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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Low Thermal Conductivity Thermal Barrier Coatings Developed

Thermal barrier coatings (TBCs) are used extensively in modern gas turbine engines to thermally insulate air-cooled metallic components from the hot gases in the engine. These coatings typically consist of a zirconia-yttria ceramic that has been applied by either plasma spraying or physical vapor deposition. Future engines will rely even more heavily on TBCs and will require materials that have even higher temperature capability with improved insulation (i.e., lower thermal conductivity even after many hours at high temperature). This report discusses new TBCs that have been developed with these future requirements in mind. The Ultra-Efficient Engine Technology Program at the NASA Glenn Research Center is funding this effort, which has been conducted primarily at Glenn with contractor support (GE and Howmet) for physical vapor deposition. As stated, the new TBC not only had to be more insulating but the insulation had to persist even after many hours of exposure-that is, the new TBC had to have both lower conductivity and improved sintering resistance. A new type of test rig was developed for this task. This new test approach used a laser to deliver a known high heat flux in an essentially uniform pattern to the surface of the coating, thereby establishing a realistic thermal gradient across its thickness. This gradient was determined from surface and backside pyrometry; and since the heat flux and coating thickness are known, this permitted continuous monitoring of thermal conductivity. Thus, this laser rig allowed very efficient screening of candidate low-conductivity, sinter-resistant TBCs. The coating-design approach selected for these new low-conductivity TBCs was to identify oxide dopants that had the potential to promote the formation of relatively large and stable groupings of defects known as defect clusters. This approach was used because it was felt that such clusters would reduce conductivity while enhancing stability. The approach proved to be successful: low-conductivity TBCs having improved sintering resistance were developed.

Zhu, Dongming↗
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↗
DOE OSTI2024

Helical dynamo growth and saturation at modest versus extreme magnetic Reynolds numbers

Understanding magnetic field growth in astrophysical objects is a persistent challenge. In stars and galaxies, turbulent flows with net kinetic helicity are believed to be responsible for driving large-scale magnetic fields. However, numerical simulations have demonstrated that such helical dynamos in closed volumes saturate at lower magnetic field strengths when increasing the magnetic Reynolds number Rm . This would imply that helical large-scale dynamos cannot be efficient in astrophysical bodies without the help of helicity outflows such as stellar winds. But do these implications actually apply for very large Rm ? Here we tackle the long-standing question of how much helical large-scale dynamo growth occurs independent of Rm in a closed volume. We analyze data from numerical simulations with a new method that tracks resistive versus nonresistive drivers of helical field growth. We identify a presaturation regime when the large-scale field grows at a rate independent of Rm , but to an Rm -dependent magnitude. The latter Rm dependence is due to a dominant resistive contribution, but whose fractional contribution to the large-scale magnetic energy decreases with increasing Rm . We argue that the resistive contribution would become negligible at large Rm and an Rm -independent dynamical contribution would dominate if the current helicity spectrum in the inertial range is steeper than k 0 . As such helicity spectra are plausible, this renews optimism for the relevance of closed dynamos. Our work pinpoints how modest Rm simulations can cause misapprehension of the Rm → ∞ behavior. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Analysis of Salmonella enterica Isolated from a Mixed-Use Watershed in Georgia, USA: Antimicrobial Resistance, Serotype Diversity, and Genetic Relatedness to Human Isolates

As the cases of Salmonella enterica infections associated with contaminated water are increasing, this study was conducted to address the role of surface water as a reservoir of S. enterica serotypes. We sampled rivers and streams (n = 688) over a 3-year period (2015 to 2017) in a mixed-use watershed in Georgia, USA, and 70.2% of the total stream samples tested positive for Salmonella. A total of 1,190 isolates were recovered and characterized by serotyping, antimicrobial susceptibility testing, and pulsed-field gel electrophoresis (PFGE). A wide range of serotypes was identified, including those commonly associated with humans and animals, with S. enterica serotype Muenchen being predominant (22.7%) and each serotype exhibiting a high degree of strain diversity by PFGE. About half (46.1%) of the isolates had PFGE patterns indistinguishable from those of human clinical isolates in the CDC PulseNet database. A total of 52 isolates (4.4%) were resistant to antimicrobials, out of which 43 isolates were multidrug resistant (MDR; resistance to two or more classes of antimicrobials). These 52 resistant Salmonella isolates were screened for the presence of antimicrobial resistance genes, plasmid replicons, and class 1 integrons, out of which four representative MDR isolates were selected for whole-genome sequencing analysis. The results showed that 28 MDR isolates resistant to 10 antimicrobials had blacmy-2 on an A/C plasmid. Persistent contamination of surface water with a high diversity of Salmonella strains, some of which are drug resistant and genetically indistinguishable from human isolates, supports a role of environmental surface water as a reservoir for and transmission route of this pathogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Protein-based forensic identification using genetically variant peptides in human bone

