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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detection of trace contaminants released from rapidly heated pulsed power electrodes by laser diagnostics

Development of a capability to measure trace gas contaminants released from pulsed power electrodes would immediately impact Sandia pulsed power research. These releases occur during ultra-fast heating of metal electrodes during pulsed power discharges and can lead to substantial power losses through plasma formation. Detection of contaminants is a formidable challenge due to the need for in-situ spatially and temporally resolved measurements of trace gases in the extreme environment of ultra-fast heated metal surfaces. We investigate the feasibility of laser diagnostics for detecting contaminants, including H-atom, OH, and H 2 O. Laser-induced fluorescence and photofragmentation fluorescence showed significant plasma emission interferences and did not yield any detectable H-atom, OH, or H 2 O. Our newly developed H-atom detection using femtosecond degenerate four-wave mixing suppressed interferences and enabled detection of H-atoms. A few shots showed large signals in the near-surface region of metal foils, suggesting the formation of a wave of H-atoms from the metal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Discovery of an Ultra-faint Stellar System near the Magellanic Clouds with the DECam Local Volume Exploration Survey

We report the discovery of a new ultra-faint stellar system found near the Magellanic Clouds in the DECam Local Volume Exploration Survey. This new system, DELVE J0155−6815 (DELVE 2), is located at a heliocentric distance of D ⊙ = 71 ± 4 kpc, which places it at a 3D physical separation of 12 ± 3 kpc from the center of the Small Magellanic Cloud and from the center of the Large Magellanic Cloud (LMC). DELVE 2 is identified as a resolved overdensity of old (τ > 13.3 Gyr) and metal-poor ( dex) stars with a projected half-light radius of and an absolute magnitude of . The size and luminosity of DELVE 2 are consistent with both the population of recently discovered ultra-faint globular clusters and the smallest ultra-faint dwarf galaxies. However, its photometrically derived age and metallicity would place it among the oldest and most metal-poor globular clusters in the Magellanic system. In the absence of spectroscopic measurements of the system’s metallicity dispersion and internal kinematics, we are unable to conclusively classify this system at this time. DELVE 2 is detected in Gaia DR2 with a clear proper-motion signal, with multiple blue horizontal-branch stars near the centroid of the system with proper motions consistent with the systemic mean. We measure the system proper motion to be = mas yr−1. We compare the spatial position and proper motion of DELVE 2 with simulations of the accreted satellite population of the LMC and find that it is very likely to be associated with the LMC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Upper Bound on Parity Breaking Scale for Doublet WIMP Dark Matter

We consider weakly interacting massive particle (WIMP) dark matter in a Parity solution to the strong CP problem. The WIMP phenomenology can be drastically affected by the presence of Parity partners of the WIMP and electroweak gauge bosons. We focus on a Parity extension of $SU(2)_L$-doublet fermion dark matter, identify the viable parameter space, and derive the predictions of the theory. We find that the Parity symmetry breaking scale is bounded from above, with the bound given by $25-60$ TeV, depending on whether or not dark matter and its Parity partner coannihilate with each other. The High-Luminosity Large Hadron Collider, future colliders, and direct and indirect detection experiments can probe the parameter space further, with correlated signal rates.

Baldwin, Matthew J. [Chicago U.; Chicago U., KICP]↗
DOE OSTI2022

Checkerboard patterns in E3SMv2 and E3SM-MMFv2

Abstract. An unphysical checkerboard pattern is identified in E3SMv2 and E3SM-MMF that is detectable across a wide range of timescales, from instantaneous snapshots to multi-year averages. A detection method is developed to quantify characteristics of the checkerboard signal by cataloguing all possible configurations of the eight adjacent neighbors for each cell on the model's cubed sphere grid using daily mean data. The checkerboard pattern is only found in cloud-related quantities, such as precipitation and liquid water path. Instances of pure and partial checkerboard are found to occur more often in E3SMv2 and E3SM-MMF when compared to satellite data regridded to the model grid. Continuous periods of partial checkerboard state are found to be more persistent in both models compared to satellite data, with E3SM-MMF exhibiting more persistence than E3SMv2. The checkerboard signal in E3SMv2 is found to be a direct consequence of the recently added deep convective trigger condition based on dynamically generated CAPE (DCAPE). In E3SM-MMF the checkerboard signal is found to be associated with the “trapping” of cloud-scale fluctuations within the embedded cloud-resolving model. Solutions to remedy this issue are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Application of Frequency Division Multiplexing and Neural Networks in the Operation and Diagnosis of the Stator Current and Shaft Position Sensors Used in Electric/Hybrid Vehicles

