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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 OSTI2022

Monitoring SARS-CoV-2 in wastewater

The detection of SARS-CoV-2 cases throughout the pandemic has been based on individual testing, which is subject to inaccuracies in what is actually occurring within the local population. Wastewater biosurveillance has been used around the world to detect the presence of drugs, viruses, and other chemicals present in a population. Fecal shedding of SARS-CoV-2 implies that wastewater can be analyzed in order to detect varying levels of the virus within a given community. This analysis can show the fluctuation of SARS-CoV-2 at a population level over time. In this experiment, the amount of SARS-CoV-2 in the wastewater sample was compared to the amount of Pepper Mild Mottle Virus (PMMoV) detected in the same sample. PMMoV is present consistently in human fecal matter, and can be used to normalize the amount of SARS-CoV-2 detected in wastewater.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Microbial and Geochemical Dynamics of an Aquifer Stimulated for Microbial Induced Calcite Precipitation (MICP)

Microbially induced calcite precipitation (MICP) is an alternative to existing soil stabilization techniques for construction and erosion. As with any biologically induced process in soils or aquifers, it is important to track changes in the microbial communities that occur as a result of the treatment. Our research assessed how native microbial communities developed in response to injections of reactants (dilute molasses as a carbon source; urea as a source of nitrogen and alkalinity) that promoted MICP in a shallow aquifer. Microbial community composition (16S rRNA gene) and ureolytic potential (ureC gene copy numbers) were also measured in groundwater and artificial sediment. Aquifer geochemistry showed evidence of sulfate reduction, nitrification, denitrification, ureolysis, and iron reduction during the treatment. The observed changes in geochemistry corresponded to microbial community succession in the groundwater and this matched parallel geophysical and mineralogical evidence of calcite precipitation in the aquifer. We detected an increase in the number of ureC genes in the microbial communities at the end of the injection period, suggesting an increase in the abundance of microbes possessing this gene as needed to hydrolyze urea and stimulate MICP. We identify geochemical and biological markers that highlight the microbial community response that can be used along with geophysical and geotechnical evidence to assess progress of MICP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Vortical interactions in turbulent thermoacoustic systems

This study examines the dynamics of vortical interactions and their implications for mitigating thermoacoustic instability in a turbulent combustor. The regions of intense vortical interactions are identified as vortical communities in the network space of weighted directed vortical networks constructed from two-dimensional experimental velocity data. One can expect vortical interactions in the combustor to be strongest near the moment of vortex shedding, as the shed vortices gradually weaken due to dissipation while convecting downstream. However, we show that, during the state of thermoacoustic instability, there is a non-trivial consistent phase lag of approximately 52° between the shedding of the coherent structures from the backward-facing step and the time instant when the vortical interactions attain their local maximum value. We explain this phase lag by investigating the correlation between acoustic pressure fluctuations, spatio-temporal dynamics of coherent structures and vortical interactions in the reaction field of the combustor. We also show the aperiodic variation of vortical interactions during the states of combustion noise and aperiodic epochs of intermittency. Furthermore, the spatio-temporal evolution of pairs of vortical communities with the maximum inter-community interactions provides insight into explaining the critical regions detected in the reaction field during the states of intermittency and thermoacoustic instability, also identified in previous studies. As a result, we further show that the most efficient suppression of thermoacoustic instability via air microjet injection is achieved when steady air jets are introduced to disrupt the maximum inter-community interactions present during the state of thermoacoustic instability.

Sahay, Ankit [Indian Institute of Technology Madra↗
DOE OSTI2024

Deep learning models map rapid plant species changes from citizen science and remote sensing data

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model— Deepbiosphere— not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Gillespie, Lauren E.↗
DOE OSTI2020