Bone tissue contains organic material that is useful for forensic investigations and may contain preserved endogenous protein that can persist in the environment for extended periods of time over a range of conditions. Single amino acid polymorphisms in these proteins reflect genetic information since they result from non-synonymous single nucleotide polymorphisms (SNPs) in DNA. Detection of genetically variant peptides (GVPs) — those peptides that contain amino acid polymorphisms — in digests of bone proteins allows for the corresponding SNP alleles to be inferred. Resulting genetic profiles can be used to calculate statistical measures of association between a bone sample and an individual. In this study proteomic analysis on rib cortical bone samples from 10 recently deceased individuals demonstrates this concept. A straight-forward acidic demineralization protocol yielded proteins that were digested with trypsin. Tryptic digests were analyzed by liquid chromatography mass spectrometry. A total of 1736 different proteins were identified across all resulting datasets. On average, individual samples contained 454 ± 121 ($\bar{x}$ ± σ) proteins. Thirty-five genetically variant peptides were identified from 15 observed proteins. Overall, 134 SNP inferences were made based on proteomically detected GVPs, which were confirmed by sequencing of subject DNA. Inferred individual SNP genetic profiles ranged in random match probability (RMP) from 1/6 to 1/42,472 when calculated with European population frequencies in the 1000 Genomes Project, Phase 3. Similarly, RMPs based on African population frequencies were calculated for each SNP genetic profile and likelihood ratios (LR) were obtained by dividing each European RMP by the corresponding African RMP. In conclusion, resulting LR values ranged from 1.4 to 825 with a median value of 16. GVP markers offer a basis for the identification of compromised skeletal remains independent of the presence of DNA template.

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

Time sequence gamma-spectrometry of irradiated salt

Persisted Memory Mapping File (MMF) techniques have developed for the processing and analysis of time-stamped list (TLIST) mode data collected from an irradiated salt sample. This is a new technique that is unique to this research and enables additional information to be obtained from a conventional pulse height analysis (PHA) gamma-spectrometry acquisition. A salt sample was irradiated using a DT neutron generator and immediately measured using TLIST acquisition for 1 month to generate a 22 GB data file. MMF techniques were used to process the file without size restrictions at a rate of 388.5 MB minute-1, with instant access to any position within the file, separating the file into a series of time sequenced spectra suitable for PHA analysis. This enabled 14 activation products to be identified at different time intervals (41Ar, 80Br, 80mBr, 47Ca, 34mCl, 38Cl, 42K, 43K, 56Mn, 22Na, 24Na, 85Sr, 87mSr and 69mZn), and 6 radionuclides (80Br, 47Ca, 34mCl, 56Mn, 24Na and 87mSr) to be definitively confirmed based upon their measured half-life. Using this technique, the detection of 47Ca, and in-growth of its 47Sc progeny, was demonstrated as useful for calculating the time since irradiation.

Burnett, Jonathan L.↗
DOE OSTI2015

Environmental contaminants activate human and polar bear (Ursus maritimus) pregnane X receptors (PXR, NR1I2) differently

Background: Many persistent organic pollutants (POPs) accumulate readily in polar bears because of their position as apex predators in Arctic food webs. The pregnane X receptor (PXR, formally NR1I2, here proposed to be named promiscuous xenobiotic receptor) is a xenobiotic sensor that is directly involved in metabolizing pathways of a wide range of environmental contaminants. Objectives: In the present study, we comparably assess the ability of 51 selected pharmaceuticals, pesticides and emerging contaminants to activate PXRs from polar bears and humans using an in vitro luciferase reporter gene assay. Results: We found that polar bear PXR is activated by a wide range of our test compounds (68%) but has a slightly more narrow ligand specificity than human PXR that was activated by 86% of the 51 test compounds. The majority of the agonists identified (70%) produces a stronger induction of the reporter gene via human PXR than via polar bear PXR, however with some notable and environmentally relevant exceptions. Conclusions: Due to the observed differences in activation of polar bear and human PXRs, exposure of each species to environmental agents is likely to induce biotransformation differently in the two species. Bioinformatics analyses and structural modeling studies suggest that amino acids that are not part of the ligand-binding domain and do not interact with the ligand can modulate receptor activation. - Highlights: • Comparative study of ligand activation of human and polar bear PXRs. • Polar bear PXR is a promiscuous ligand-activated nuclear receptor but less so than human PXR. • Environmental contaminants activate human and polar bear PXRs differently. • Expression and ligand promiscuity indicate that PXR is a xenosensor in polar bears.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Meteorological Drivers and Large-Scale Climate Forcing of West Antarctic Surface Melt

Understanding the drivers of surface melting in West Antarctica is crucial for understanding future ice loss and global sea level rise. This study identifies atmospheric drivers of surface melt on West Antarctic ice shelves and ice sheet margins and relationships with tropical Pacific and high-latitude climate forcing using multidecadal reanalysis and satellite datasets. Physical drivers of ice melt are diagnosed by comparing satellite-observed melt patterns to anomalies of reanalysis near-surface air temperature, winds, and satellite-derived cloud cover, radiative fluxes, and sea ice concentration based on an Antarctic summer synoptic climatology spanning 1979–2017. Summer warming in West Antarctica is favored by Amundsen Sea (AS) blocking activity and a negative phase of the southern annular mode (SAM), which both correlate with El Niño conditions in the tropical Pacific Ocean. Extensive melt events on the Ross–Amundsen sector of the West Antarctic Ice Sheet (WAIS) are linked to persistent, intense AS blocking anticyclones, which force intrusions of marine air over the ice sheet. Surface melting is primarily driven by enhanced downwelling longwave radiation from clouds and a warm, moist atmosphere and by turbulent mixing of sensible heat to the surface by föhn winds. Since the late 1990s, concurrent with ocean-driven WAIS mass loss, summer surface melt occurrence has increased from the Amundsen Sea Embayment to the eastern Ross Ice Shelf. We link this change to increasing anticyclonic advection of marine air into West Antarctica, amplified by increasing air–sea fluxes associated with declining sea ice concentration in the coastal Ross–Amundsen Seas.

79 ASTRONOMY AND ASTROPHYSICS↗