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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Volume IV. The DUNE far detector single-phase technology

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. Central to achieving DUNE's physics program is a far detector that combines the many tens-of-kiloton fiducial mass necessary for rare event searches with sub-centimeter spatial resolution in its ability to image those events, allowing identification of the physics signatures among the numerous backgrounds. In the single-phase liquid argon time-projection chamber (LArTPC) technology, ionization charges drift horizontally in the liquid argon under the influence of an electric field towards a vertical anode, where they are read out with fine granularity. A photon detection system supplements the TPC, directly enhancing physics capabilities for all three DUNE physics drivers and opening up prospects for further physics explorations. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume IV presents an overview of the basic operating principles of a single-phase LArTPC, followed by a description of the DUNE implementation. Each of the subsystems is described in detail, connecting the high-level design requirements and decisions to the overriding physics goals of DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Specialized protist communities on mycorrhizal fungal hyphae

Abstract Arbuscular mycorrhizal (AM) fungi not only play a crucial role in acquiring nutrients for plants but also serve as a habitat for soil microbes. Recent studies observed that AM fungal hyphae are colonized by specific bacterial communities. However, so far it has not been explored whether fungal hyphae and mycorrhizal networks also harbor specific communities of protists, a key group of microbes in the soil microbiome. Here, we characterized protist communities in soil in a compartment with plant roots and on hyphae collected from hyphal compartments without plant roots. We detected specific protist communities on fungal hyphae. Fourteen protistan amplicon sequences variants (ASVs) were significantly associated with fungal hyphae, half of which belonged to the Cercozoa group. This research, for the first-time detected specific protist ASVs directly associated with abundant AM fungus hyphae, highlighting the complexity of the hyphal food web.

Mycology↗
DOE OSTI2023

Online detection of airborne nanoparticle composition with mass spectrometry: Recent advances, challenges, and opportunities

Airborne nanoparticles are receiving growing attention due to their impacts on human health, air quality, and climate. Additionally, there are increasing applications of aerosol-based nanotechnology. Real-time measurement of airborne nanoparticle composition is challenging due to their small masses and the difficulties in effectively separating them from larger particles. Custom-built instruments based on mass spectrometry have been developed for nanoparticle composition, including thermal desorption-based, laser-based, and solution-based techniques. They have significantly promoted the understanding of airborne nanoparticles in the last two decades. However, they are affected by molecular fragmentation, lack of mass-resolving power, incomplete species detection, and difficulties in directly comparing to gas-phase measurements. Recent developments in atmospheric mass spectrometry provide possible solutions. Here, this review presents the potential application of these new advances to real-time measurements of the molecular nanoparticle composition and discusses the associated challenges. Such measurements present opportunities for a more comprehensive view of airborne nanoparticles and their impacts.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Climatology and Evolution of the Antarctic Peninsula Föhn Wind-Induced Melt Regime From 1979–2018

Warm and dry föhn winds on the Antarctic Peninsula (AP) cause surface melt that can destabilize vulnerable ice shelves. Topographic funneling of these downslope winds through mountain passes and canyons can produce localized wind-induced melt that is difficult to quantify without direct measurements. Our Föhn Detection Algorithm (FöhnDA) identifies the surface föhn signature that causes melt from measurement by 12 Automatic Weather Stations on the AP, that train a machine learning model to detect föhn in 5 km Regional Atmospheric Climate Model 2 (RACMO2.3p2) simulations and in the ERA5 reanalysis model. We estimate the fraction of AP surface melt attributed to föhn and possibly katabatic winds and identify the drivers of melt, temporal variability, and long-term trends and evolution from 1979–2018. We find that föhn wind-induced melt accounts for 3.1% of the total melt on the AP and can be as high at 18% close to the mountains where the winds funnel through mountain canyons. Föhn-induced surface melt does not significantly increase from 1979–2018, despite a warmer atmosphere and more positive Southern Annular Mode. However, a significant increase (+0.1 Gt y-1) and subsequent decrease/stabilization occur in 1979–1998 and 1999–2018, consistent with the AP warming and cooling trends during the same time periods. Föhn occurrence, more than föhn strength, drives the annual variability in föhn-induced melt. Long-term föhn-induced melt trends and evolution are attributable to seasonal changes in föhn occurrence, with increased occurrence in summer, and decreased occurrence in fall, winter, and early spring over the past 20 years.