Multilateral Testing Workshop on Relocatable Portal Monitors

The procurement and deployment of radiation detection equipment is a multi-faceted challenge across the globe. Knowledge sharing of the testing methods used to evaluate equipment for deployment scenarios helps improve the understanding of deployed systems by the global community. The United States Department of Energy’s Nuclear Smuggling Detection and Deterrence Office (NSDD) performed a series of characterization measurements in 2019, focused on radiation detection systems that could function as relocatable portal monitors. The capstone activity for this project was a multilateral and cross-disciplinary workshop demonstrating, performing, and refining the techniques used in the characterization measurements with International Atomic Energy Agency (IAEA) and global partners. A group of technical experts including representatives from nine countries, the IAEA, and NSDD gathered at Sandia National Laboratories in Albuquerque, NM during September of 2019 for the Operational and Performance Testing and Evaluation of Relocatable Portals Workshop. Over the course of a week, the group discussed the necessity for and process of developing operational and performance requirements, challenges related to deploying radiation detection systems for the countries in attendance, use cases for deploying relocatable radiation detection equipment, and considerations related to testing equipment for appropriate deployment scenarios. All participants were given the opportunity to have hands-on experience with eleven relocatable systems in executing a limited scope characterization test comprised of six test scenarios. At the conclusion of testing, participants reviewed and presented their findings, and the group as a whole compared and contrasted their experiences. Suggested revisions to the test methods and ideas for further collaborations were discussed. This report discusses the logistical and planning considerations for bringing together experts across disciplines in a multilateral workshop on testing of radiation detectors, as well as presenting the testing methods performed, results, and paths forward. Success of workshops related to technical knowledge transfer and improvement of test methods is key to global technical and scientific support of radiation detection deployments.

Erchinger, Jennifer L.↗
DOE OSTI2026

Vera C. Rubin Observatory Prompt Products: alert packets data

Data products produced by prompt and daily processing of images obtained in the Legacy Survey of Space and Time. These include realtime alerts sent to community alert brokers, newly-discovered Solar System Objects reported to the Minor Planet Center, processed visit and difference images, and source catalogs. Prompt Products are not a static single data release but continually grow throughout the ten-year LSST survey. This dataset is a subset of the full data release consisting of a dataset named alert packets. This dataset contains measurements for 5-sigma sources detected in difference images that were issued to the community brokers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Benzenesulfonamide Derivatives as Complexants and Extractants for Addressing the Mercury Problem at the Savannah River Site

Mercury (Hg) is a major global pollutant arising from both natural and anthropogenic sources. Its widespread use in medicinal and industrial applications makes it a common chemical exposure and environmental pollutant. It can exist in several forms which include: Metallic mercury (Hg{sup 0}), mercurous (Hg{sub 2}{sup 2+}), mercuric salts (Hg{sup 2+}), and organic mercury (e.g. CH{sub 3}Hg{sup +}), with the latter being the most toxic of all the species. Due to mercury's high toxicity, new approaches towards its detection has received significant attention in the scientific community. Mercury exposure at the Savannah River Site (SRS) has been a recent concern especially with increasing amounts of organic mercury in the saltstone. It originates mainly from its use as an acidic dissolution catalyst of aluminum cladding from target fuels within the uranium and plutonium processing operations [1]. It is present to an amount of about 60 metric tons in the high-level waste (HLW) tanks. Organic Mercury species have been found in low activity waste (LAW) at the site that eventually ends up in the saltstone. Therefore, there is a need for: i) Converting organic mercury to other less toxic forms and ii) Complexation and removal of Hg prior of disposal of LAW in saltstone. Various methods have been developed for selective sensing of mercury in the presence of other toxic metals. These methods include using ligands that can form organo-soluble metal complexes with different optical and spectroscopic properties that can be used for toxic metal sensing. In 2005, our group pioneered an ion-exchange extraction method, in which o-phenylenediamine-derived disulfonamides were used to complex and selectively extract and sense Pb{sup 2+} from aqueous solutions into an organic phase [2,3]. Herein, a disulfonamide and a bis-dansylamide have been shown to extract, complex and sense Hg(II). Ligand 1: The crystal structure of the disulfonamide-Hg complex confirms the complexation of Hg(II) with the ligand. Complexation was corroborated by the {sup 1}H-NMR spectra obtained after contacting solutions of various concentrations of Hg{sup 2+} with 2 mM ligand in chloroform. Distinct resonances are observed at Hg/L ratio of 0.5 that are also observed for the isolated 1:2 complex. In the presence of excess mercury, new resonances, as well as the movement of Et{sub 3}N resonances indicate the formation of a different Hg-sulfonamide-triethylamine complex, presumably having 1:1 Hg:L stoichiometry. The electronic spectra of aqueous phases after extraction show that there was no free ligand absorption at 0.5 eq of Hg, indicating a complete complexation. Complexation was also confirmed by the UV-visible titrations with Hg{sup 2+} at constant ligand concentration. pH-dependent extraction carried out shows that extraction of Hg(II) by ligand 1 was over 90% for most alkaline pHs. Ligand 2: The crystal structure of the Ligand 2 complex formed with Hg(OAc){sub 2} shows a remarkable coordination pattern with 4:2 metal:ligand stoichiometry. The fluorescent bis-dansyl disulfonamide derivative was found to complex and sense HgCl{sub 2} and Hg(OAc){sub 2} by demonstrating fluorescence quenching upon Hg(II) addition in comparison with other metals (Zn(II), Cd(II), Pb(II)). No were observed for Cu(II), Ag(I) and Co(II). We have shown the complexation of Hg(II) by a disulfonamide and a bis-dansyl disulfonamide ligand using several spectroscopic methods. Ligand 1 was able to extract mercury into chloroform and form a complex in the presence of excess mercury by synergistic complexation with triethylamine acting as a co-ligand. X-ray and NMR both confirm a 1:2 HgL{sub 2} stoichiometry. Ligand 2 can be used for sensing of Hg(II) as fluorescence quenching was observed after addition of Hg(II)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Amylases in the Human Vagina

