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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 OSTI2015

A SPECTROSCOPIC AND PHOTOMETRIC EXPLORATION OF THE C/M RATIO IN THE DISK OF M31

We explore the ratio (C/M) of carbon-rich to oxygen-rich thermally pulsing asymptotic giant branch (TP-AGB) stars in the disk of M31 using a combination of moderate-resolution optical spectroscopy from the Spectroscopic Landscape of Andromeda’s Stellar Halo survey and six-filter Hubble Space Telescope photometry from the Panchromatic Hubble Andromeda Treasury survey. Carbon stars were identified spectroscopically. Oxygen-rich M-stars were identified using three different photometric definitions designed to mimic, and thus evaluate, selection techniques common in the literature. We calculate the C/M ratio as a function of galactocentric radius, present-day gas-phase oxygen abundance, stellar metallicity, age (via proxy defined as the ratio of TP-AGB stars to red giant branch, stars), and mean star formation rate over the last 400 Myr. We find statistically significant correlations between log(C/M) and all parameters. These trends are consistent across different M-star selection methods, though the fiducial values change. Of particular note is our observed relationship between log(C/M) and stellar metallicity, which is fully consistent with the trend seen across Local Group satellite galaxies. The fact that this trend persists in stellar populations with very different star formation histories indicates that the C/M ratio is governed by stellar properties alone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CY2019 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2019–December 2019), Revision 1

Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2019. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2019 as compared to measurements in 2018. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2019 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, though changes from 2018 to 2019 are minimal. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2019. Rising water-level trends continue to be observed in Well ER-5-3 deep piezometer and former water supply Well WW-5A. Water supply Well WW-5B experienced a rise in water level as a result of an absence of pumping in the first part of the year (due to a mechanical problem), whereas water levels declined in WW-4 and WW-4A in response to greater pumping in 2019. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A simple model of COVID-19 explains disease severity and the effect of treatments

Abstract Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Probing the structure and function of the protease domain of botulinum neurotoxins using single-domain antibodies

Botulinum neurotoxins (BoNTs) are among the deadliest of bacterial toxins. BoNT serotype A and B in particular pose the most serious threat to humans because of their high potency and persistence. To date, there is no effective treatment for late post-exposure therapy of botulism patients. Here, we aim to develop single-domain variable heavy-chain (VHH) antibodies targeting the protease domains (also known as the light chain, LC) of BoNT/A and BoNT/B as antidotes for post-intoxication treatments. Using a combination of X-ray crystallography and biochemical assays, we investigated the structures and inhibition mechanisms of a dozen unique VHHs that recognize four and three non-overlapping epitopes on the LC of BoNT/A and BoNT/B, respectively. We show that the VHHs that inhibit the LC activity occupy the extended substrate-recognition exosites or the cleavage pocket of LC/A or LC/B and thus block substrate binding. Notably, we identified several VHHs that recognize highly conserved epitopes across BoNT/A or BoNT/B subtypes, suggesting that these VHHs exhibit broad subtype efficacy. Further, we identify two novel conformations of the full-length LC/A, that could aid future development of inhibitors against BoNT/A. Our studies lay the foundation for structure-based engineering of protein- or peptide-based BoNT inhibitors with enhanced potencies and cross-subtypes properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Molecular Electrocatalysts for Oxidation of Hydrogen Using Earth-Abundant Metals: Shoving Protons Around with Proton Relays