Fast, precise and robust sensing of currents and motor shaft angle is essential for the excellent performance of electric and hybrid vehicles (EV/HEV). Multiplexing techniques are commonly applied in data acquisition systems (DAQs) to digitize the signals sensed in EV/HEV drives. Frequency-division multiplexing (FDM) applied to get the signals from current sensors and resolver angular position sensor has advantages over conventional multiplexing approaches. However, problems such as aging and mechanical imperfections distort the outputs of those sensors, producing measurement errors of the angular position and currents. Conventional techniques designed to compensate for those errors cannot be applied in signals multiplexed in frequency. This paper proposes online techniques to detect and compensate for the distortions in the resolver sensor and current sensors. The demultiplexing process was adjusted to allow distortion detection and compensation. An auto-associative neural network (ANN) compensates for the current measurement error, while an energy-based technique is applied to compensate for the distortions in the resolver outputs. The obtained results show that the distortions were compensated, allowing a more accurate estimation of stator currents and angular position when FDM is applied in EV/HEV DAQs.

Pereira Pinto, Joao↗
DOE OSTI2023

Multimodal photon and neutron imaging devices with fast event-by-event multisampling readout and optimized particle type discrimination

A particle imaging method for distinguishing between types of incident particles, such as neutrons, photons, and alphas, and improving the position resolution of particle imaging devices with matrix readout. The method includes high frequency multisampling readout electronics that provides the sequences of multiple measurements for each detected event, resulting in recorded detailed waveform information describing the signals. Such detailed information is used to approximate each signal waveform with a parameterized function in which the extracted parameter sets determine the type of the incident particle in an optimized fashion. The detailed event-by-event multisampling information for each signal readout channel in the matrix readout of the radiation imaging devices improves and optimizes the position resolution for variable shapes of the signals. Such devices can be used in mixed radiation fields, creating a new class of multimodal photon and neutron imagers.

Degtiarenko, Pavel V.↗
DOE OSTI2022

Avoiding thermal runaway in lithium-ion batteries using ultrasound detection of early failure mechanisms

Thermal runaway leading to catastrophic failure has slowed the adoption of lithium-ion batteries, highlighting the need for early warning systems. In this work, ultrasound is used to detect physical changes in 0.950 Ah Li-ion battery cells by inducing conditions associated with thermal runaway. Ultrasound signal features are extracted as the batteries are cycled under baseline conditions and subsequently subjected to constant current and voltage overcharges. Two conditions identifying failure are defined: a warning to detect the start of overcharge and an emergency stop (E-stop), to immediately take the battery out of service. Using changes in ultrasound signal features, consistent warning and stopping classifications are applied to all failure experiments. On average, a warning notification was issued after 15% of the overcharge time and an E-stop was triggered after 35% of total overcharge duration before failure. Further testing suggests that it is possible to avoid thermal runaway by reacting to intermediate, warning notifications prior to an immediate E-stop. In other words, not only can detection derived by ultrasound identify battery failure before a catastrophic event, but can also provide early, actionable warnings so that overcharges can be detected and corrected quickly enough so the battery does not need to be decommissioned.