ABSTRACT Dominance of Lactobacillus species in vaginal communities is a hallmark of healthy conditions in the female genital tract. Key nutrients for lactobacilli include sugars produced when glycogen is degraded by α-amylase in the vagina. While α-amylase activity has been demonstrated in vaginal fluids, it is unclear whether α-amylases are produced solely by the host, bacteria in the vagina, or both. We screened cervicovaginal mucus from 23 reproductive-age women, characterized the species composition of vaginal communities, measured vaginal pH, and determined levels of amylase activity, glycogen, and lactic acid. Based on differences in these measured variables, one sample from each of four individual donors was selected for metagenomic and proteomic analyses. Of eight putative bacterial amylases identified in the assembled bacterial metagenomes, we detected four in vaginal fluids. These amylases were produced by various bacteria in different vaginal communities. Moreover, no two communities were the same in terms of which bacteria were producing amylases. Although we detected bacterial amylases in vaginal fluids, there was no clear association between the bacterial species that was dominant in a community and the level of amylase activity. This association was likely masked by the presence of human α-amylase, which was also detected in vaginal fluids. Finally, the levels of amylase activity and glycogen were only weakly associated. Our findings show, for the first time, that multiple amylases from both bacterial and human origins can be present simultaneously in the vagina. This work also suggests that the link between glycogen, amylase, and Lactobacillus in the vagina is complex. IMPORTANCE In this study, we show that multiple bacteria in the vaginal community produce amylases that hydrolyze glycogen into simpler sugars (i.e., maltose and maltotriose). These sugars serve as “common goods” that sustain bacterial populations in vaginal communities. Given the temporal changes that are observed in the human vaginal microbiome, we expect the kinds of bacterial amylases produced will also vary over time. These differences influence the pool of resources that are broadly shared and shape the species composition of the vaginal bacterial community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Transcriptional Response of Soil Bacteria to Long-Term Warming and Short-Term Seasonal Fluctuations in a Terrestrial Forest

Terrestrial ecosystems are an important carbon store, and this carbon is vulnerable to microbial degradation with climate warming. After 30 years of experimental warming, carbon stocks in a temperate mixed deciduous forest were observed to be reduced by 30% in the heated plots relative to the controls. In addition, soil respiration was seasonal, as was the warming treatment effect. We therefore hypothesized that long-term warming will have higher expressions of genes related to carbohydrate and lipid metabolism due to increased utilization of recalcitrant carbon pools compared to controls. Because of the seasonal effect of soil respiration and the warming treatment, we further hypothesized that these patterns will be seasonal. We used RNA sequencing to show how the microbial community responds to long-term warming (~30 years) in Harvard Forest, MA. Total RNA was extracted from mineral and organic soil types from two treatment plots (+5°C heated and ambient control), at two time points (June and October) and sequenced using Illumina NextSeq technology. Treatment had a larger effect size on KEGG annotated transcripts than on CAZymes, while soil types more strongly affected CAZymes than KEGG annotated transcripts, though effect sizes overall were small. Although, warming showed a small effect on overall CAZymes expression, several carbohydrate-associated enzymes showed increased expression in heated soils (~68% of all differentially expressed transcripts). Further, exploratory analysis using an unconstrained method showed increased abundances of enzymes related to polysaccharide and lipid metabolism and decomposition in heated soils. Compared to long-term warming, we detected a relatively small effect of seasonal variation on community gene expression. Together, these results indicate that the higher carbohydrate degrading potential of bacteria in heated plots can possibly accelerate a self-reinforcing carbon cycle-temperature feedback in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Wastewater Surveillance for Poliovirus in Selected Jurisdictions, United States, 2022–2023