Sustainable, carbon-neutral energy is needed to supplant the worldwide reliance on fossil fuels, to address the persistent problem of increasing emissions of CO 2 . Solar and wind energy are intermittent, highlighting the need to develop energy storage on a huge scale. Electrocatalysts provide a way to convert between electrical energy generated by renewable energy sources and chemical energy in the form of chemical bonds. Here, the oxidation of hydrogen to give two electrons and two protons is carried out in fuel cells, but the typical catalyst is platinum, a precious metal of low earth-abundance and high cost. In nature, hydrogenases based on iron or iron/nickel reversibly oxidize hydrogen with remarkable efficiency and rates. Functional models of these enzymes are synthesized with the goal of achieving electrocatalytic H 2 oxidation using inexpensive, earth-abundant metals along with a key feature identified in the [FeFe]-hydrogenase: an amine base positioned near the metal. The diphosphine ligands P R 2 N R' 2 (1,5-diaza-3,7-diphosphacyclooctane with alkyl or aryl groups on the P and N) are used as ligands in Ni, Fe and Mn complexes. The pendant amines promote binding and heterolytic cleavage of H 2 , placing the hydride on the metal and the proton on the amine. The pendant amines also serve as proton relays, accelerating intramolecular and intermolecular proton transfers. Electrochemical oxidations and deprotonations by an exogeneous amine base lead to catalytic cycles for oxidation of H 2 (1 atm) at room temperature for catalysts derived from [Ni(P Cy 2 N R' 2 ) 2 ] 2+ , Cp C6F5 Fe(P tBu 2 N Bn 2 )H and MnH(P Ph 2 N Bn 2 )(bppm)(CO) [bppm = (PAr F 2 ) 2 CH 2 )]. The Mn cation [Mn(P Ph 2 N Bn 2 )(bppm)(CO)] + mediates the rapid (>10 4 s -1 at -95 °C), reversible heterolytic cleavage of H 2 . Obtaining the optimal benefit of pendant amines incorporated into the ligand requires that the pendant amine be properly positioned to interact with a M-H or M(H 2 ) bond. In addition, ligands are ideally selected such that the hydride acceptor ability of the metal and the basicity of a pendant are tuned to give low barriers for heterolytic cleavage of the H-H bond and for subsequent proton transfer reactions. Using these principles allows the rational design of electrocatalysts for H 2 oxidation using earth-abundant metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing

The application of data science in cancer research has been boosted by major advances in three primary areas: (1) Data: diversity, amount, and availability of biomedical data; (2) Advances in Artificial Intelligence (AI) and Machine Learning (ML) algorithms that enable learning from complex, large-scale data; and (3) Advances in computer architectures allowing unprecedented acceleration of simulation and machine learning algorithms. These advances help build in silico ML models that can provide transformative insights from data including: molecular dynamics simulations, next-generation sequencing, omics, imaging, and unstructured clinical text documents. Unique challenges persist, however, in building ML models related to cancer, including: (1) access, sharing, labeling, and integration of multimodal and multi-institutional data across different cancer types; (2) developing AI models for cancer research capable of scaling on next generation high performance computers; and (3) assessing robustness and reliability in the AI models. In this paper, we review the National Cancer Institute (NCI) -Department of Energy (DOE) collaboration, Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), a multi-institution collaborative effort focused on advancing computing and data technologies to accelerate cancer research on three levels: molecular, cellular, and population. This collaboration integrates various types of generated data, pre-exascale compute resources, and advances in ML models to increase understanding of basic cancer biology, identify promising new treatment options, predict outcomes, and eventually prescribe specialized treatments for patients with cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Do Arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulations

Abstract. Mixed-phase clouds are ubiquitous in the Arctic. These clouds can persist for days and dissipate in a matter of hours. It is sometimes unknown what causes this sudden dissipation, but aerosol–cloud interactions may be involved. Arctic aerosol concentrations can be low enough to affect cloud formation and structure, and it has been hypothesized that, in some instances, concentrations can drop below some critical value needed to maintain a cloud. We use observations from a Department of Energy ARM site on the northern slope of Alaska at Oliktok Point (OLI), the Arctic Summer Cloud Ocean Study (ASCOS) field campaign in the high Arctic Ocean, and the Integrated Characterisation of Energy, Clouds, Atmospheric state, and Precipitation at Summit – Aerosol Cloud Experiment (ICECAPS-ACE) project at the NSF (National Science Foundation) Summit Station in Greenland (SMT) to identify one case per site where Arctic boundary layer clouds dissipated coincidentally with a decrease in surface aerosol concentrations. These cases are used to initialize idealized large eddy simulations (LESs) in which aerosol concentrations are held constant until, at a specified time, all aerosols are removed instantaneously – effectively creating an extreme case of aerosol-limited dissipation which represents the fastest a cloud could possibly dissipate via this process. These LESs are compared against the observed data to determine whether cases could, potentially, be dissipating due to insufficient aerosol. The OLI case's observed liquid water path (LWP) dissipated faster than its simulation, indicating that other processes are likely the primary drivers of the dissipation. The ASCOS and SMT observed LWP dissipated at similar rates to their respective simulations, suggesting that aerosol-limited dissipation may be occurring in these instances. We also find that the microphysical response to this extreme aerosol forcing depends greatly on the specific case being simulated. Cases with drizzling liquid layers are simulated to dissipate by accelerating precipitation when aerosol is removed while the case with a non-drizzling liquid layer dissipates quickly, possibly glaciating via the Wegener–Bergeron–Findeisen (WBF) process. The non-drizzling case is also more sensitive to ice-nucleating particle (INP) concentrations than the drizzling cases. Overall, the simulations suggest that aerosol-limited cloud dissipation in the Arctic is plausible and that there are at least two microphysical pathways by which aerosol-limited dissipation can occur.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Activation of Notch1 inhibits medial edge epithelium apoptosis in all-trans retinoic acid-induced cleft palate in mice

