Hall edge states in graphene with high spatial resolution and demonstrate how correlations dictate the structures of edge channels on both magnetic and atomic length scales. For integer quantum Hall states in the zeroth Landau level, we show that interactions renormalize the edge velocity, dictate the spatial profile for copropagating modes, and induce unexpected edge valley polarization that differ from those of the bulk. While some of our findings can be understood by mean-field theory, others show breakdown of this picture, highlighting the roles of edge fluctuations and inter-channel couplings. We also extend our measurements to spatially resolve the edge state of fractional quantum Hall phases and detect spectroscopic signatures of interactions in this chiral Luttinger liquid. Furthermore, our study establishes STM as a promising tool for exploring edge physics of the rapidly expanding 2D topological phases, including newly realized fractional Chern insulators.

Electronic properties and materials↗
DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation: Preprint

This paper proposes a hybrid data and model-based anomaly detection for securing the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders (AE) are set up at the edge level by taking local DER data and detect anomalous operations by leveraging the reconstruction ability. In parallel, model-based state estimation (SE) is running at the system level by taking system models and measurements, the anomalies are identified by analyzing the measurements residual. The hybrid scheme preserves the benefits of both data-driven and model-based analysis and thus improves the robustness and accuracy of anomaly detection. It can be established by getting full use of the existing infrastructures in distribution grids. Numerical tests on a realistic distribution feeder in Southern California highlight the effectiveness as well as benefits of the proposed scheme.

anomaly detection↗
DOE OSTI2020

Josephson Junctions and Cosmic Microwave Background

The implementation of utilizing superconducting quantum interference device (SQUID) readout for constant voltage biased transition edge sensors (TES) has enabled the detection of the infinitesimal fluctuation in cosmic microwave background (CMB). The properties of the fluctuations will provide us the information of the universe at the time that this light was first emitted. In short, by measuring the CMB today, we learn about the distant, ancient universe—how the universe began, what it is made of, and how it evolved to its current state. Over the past 20 years, we have achieved many successful CMB measurements with Josephson junctions. Brian, I extend my congratulations on your eight decades of life—Happy 80th birthday!

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Negative-Ion Formation upon Soft X-ray Photoexcitation of 2-Propanol

This study investigates the formation of negative ion fragments from gas-phase 2-propanol molecules after interaction with soft X-rays near the O K-edge. The experiment was performed by detecting negative and positive ions in coincidence with time-of-flight spectrometry. The analysis of two- and three-ion coincidence data revealed that nine different anions were produced: H – , C – , CH – , CH 2 – , O – , OH – , C 2 – , C 2 H – , and C 3 – . For all anions, the most common three-ion events were those involving two protons. The results highlight the sensitivity of negative-ion/positive-ion coincidence spectroscopy and provide new insight into the fragmentation processes of organic molecules under soft X-ray excitation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Theory-Guided X-ray Absorption Spectroscopy Approach for Identifying Active Sites in Atomically Dispersed Transition-Metal Catalysts

Atomically dispersed supported metal catalysts offer new properties and the benefits of maximized metal accessibility and utilization. The characterization of these materials, however, remains challenging. Using atomically dispersed platinum supported on crystalline MgO (chosen for its well-defined bonding sites) as a prototypical example, we demonstrate in this work how systematic density functional theory calculations for assessing all the potentially stable platinum sites, combined with automated analysis of extended X-ray absorption fine structure (EXAFS) spectra, leads to unbiased identification of isolated, surface-enveloped platinum cations as the catalytic species for CO oxidation. The catalyst has been characterized by atomic-resolution imaging and EXAFS and high-energy resolution fluorescence detection X-ray absorption near edge spectroscopy. The proposed platinum sites are in agreement with experiment. This theory-guided workflow leads to rigorously determined structural models and provides a more detailed picture of the structure of the catalytically active site than what is currently possible with conventional EXAFS analyses. As this approach is efficient and agnostic to the metal, support, and catalytic reaction, we posit that it will be of broad interest to the materials characterization and catalysis communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-Analytical Investigation of Arsenical Transfer and Remediation on Nineteenth-Century Green Books