25 ENERGY STORAGE↗
DOE OSTI2025

Earthquake detection in a simulated lunar regolith using distributed acoustic sensing

Current models of inner lunar geology have largely been inferred from the seismic experiments and observations performed during the Apollo missions that comprised a relatively small number of seismic instruments. Refining constraints on fundamental lunar relationships such as crust-mantle and mantle-core boundaries in the future will require seismic arrays spanning larger epicentral distances. A promising technology for installing dense seismic arrays with minimal human effort is distributed acoustic sensing (DAS), an approach that allows a single length of fiber optic cable to act as hundreds or thousands of sensors when coupled with a DAS interrogator. While terrestrial uses of DAS technology for seismic monitoring rely on burying the cable to maximize fidelity of seismic signal transmission to the fiber, digging meters of trench to bury optical fiber on lunar or planetary surfaces is logistically infeasible. To evaluate DAS signal attenuation due to surface deployment of cable in lunar regolith, we completed earthquake detection analyses that evaluated the sensitivity of an optic-fiber DAS system to seismic signals at different burial depths. We deployed a single-mode fiber in a 10-m open-bottom wooden box filled with a lunar regolith simulant (LRS) with fiber buried at different depths within the LRS and recorded signals for four regional and local earthquakes. The results were used to identify and evaluate signal attenuation in surface-deployed fiber compared to buried fiber in the LRS. Burial depth responses to active-source signals were also evaluated similar to previous studies characterizing DAS sensitivity of surface-deployed fiber. Atmospheric noise was minimal as the cable was deployed in an indoor environment; however, where observed, atmospheric and anthropogenic noise was filtered out using the same bandpass filtering used to identify earthquake events. We found that signal attenuation of the surface-deployed fiber compared to buried fiber was relatively high in active-source experiments but was not consistently observed in earthquake signals. That burial depth is not highly correlated to attenuation of the observed earthquake signals indicates that in a noise-limited environment, placing DAS-interrogated fiber directly at the regolith surface may be a promising deployment strategy to consider for sensing remote seismic signals during lunar exploration.

58 GEOSCIENCES↗
DOE OSTI2022

Optical readout of singlet fission biexcitons in a heteroacene with photoluminescence detected magnetic resonance

Molecular spin systems based on photoexcited triplet pairs formed via singlet fission (SF) are attractive as carriers of quantum information because of their potentially pure and controllable spin polarization, but developing systems that offer optical routes to readout as well as initialization is challenging. Herein, we characterize the electron spin magnetic resonance change in the photoluminescence intensity for a tailored organic molecular crystal while sweeping a microwave drive up to 10 GHz in a broadband loop structure. We observe resonant transitions for both triplet and quintet spin sublevel populations showing their optical sensitivity and revealing the zero-field parameters for each. We map the evolution of these spectra in both microwave frequency and magnetic field, producing a pattern of optically detected magnetic resonance (ODMR) peaks. Fits to these data using a suitable model suggest significant spin polarization in this system with orientation selectivity. Unusual excitation intensity dependence is also observed, which inverts the sign of the ODMR signal for the triplet features, but not for the quintet. These observations demonstrate optical detection of the spin sublevel population dictated by SF and intermolecular geometry, and highlight anisotropic and multi-scale dynamics of triplet pairs.

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

A Scintillating Xenon Bubble Chamber for Dark Matter Detection. Final Report

This report describes the progress in the search for particle dark matter achieved under DOE award DE-SC0012161, as well as the invention of a new dark matter and neutrino detection technique. Work supported by this award follows in three distinct thrusts: (1) the successful completion of the Generation-1 Direct Detection experiment PICO-60, which set the world-leading limit on the spin-dependent coupling of dark matter to protons and achieved a precise understanding of the response of bubble chambers to nuclear-recoil signals and electron-recoil backgrounds; (2) the construction of the Generation-2 Direct Detection experiment LZ, which will soon be the world's most sensitive dark matter detector; and (3) the demonstration of the first scintillating bubble chamber. The development of a scintillating liquid noble bubble chamber was the primary goal of the proposed work, with the aim of combining the excellent background rejection of a PICO-style bubble chamber with the event-by-event energy resolution of a liquid-noble detector such as LZ. This work produced the first ever observation of coincident scintillation and bubble nucleation by a nuclear recoil in a superheated fluid and also revealed an unexpected benefit to the use of noble liquids in a bubble chamber, namely the ability to increase the degree of superheat by an order of magnitude beyond that achievable in PICO-style detectors while maintaining PICO's world-leading background rejection. This discovery has led to new projects in the US and Canada, developing noble liquid bubble chambers both as detectors for low-mass dark matter and as detectors of coherent elastic neutrino-nucleus scattering (CEvNS) by neutrinos produced at nuclear reactors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