Administration of all-trans retinoic acid (atRA) on E12.0 (embryonic day 12.0) leads to failure of medial edge epithelium (MEE) disappearance and cleft palate. However, the molecular mechanism underlying the relationship between atRA and MEE remains to be identified. In this study, atRA (200 mg/kg) administered by gavage induced a 75% incidence of cleft palate in C57BL/6 mice. Notch1 was up-regulated in MEE cells in the atRA-treated group compared with the controls at E15.0, together with reduced apoptosis and elevated proliferation. Next, we investigated the mechanisms underlying atRA, Notch1 and MEE degradation in palate organ culture. Our results revealed that down-regulation of Notch1 partially rescued the inhibition of atRA-induced palate fusion. Molecular analysis indicated that atRA increased the expression of Notch1 and Rbpj and decreased the expression of P21. In addition, depletion of Notch1 expression decreased the expression of Rbpj and increased the expression of P21. Moreover, inhibition of Rbpj expression partially reversed atRA-induced MEE persistence and increased P21 expression. These findings demonstrate that atRA inhibits MEE degradation, which in turn induces a cleft palate, possibly through the Notch1/RBPjk/P21 signaling pathway. - Highlights: • atRA exposure on E12.0 induced MEE persistence and cleft palate. • Notch1 was up-regulated in MEE cells in the atRA-treated embryos. • atRA inhibits MEE degradation, which in turn induces cleft palate, possibly through the Notch1/RBPjk/P21 signaling pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The persistence of large scale structures. Part I. Primordial non-Gaussianity

Abstract We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology . Persistent homology is a technique from topological data analysis that quantifies the multiscale topology of a data set, in our context unifying the contributions of clusters, filament loops, and cosmic voids to cosmological constraints. We describe how this method captures the imprint of primordial local non-Gaussianity on the late-time distribution of dark matter halos, using a set of N-body simulations as a proxy for real data analysis. For our best single statistic, running the pipeline on several cubic volumes of size 40 (Gpc/h) 3 , we detect f NL loc =10 at 97.5% confidence on ~ 85% of the volumes. Additionally wetest our ability to resolve degeneracies betweenthe topological signature of f NL loc and variation of σ 8 and argue that correctly identifying nonzero f NL loc in this case is possible via an optimal template method. Our method relies on information living at $\mathcal{O}$(10) Mpc/h, a complementary scale with respect to commonly used methods such as the scale-dependent bias in the halo/galaxy power spectrum. Therefore, while still requiring a large volume, our method does not require sampling long-wavelength modes to constrain primordial non-Gaussianity. Moreover, our statistics are interpretable: we are able to reproduce previous results in certain limits and we make new predictions for unexplored observables, such as filament loops formed by dark matter halos in a simulation box.

Astronomy & Astrophysics↗
DOE OSTI2014

SU-E-J-16: A Review of the Magnitude of Patient Imaging Shifts in Relation to Departmental Policy Changes

Purpose: To evaluate how changes in imaging policy affect the magnitude of shifts applied to patients. Methods: In June 2012, the department's imaging policy was altered to require that any shifts derived from imaging throughout the course of treatment shall be considered systematic only after they were validated with two data points that are consistent in the same direction. Multiple additions and clarifications to the imaging policy were implemented throughout the course of the data collection, but they were mostly of administrative nature. Entered shifts were documented in MOSAIQ (Elekta AB) through the localization offset. The MOSAIQ database was queried to identify a possible trend. A total of 25,670 entries were analyzed, including four linear accelerators with a combination of MV planar, kV planar and kV three dimensional imaging. The monthly average of the magnitude of the vector was used. Plan relative offsets were excluded. During the evaluated period of time, one of the satellite facilities acquired and implemented Vision RT (AlignRT Inc). Results: After the new policy was implemented the shifts variance and standard deviation decreased. The decrease is linear with time elapsed. Vision RT implementation at one satellite facility reduced the number of overall shifts, specifically for breast patients. Conclusion: Changes in imaging policy have a significant effect on the magnitude of shifts applied to patients. Using two statistical points before applying a shift as persistent decreased the overall magnitude of the shifts applied to patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