Books containing heavy metals, specifically nineteenth-century green arsenical books, have been identified at Northwestern University Libraries, raising health and safety concerns related to handling. Copper acetoarsenite pigments, such as emerald green, were detected on book covers, decorative page edges, labels, and other components using noninvasive analytical techniques including X-ray fluorescence (XRF), Raman spectroscopy, and Fourier-transform infrared (FTIR) spectroscopy. Further examination of selected volumes using synchrotron radiation (SR) techniques revealed pigment migration, degradation, and arsenic transfer to adjacent books. This paper expands on initial findings through two related experiments. The first explored the transfer of arsenic using mechanical friction; Staedtler Mars® white vinyl erasers rubbed on arsenical books generated crumbs which were analyzed via scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM-EDX). Results confirmed the transfer of arsenic, copper, and lead, with decorative page edges being particularly prone to shedding arsenic onto other materials. The second experiment tested remediation methods on a book contaminated by prolonged exposure to an arsenical neighbor. Surface cleaning using erasers and a vacuum removed flecks of pigment but did not eliminate non-chromophoric arsenic as confirmed by SR analyses, which highlights its presence either as a degradation product embedded within the paper or present in the paper as part of its production process. Findings demonstrate the acute toxicity risk posed by arsenical books and support the need for safe handling protocols. However, materials with only trace levels of arsenic embedded during production may pose a lower risk of transfer. Cross contamination beyond prolonged direct contact appears limited. These results highlight critical considerations for library preservation practices and future research on arsenic in historical materials.

arsenic↗
DOE OSTI2022

DER Cybersecurity Detection and Response Suite

SAND2024-08475O The Distributed Energy Resource (DER) Cybersecurity Detection and Response Suite is a solution for distributed energy resource (DER) systems. The DER Security Orchestration, Automation, and Response (SOAR) solution that uses alerts from signature- and behavior-based Intrusion Detection Systems are intended to be deployed as bump-in-the-wire (BITW) devices in front of DER equipment. The fielded application would use multiple intrusion detection systems that report data to SOAR to respond to cyberattacks. The suite consists of two software components: • The proactive intrusion detection and mitigation system (PIDMS) secures grid-edge photovoltaic smart inverters and other equipment in distributed energy resource systems. It is a distributed BITW solution; cyber and physical data are automatically processed using network inspection tools and custom machine learning algorithms to detect abnormal events and correlate cyber-physical events. • The Security Orchestration, Automation, and Response for Distributed Energy Resources (SOAR4DER) application ingests data from several intrusion detection systems to quickly block attacks and revert DER systems to good states. Using a collection of intrusion detection system technologies on a BITW device, it incorporates physical and cyber data to detect abnormal and potential malicious behaviors. Multiple SOAR playbooks then use the intrusion detection system data streams to automatically defend the system. SOAR4DER system testing showed detection and response times under 30 seconds for all adversary reconnaissance, denial-of-service attacks, malicious Modbus commands, brute-force logins, and machine-in-the-middle attacks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Johnson, Jay↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

van der Waals Epitaxy, Superlubricity, and Polarization of the 2D Ferroelectric SnS

Tin monosulfide (SnS) is a two-dimensional layered semiconductor that exhibits in-plane ferroelectric order at very small thicknesses and is of interest in highly scaled devices. Here, in this study, we report the epitaxial growth of SnS on hexagonal boron nitride (hBN) using a pulsed metal-organic chemical vapor deposition process. Lattice matching is observed between the SnS($100$) and hBN{$1\bar{10}$} planes, with no evidence of strain. Atomic force microscopy reveals superlubricity along the commensurate direction of the SnS/hBN interface, and first-principles calculations suggest that friction is controlled by the edges of the SnS islands, rather than interface interactions. Differential phase contrast imaging detects remnant polarization in SnS islands with domains that are not dictated by step-edges in the SnS. The growth of ferroelectric SnS on high quality hBN substrates is a promising step toward electrically switchable ferroelectric semiconducting devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Calcium-Uranyl-Carbonato Species Kinetically Limit U(VI) Reduction by Fe(II) and Lead to U(V)-Bearing Ferrihydrite

Reaction conditions and mechanisms promoting or inhibiting U reduction exert a central control on U solubility and, therefore, U transport and its associated risks. Here, we vary and track common aqueous uranium species to show that a kinetic restriction inhibits homogeneous reduction of the calcium-uranyl-carbonato species (CaUO$_2$(CO$_3$)$_3$$^{2–}$ and Ca$_2$UO$_2$(CO$_3$)$_3$) by Fe(II)$_{(aq)}$, while ferrihydrite surface-catalyzed reduction of all aqueous uranyl by Fe(II) proceeds. Using U L$_3$ high energy resolution fluorescence detection (HERFD) X-ray absorption near edge structure (XANES) spectroscopy, U L$_3$ extended X-ray absorption fine structure (EXAFS) spectroscopy, and transmission electron microscopy (TEM), we also show that U(V) is generated and incorporated into ferrihydrite formed from homogeneous U(VI) reduction by Fe(II)(aq). Through elucidation of the mechanisms that inhibit reduction of the calcium-uranyl-carbonato species and promote stabilization of U(V), we advance our understanding of the controls on U solubility and thus improve prediction of U transport in surface and subsurface systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