EXPRES. II. Searching for Planets around Active Stars: A Case Study of HD 101501

By controlling instrumental errors to below 10 cm s{sup −1}, the EXtreme PREcision Spectrograph (EXPRES) allows for a more insightful study of photospheric velocities that can mask weak Keplerian signals. Gaussian processes (GP) have become a standard tool for modeling correlated noise in radial velocity data sets. While GPs are constrained and motivated by physical properties of the star, in some cases they are still flexible enough to absorb unresolved Keplerian signals. We apply GP regression to EXPRES radial velocity measurements of the 3.5 Gyr old chromospherically active Sun-like star, HD 101501. We obtain tight constraints on the stellar rotation period and the evolution of spot distributions using 28 seasons of ground-based photometry, as well as recent Transiting Exoplanet Survey Satellite data. Light-curve inversion was carried out on both photometry data sets to reveal the spot distribution and spot evolution timescales on the star. We find that the >5 m s{sup −1} rms radial velocity variations in HD 101501 are well modeled with a GP stellar activity model without planets, yielding a residual rms scatter of 45 cm s{sup −1}. We carry out simulations, injecting and recovering signals with the GP framework, to demonstrate that high-cadence observations are required to use GPs most efficiently to detect low-mass planets around active stars like HD 101501. Sparse sampling prevents GPs from learning the correlated noise structure and can allow it to absorb prospective Keplerian signals. We quantify the moderate to high-cadence monitoring that provides the necessary information to disentangle photospheric features using GPs and to detect planets around active stars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗
DOE OSTI2022

Autoencoders for semivisible jet detection

The production of dark matter particles from confining dark sectors may lead to many novel experimental signatures. Depending on the details of the theory, dark quark production in proton-proton collisions could result in semivisible jets of particles: collimated sprays of dark hadrons of which only some are detectable by particle collider experiments. The experimental signature is characterised by the presence of reconstructed missing momentum collinear with the visible components of the jets. This complex topology is sensitive to detector inefficiencies and mis-reconstruction that generate artificial missing momentum. With this work, we propose a signal-agnostic strategy to reject ordinary jets and identify semivisible jets via anomaly detection techniques. A deep neural autoencoder network with jet substructure variables as input proves highly useful for analyzing anomalous jets. The study focuses on the semivisible jet signature; however, the technique can apply to any new physics model that predicts signatures with anomalous jets from non-SM particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data

We present the first study of anti-isolated Upsilon decays to two muons (ϒ→𝜇⁺⁢𝜇⁻) in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-based anomaly detection strategy, we “rediscover” the ϒ in 13 TeV CMS Open Data from 2016, despite overwhelming anti-isolated backgrounds. We elevate the signal significance to 6.4⁢𝜎 using these methods, starting from 1.6⁢𝜎 using the dimuon mass spectrum alone. Moreover, we demonstrate improved sensitivity from using an ML-based estimate of the multifeature likelihood compared to traditional “cut-and-count” methods. This is the first ever detection of anti-isolated Upsilons, which can be useful in the study of heavy-flavor fragmentation in quantum chromodynamics. Our Letter demonstrates that it is possible and practical to find real signals in experimental collider data using ML-based anomaly detection, and we distill a readily accessible benchmark dataset from the CMS Open Data to facilitate future anomaly detection developments.

machine learning↗
DOE OSTI2021

The Swan: Data-driven Inference of Stellar Surface Gravities for Cool Stars from Photometric Light Curves