"BAAE" instabilities observed without fast ion drive

The instability that was previously identified as a fast-ion driven beta-induced Alfv´en-acoustic eigenmode (BAAE) in DIII-D was misidentified. In a dedicated experiment, low frequency modes (LFM) with characteristic “Christmas light” patterns of brief instability linked to the safety factor evolution occur in plasmas with electron temperature T e ≳ 2.1 keV but modest beta. To isolate the importance of different driving gradients on these modes, the electron cyclotron heating power and 80 keV, sub-Alfv´enic neutral beams are altered for 50-100 ms durations in reproducible discharges. Although beta-induced Alfv´en eigenmodes and reversed-shear Alfv´en eigenmodes stabilize when beam injection ceases (as expected for a fast-ion driven instability), the low frequency modes that were called BAAEs persist. Data mining reveals that characteristic LFM instabilities can occur in discharges with no beam heating but strong electron cyclotron heating. A large database of over 1000 discharges shows that LFMs are only unstable in plasmas with hot electrons but modest overall beta. The experimental LFMs have low frequencies (comparable to diamagnetic drift frequencies) in the plasma frame, occur near the minimum of the safety factor q min , and appear when q min is close to rational values. In conclusion, theoretical analysis suggests that the LFMs are a low frequency reactive instability of predominately Alfv´enic polarization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Cusps enable line attractors for neural computation

Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Regional Feedstock Partnership Summary Report: Enabling the Billion-Ton Vision

The U.S. Department of Energy (DOE) and the Sun Grant Initiative established the Regional Feedstock Partnership (referred to as the Partnership) to address information gaps associated with enabling the vision of a sustainable, reliable, billion-ton U.S. bioenergy industry by the year 2030 (i.e., the Billion-Ton Vision). Over the past 7 years (2008–2014), the Partnership has been successful at advancing the biomass feedstock production industry in the United States, with notable accomplishments. The Billion-Ton Study identifies the technical potential to expand domestic biomass production to offset up to 30% of U.S. petroleum consumption, while continuing to meet demands for food, feed, fiber, and export. This study verifies for the biofuels and chemical industries that a real and substantial resource base could justify the significant investment needed to develop robust conversion technologies and commercial-scale facilities. DOE and the Sun Grant Initiative established the Partnership to demonstrate and validate the underlying assumptions underpinning the Billion-Ton Vision to supply a sustainable and reliable source of lignocellulosic feedstock to a large-scale bioenergy industry. This report discusses the accomplishments of the Partnership, with references to accompanying scientific publications. These accomplishments include advances in sustainable feedstock production, feedstock yield, yield stability and stand persistence, energy crop commercialization readiness, information transfer, assessment of the economic impacts of achieving the Billion-Ton Vision, and the impact of feedstock species and environment conditions on feedstock quality characteristics.

09 BIOMASS FUELS↗
DOE OSTI2023

SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Ultra-Low Amounts of Transition Metals in Carbon-Based Catalysts Improve Their Alkaline OER Performance: A Systematic Study

The pursuit of green hydrogen production highlights a persistent gap in electrocatalyst research: while academic efforts prioritize cost-efficiency via activity enhancement, industrial viability demands greater emphasis on electrochemical stability. Carbon-based electrocatalysts, particularly those incorporating transition metals, have shown promise in alkaline oxygen evolution (OER) due to their high activity, cost-efficiency, and resource-efficiency. However, these catalysts suffer from insufficient stability under oxidizing conditions compared to pure transition metal catalysts due to erosion of the carbon support resulting from carbon corrosion, among other degradation mechanisms. In this systematic study, the influence of ultra-low amounts (<1 wt %) of iron, cobalt, nickel, and their most common combinations on the stability of a hydrothermally derived, N-doped carbon support and the overall catalyst performance during alkaline OER is systematically explored. By identifying critical stability descriptors and correlating them with synthesis conditions and catalyst properties, primary and secondary corrosion pathways are unraveled. Subsequently, through careful adjustment of carbonization temperature and composition of incorporated transition metals, overall catalyst corrosion can be suppressed immensely. Especially, the inclusion of Ni and Fe is paramount for the formation of stable catalyst materials under laboratory conditions (10 mA/cm 2 in 0.1 M KOH), which is surprisingly unconstrained by the degree of graphitization of the carbon support. Mixing this electrochemically stable material with a graphitic carbon powder results in an excellent stability of over 400 h at 100 mA/cm 2 in 1 M KOH, implying great potential for the future improvement of carbon-based electrodes under oxidizing conditions toward industrial application.