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

Integrating N -glycan and CODEX imaging reveal cell-specific protein glycosylation in healthy human lung

Identifying cell-specific glycan structures in human lungs is critical for understanding the chemistry and mechanisms that guide cell–cell and cell–matrix interactions and determining nuanced functions of specific glycosylation. Our dual-modality omics platform, which uses matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to profile glycan chemistry at 50 μm × 50 μm scale, combined with co-detection by indexing (CODEX) to provide cell identification from the exact same tissue section, is a significant step in this direction. It enabled us to detect, differentiate, and reveal chemical properties of N-glycans in the various cell types of a human lung, suggesting the cell-specific function of distinct carbohydrate moieties. This innovative technological combination bridges the gap between the specific protein glycosylation and their cellular origin, paving the way for targeted studies in the lungs and many other human tissues where glycans mediate cell–cell recognition events.

Veličković, Dušan [Pacific Northwest National Labo↗
DOE OSTI2021

Use of nucleic acid amplification testing for rapid detection of Mycobacterium tuberculosis complex among U.S. tuberculosis patients from 2011–2017

Background: Nucleic acid amplification (NAA) tests rapidly detect Mycobacterium tuberculosis complex directly from clinical specimens, providing valuable results for those evaluated for tuberculosis. Methods: We analyzed characteristics of cases with NAA testing performed, compared cases with positive and negative NAA test results, and calculated turnaround time and time to treatment for all verified cases reported to the National Tuberculosis Surveillance System in the United States during 2011–2017. Results: Among 67082 verified tuberculosis cases with NAA testing information, 30820 (45.9%) were reported as not having an NAA test performed; the proportion without NAA testing declined annually, from 60.5% in 2011 to 33.6% in 2017. Of 67082 verified cases, 27912 (41.6%) had positive, 8215 (12.2%) had negative, and 135 (0.2%) had indeterminate NAA test results. Among the 33937 cases with an acid-fast bacilli (AFB) smear-positive result, 24093 (70.9%) had an NAA test performed; 11490 of the 30244 (38.0%) with an AFB smear-negative result had an NAA test performed. Although sputum was the most common specimen type tested, 79.8% (7023/8804) of nonsputum specimen types had a positive NAA test result. Overall, 63.7% of cases with laboratory testing had NAA test results reported <6 days following specimen collection; for 13891 cases not yet on treatment, median time to treatment after the laboratory report date was 2 days. Conclusions: Our analyses demonstrate increased NAA test utilization between 2011 and 2017. However, a large proportion of cases did not have an NAA test performed, reflecting challenges in broader uptake, suggesting an opportunity to expand use of this diagnostic methodology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Prediction of spin polarized Fermi arcs in quasiparticle interference in CeBi

We predict that CeBi in the ferromagnetic state is a Weyl semimetal. Our calculations within density functional theory show the existence of two pairs of Weyl nodes on the momentum path (0,0,k z ) at 15meV above and 100meV below the Fermi level. Two corresponding Fermi arcs are obtained on surfaces of mirror-symmetric (010)-oriented slabs at E=15meV and both arcs are interrupted into three segments due to hybridization with a set of trivial surface bands. By studying the spin texture of surface states, we find the two Fermi arcs are strongly spin polarized but in opposite directions, which can be detected by spin-polarized ARPES measurements. Here, our theoretical study of quasiparticle interference (QPI) for a nonmagnetic impurity at the Bi site also reveals several features related to the Fermi arcs. Specifically, we predict that the spin polarization of the Fermi arcs leads to a bifurcation-shaped feature only in the spin-dependent QPI spectrum, serving as a fingerprint of the Weyl nodes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

BICEP/ K e c k XIV: Improved constraints on axionlike polarization oscillations in the cosmic microwave background

We present an improved search for axionlike polarization oscillations in the cosmic microwave background (CMB) with observations from the Keck Array . An all-sky, temporally sinusoidal rotation of CMB polarization, equivalent to a time-variable cosmic birefringence, is an observable manifestation of a local axion field and potentially allows a CMB polarimeter to detect axionlike dark matter directly. We describe improvements to the method presented in previous work, and we demonstrate the updated method with an expanded dataset consisting of the 2012–2015 observing seasons. We set limits on the axion-photon coupling constant for mass m in the range 10 - 23 – 10 - 18 eV , which corresponds to oscillation periods on the order of hours to years. Our results are consistent with the background model. For periods between 1 and 30 d ( 1.6 × 10 - 21 ≤ m ≤ 4.8 × 10 - 20 eV ), the 95%-confidence upper limits on rotation amplitude are approximately constant with a median of 0.27°, which constrains the axion-photon coupling constant to g φ γ < ( 4.5 × 10 - 12 GeV - 1 ) m / ( 10 - 21 eV ) , if axionlike particles constitute all of the dark matter. More than half of the collected BICEP dataset has yet to be analyzed, and several current and future CMB polarimetry experiments can apply the methods presented here to achieve comparable or superior constraints. In the coming years, oscillation measurements can achieve the sensitivity to rule out unexplored regions of the axion parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Termination switching of antiferromagnetic proximity effect in topological insulator