Stellar light curves are well known to encode physical stellar properties. Precise, automated, and computationally inexpensive methods to derive physical parameters from light curves are needed to cope with the large influx of these data from space-based missions such as Kepler and TESS. Here we present a new methodology that we call “The Swan,” a fast, generalizable, and effective approach for deriving stellar surface gravity (logg) for main-sequence, subgiant, and red giant stars from Kepler light curves using local linear regression on the full frequency content of Kepler long-cadence power spectra. With this inexpensive data-driven approach, we recover logg to a precision of ~0.02 dex for 13,822 stars with seismic logg values between 0.2 and 4.4 dex and ~0.11 dex for 4646 stars with Gaia-derived logg values between 2.3 and 4.6 dex. We further develop a signal-to-noise metric and find that granulation is difficult to detect in many cool main-sequence stars (T {sub eff} ≲ 5500 K), in particular K dwarfs. By combining our logg measurements with Gaia radii, we derive empirical masses for 4646 subgiant and main-sequence stars with a median precision of ~7%. Finally, we demonstrate that our method can be used to recover logg to a similar mean absolute deviation precision for a TESS baseline of 27 days. Our methodology can be readily applied to photometric time series observations to infer stellar surface gravities to high precision across evolutionary states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum limits of superconducting-photonic links and their extension to millimeter waves

Photonic addressing of superconducting circuits has been proposed to overcome wiring complexity and heat-load challenges. However, such superconducting-photonic links suffer from an efficiency-noise trade-off that limits scalability. This trade-off arises because increasing power conversion efficiency entails reducing optical power, which makes the converted signal susceptible to shot noise. We analyze this trade-off and find that the laser-driven qubit gate infidelity scales inversely with the number of photons used. While methods such as nonlinear detection or squeezed light could mitigate this effect, we consider generating higher-frequency electrical signals, such as millimeter waves (100 GHz), using laser light. At these higher frequencies, circuits have higher operating temperatures and cooling power budgets and alleviate constraints posed by the trade-off. Therefore, we demonstrate an optically driven cryogenic millimeter-wave source with a maximum power efficiency of 8 ×10 −5 that can generate a maximum of 0.7 μ⁢W of 80 GHz power, with a 1200-thermal-photon equivalent of added noise at 4K. Using this source, we perform frequency-domain spectroscopy of superconducting NbTiN resonators at 80–90 GHz. Our results show a promising approach to lessen the efficiency-noise constraints on superconducting-photonic links, while leveraging the benefits of photonic signal delivery. Further optimization of power efficiency and noise at high frequencies could make scalable photonic control of superconducting qubits viable at temperatures exceeding 1K.

Optoelectronics↗
DOE OSTI2025

New Ideas on the Formation and Astrophysical Detection of Primordial Black Holes

Recently, a number of novel scenarios for primordial black hole (PBH) formation have been discovered. Some of them require very minimal new physics, some others require no new ingredients besides those already present in commonly considered models, such as supersymmetry. At the same time, new strategies have emerged for detection of PBHs. For example, an observation of an orphan kilonova unaccompanied by the gravitational waves signal of merging neutron stars, but associated with a fast radio burst, could be a smoking gun of PBH dark matter. We review some new ideas for PBH formation and detection.

Flores, Marcos M.↗
DOE OSTI2024

Direct detection system for full-field nanoscale X-ray diffraction-contrast imaging

Recent developments in X-ray science provide methods to probe deeply embedded mesoscale grain structures and spatially resolve them using dark field X-ray microscopy (DFXM). Extending this technique to investigate weak diffraction signals such as magnetic systems, quantum materials and thin films prove challenging due to available detection methods and incident X-ray flux at the sample. We present a direct detection method developed in conjunction with KAImaging which focuses on DFXM studies in the hard X-ray range of 10s of keV and above capable of approaching nanoscale resolution. Additionally, we compare this direct detection scheme with routinely used scintillator-based optical detection and achieve an order of magnitude improvement in exposure times allowing for imaging of weakly diffracting ordered systems.

47 OTHER INSTRUMENTATION↗