N-doped carbon↗
DOE OSTI2025

Bacterial response to the 2021 Orange County, California, oil spill was episodic but subtle relative to natural fluctuations

ABSTRACT An oil spill began in October 2021 off the coast of Orange County, California, releasing 24,696 gallons of crude oil into coastal environments. Although oil spills, such as this one, are recurrent accidents along the California coast, no prior studies have been performed to examine the severity of the local bacterial response. A coastal 10-year time series of short-read metagenomes located within the impacted area allowed us to quantify the magnitude and duration of the disturbance relative to natural fluctuations. We found that the largest change in bacterial beta-diversity occurred at the end of October. The change in taxonomic beta-diversity corresponded with an increase in the sulfur-oxidizing clade Candidatus Thioglobus, an increase in the total relative abundance of potential hydrocarbon-degrading bacteria, and an anomalous decline in the picocyanobacteria Synechococcus . Similarly, changes in function were related to anomalous declines in photosynthetic pathways and anomalous increases in sulfur metabolism pathways as well as aromatic degradation pathways. There was a lagged response in taxonomy and function to peaks in total PAHs. One week after peaks in total PAH concentrations, the largest shifts in taxonomy were observed, and 1 week after the taxonomy shifts were observed, unique functional changes were seen. This response pattern was observed twice during our sampling period, corresponding with the combined effect of resuspended PAHs and increased nutrient concentrations due to physical transport events. Thus, the impact of the spill on bacterial communities was temporally extended and demonstrates the need for continued monitoring for longer than 3 months after initial oil exposure. IMPORTANCE Oil spills are common occurrences in waterways, releasing contaminants into the aquatic environment that persist for long periods of time. Bacterial communities are rapid responders to environmental disturbances, such as oil spills. Within bacterial communities, some members will be susceptible to the disturbance caused by crude oil components and will decline in abundance, whereas others will be opportunistic and will be able to use crude oil components for their metabolism. In many cases, when an oil spill occurs, it is difficult to assess the oil spill’s impact because no samples were collected prior to the accident. Here, we examined the bacterial response to the 2021 Orange County oil spill using a 10-year time series that lies within the impacted area. The results presented here are significant because (i) susceptible and opportunistic taxa to oil spills within the coastal California environment are identified and (ii) the magnitude and duration of the in situ bacterial response is quantified for the first time.

Brock, Melissa L. (ORCID:0000000340329241)↗
DOE OSTI2023

Entanglement structures in quantum field theories: Negativity cores and bound entanglement in the vacuum

Here, the many-body entanglement between two finite (size-d) disjoint vacuum regions of noninteracting lattice scalar field theory in one spatial dimension, i.e., a (d A × d B ) mixed Gaussian continuous variable system, is locally transformed into a tensor-product core of (1 A × 1 B ) mixed entangled pairs. Accessible entanglement within these core pairs exhibits an exponential hierarchy and as such identifies the structure of dominant region modes from which vacuum entanglement could be extracted into a spatially separated pair of quantum detectors. Beyond the core, the remaining modes of the halo are determined to be AB separable in isolation, as well as separable from the core. However, state preparation protocols that distribute entanglement in the form of (1 A × 1 B ) mixed core pairs are found to require additional entanglement in the halo that is obscured by classical correlations. This inaccessible (bound) halo entanglement is found to mirror the accessible entanglement, but with a step behavior as the continuum is approached. It remains possible that alternate initialization protocols that do not utilize the exponential hierarchy of core-pair entanglement may require less inaccessible entanglement. Entanglement consolidation is expected to persist in higher dimensions and may aid classical and quantum simulations of asymptotically free gauge field theories, such as quantum chromodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