This work reports the ferromagnetism of topological insulator, (Bi,Sb) 2 Te 3 (BST), with a Curie temperature of approximately 120 K induced by magnetic proximity effect (MPE) of an antiferromagnetic CrSe. The MPE was shown to be highly dependent on the stacking order of the heterostructure, as well as the interface symmetry: Growing CrSe on top of BST results in induced ferromagnetism, while growing BST on CrSe yielded no evidence of an MPE. Cr-termination in the former case leads to double-exchange interactions between Cr 3+ surface states and Cr 2+ bulk states. This Cr 3+ -Cr 2+ exchange stabilizes the ferromagnetic order localized at the interface and magnetically polarizes the BST Sb band. In contrast, Se-termination at the CrSe/BST interface yields no detectable MPE. These results directly confirm the MPE in BST films and provide critical insights into the sensitivity of the surface state.

42 ENGINEERING↗
DOE OSTI2025

Higgs-portal dark matter in Brane-world cosmology

Abstract The Higgs-portal scalar dark matter (DM) model is a simple extension of the Standard Model (SM) to incorporate a DM particle to the SM, where a $$Z_2$$ Z 2 -odd real scalar field is introduced as a DM candidate. We consider this DM model in the context of 5-dimensional brane-world cosmology, where our 3-dimensional space is realized as a hyper-surface embedded in 4-dimensional space. In the setup, all the SM and DM fields reside on the hyper-surface while graviton lives in the bulk. We consider two well-known brane-world cosmologies, namely, the Randall–Sundrum (RS) and the Gauss–Bonnet (GB) brane-world cosmologies, in which the standard Big Bang cosmology is reproduced at low temperatures below the so-called “transition temperature” while at high temperatures the expansion law of the universe is significantly modified. Such a non-standard expansion law directly impacts the prediction for the relic density of the Higgs-portal DM. We investigate the brane-world cosmological effects and identify the allowed model parameter region by combining the constraints from the observed DM relic density, and the direct and indirect DM detection experiments. It is well-known that only DM masses in the vicinity of half the Higgs boson mass are allowed in the Higgs-portal scalar DM model. We find that the allowed parameter region becomes more severely constrained and even disappears in the RS cosmology, while the GB cosmological effect significantly enlarges the allowed region. Upon discovering Higgs-portal DM, we can determine transition temperature in the GB brane-world cosmology.

Liu, Taoli↗
DOE OSTI2020

Noncontact Flow Rate Using Laser Ultrasonics

Several types of advanced nuclear reactors are cooled with high-temperature liquid metal or molten salt flows. There is a critical need to measure flow velocity in flow channels for test purposes, and eventually in operational reactors. In conventional ultrasonic flow sensors, ultrasonic waves traveling in both the upstream and downstream directions are generated and detected by transducers that must contact the flow channels. A shift in the frequency or transit time between the two ultrasonic waves is measured to determine flow velocity. We describe here an initial effort to apply that sensing concept when the contact transducers are replaced by laser-based generation and detection instrumentation. This noncontact sensing avoids many practical problems associated with contact transducers when implemented on flow channels at high temperature. Laser-based flow monitoring can also be applied to hot-process piping in the geothermal energy, chemical-processing and petroleum-refining industries. Our effort has included theoretical simulation of noncontact laser-based flow monitoring, indicating capability of measuring flow velocities relevant to reactor cooling. It also included a room-temperature experimental demonstration using water as the flow liquid, and indicating capability of measuring flow velocity at a responsivity roughly consistent with simulation predictions. Plans were made for an experimental demonstration at Oregon State University using liquid metal at 110 degrees C.

02 PETROLEUM↗
DOE OSTI2021

Mid-infrared Pulsed Upconversion Imaging in a Rotating Detonation Combustor

To meet the challenges associated with performing mid-InfraRed (IR) imaging in Rotating Detonation Combustors (RDCs), a novel pulsed mid-IR UpConversion Imaging (UCI) diagnostic has been implemented. UCI is an alternative to direct mid-IR detection that uses nonlinear optical frequency mixing to shift mid-IR wavelengths carrying a target image to shorter wavelengths that can be imaged with high-performance silicon-based CCD/CMOS cameras. This approach offers several favorable properties including high spectral selectivity, high temporal resolution, and superior low-light detectivity. A hydrogen-air research RDC was operated with carbon dioxide addition to allow pulsed UCI imaging of mid-IR luminosity within the combustion channel from spontaneous thermal emissions. The resulting measurements demonstrate high spatiotemporal resolution capable of imaging small structures near the supersonically propagating detonation wave front. The results show how this technique can be used to observe sharp gradients and millimeter-scale structures in the high-temperature, high-pressure zones RDC flow fields.

White, Logan W.↗
DOE OSTI2022

The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS

The Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Balancing Trade-Offs Imposed by Growth Media and Mass Spectrometry for Bacterial Exometabolomics

The bacterial exometabolome consists of a vast array of specialized metabolites, many of which are only produced in response to specific environmental stimuli. For this reason, it is desirable to control the extracellular environment with a defined growth medium composed of pure ingredients. However, complex (undefined) media are expected to support the robust growth of a greater variety of microorganisms than defined media. Here, we investigate the trade-offs inherent to a range of complex and defined solid media for the growth of soil microorganisms, production of specialized metabolites, and detection of these compounds using direct infusion mass spectrometry. We find that complex media support growth of more soil microorganisms, as well as allowing for the detection of more previously discovered natural products as a fraction of total m/z features detected in each sample. However, the use of complex media often caused mass spectrometer injection failures and poor-quality mass spectra, which in some cases resulted in over a quarter of samples being removed from analysis. Defined media, while more limiting in growth, generated higher quality spectra and yielded more m/z features after background subtraction. These results inform future exometabolomic experiments requiring a medium that supports the robust growth of many soil microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

A Frequency-Domain-Based Algorithm for Detecting Microseismicity Using Dense Surface Seismic Arrays

We propose a new frequency-domain-based algorithm for detecting small-magnitude seismic events using dense surface seismic arrays. Our proposed method takes advantage of the high energy carried by S waves, and approximate known source locations, which are used to rotate the horizontal components to obtain the maximum amplitude. By surrounding the known source area with surface geophones, we achieve a favorable geometry for locating the detected seismic events with the backprojection method. To test our new detection method, we used a dense circular array, consisting of 151 5 Hz three-component geophones, over a 5 km aperture that was in operation at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah. We apply the new detection method during a small-scale test injection phase at FORGE, and during an aftershock sequence of an Mw 4.1 earthquake located ~30 km north of the geophone array, within the Black Rock volcanic field. We are able to detect and locate microseismic events (Mw<0) during injections, despite the high level of anthropogenic activity, and several aftershocks that are missing from the regional catalog. By comparing our method with known algorithms that operate both in the time and frequency domain, we show that our proposed method performs better in the case of the FORGE injection monitoring, and equally well for the off-array aftershock sequence. Our new method has the potential to improve microseismic event detections even in extremely noisy environments, and the proposed location scheme serves as a direct discriminant between true and false detections.

Geochemistry & Geophysics↗
DOE OSTI2024

Energy Delivery Systems with Verifiable Trustworthiness (Final Report)

Energy Delivery Systems (EDS) must be verified to be free from intrusive and malicious software. One way of verifying this software is to perform device scans to detect malicious code. Because it is possible to have “fileless” malware that exists only in device (volatile) memory, offline scanning and even many forms of online scanning is insufficient for detection. This project (“Verify”) addresses this need by performing direct sampling of memory during device operation to detect unexpected or modified software while not interfering with device operation. The Verify project provides a proof-of-concept of detection by random sampling combined with remote software- and timing-based attestation methods for robust detection of in-memory threats. An external review of Verify was performed by our partner, General Electric (GE), and a summary of their findings is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Jamming Detection for Low-Resolution SC-FDE Systems: A Machine Learning Approach

Jammers interfere with communication between base stations (BSs) and legitimate users, leading to degradation of wireless system performance. Our study focuses on jamming detection for wideband single-carrier frequency domain equalization (SC-FDE) systems with low-resolution analog-to digital converters (ADCs). In such systems, jamming detection is challenging because traditional analytical approaches cannot be directly applied due to the delay dispersion in wideband channels and the non-linearity induced by low-resolution ADCs. We propose a machine learning (ML)-based jamming detection method that directly uses the quantized receive signals. Significantly, our ML-based detector can be integrated into existing standard frameworks, such as unique word (UW)-based SC-FDE systems, as it uses existing pilots without requiring additional pilots for jamming detection. Through numerical simulations, we show that two or more bits provide satisfactory performance compared to unquantized scenarios. Additionally, we demonstrate that using more and well-separated pilot symbols improves performance.

99 GENERAL AND MISCELLANEOUS↗