Wastewater testing can inform public health action as a component of polio outbreak response. During 2022-2023, a total of 7 US jurisdictions (5 states and 2 cities) participated in prospective or retrospective testing of wastewater for poliovirus after a paralytic polio case was identified in New York state. Two distinct vaccine-derived poliovirus type 2 viruses were detected in wastewater from New York state and New York City during 2022, representing 2 separate importation events. Of those viruses, 1 resulted in persistent community transmission in multiple New York counties and 1 paralytic case. No poliovirus was detected in the other participating jurisdictions (Connecticut, New Jersey, Michigan, and Illinois and Chicago, IL). The value of routine wastewater surveillance for poliovirus apart from an outbreak is unclear. However, these results highlight the ongoing risk for poliovirus importations into the United States and the need to identify undervaccinated communities and increase vaccination coverage to prevent paralytic polio.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Genetic underpinnings of arthropod community distributions in Populus trichocarpa

Community genetics seeks to understand the mechanisms by which natural genetic variation in heritable host phenotypes can encompass assemblages of organisms such as bacteria, fungi, and many animals including arthropods. Prior studies that focused on plant genotypes have been unable to identify genes controlling community composition, a necessary step to predict ecosystem structure and function as underlying genes shift within plant populations. Here, we surveyed arthropods within an association population of Populus trichocarpa in three common gardens to discover plant genes that contributed to arthropod community composition. We analyzed our surveys with traditional single-trait genome-wide association analysis (GWAS), multitrait GWAS, and functional networks built from a diverse set of plant phenotypes. Plant genotype was influential in structuring arthropod community composition among several garden sites. Candidate genes important for higher level organization of arthropod communities had broadly applicable functions, such as terpenoid biosynthesis and production of dsRNA binding proteins and protein kinases, which may be capable of targeting multiple arthropod species. We have demonstrated the ability to detect, in an uncontrolled environment, individual genes that are associated with the community assemblage of arthropods on a host plant, further enhancing our understanding of genetic mechanisms that impact ecosystem structure.

Community genetics↗
DOE OSTI2024

On the detectability of the moving lens signal in CMB experiments

Abstract Upcoming cosmic microwave background (CMB) experiments are expected to detect new signals probing interaction of CMB photons with intervening large-scale structure. Among these the moving-lens effect, the CMB temperature anisotropy induced by cosmological structures moving transverse to our line of sight, is anticipated to be measured to high significance in the near future. In this paper, we investigate two possible strategies for the detection of this signal: pairwise transverse-velocity estimation and oriented stacking. We expand on previous studies by including in the analysis realistic simulations of competing signals and foregrounds. We confirm that the moving lens effect can be detected at ≥ 10σlevel by a combination of CMB-S4 and LSST surveys. We show that the limiting factors in the detection depend on the strategy: for the stacking analysis, correlated extragalactic foregrounds, namely the cosmic infrared background and thermal Sunyaev Zel'dovich effect, play the most important role. The addition of foregrounds make the signal-to-noise ratio be most influenced by large and nearby objects. As for the pairwise detection, halo lensing and pair number counts are the main issues. In light of our findings, we elaborate on possible strategies to improve the analysis approach for the moving lens detection with upcoming experiments. We also deliver to the community all the simulations and tools we developed for this study.

Astronomy & Astrophysics↗
DOE OSTI2022

Phosphate Availability Modulates Root Exudate Composition and Rhizosphere Microbial Community in a Teosinte and a Modern Maize Cultivar

Domestication and breeding have affected interactions between plants and their microbiomes in ways that are only beginning to be understood but may have important implications for recruitment of rhizosphere microorganisms, particularly under stress conditions. We investigated the responses of a modern maize (Zea mays subsp. mays) cultivar and its wild relative, teosinte (Z. mays subsp. parviglumis), to different phosphate availabilities. We appraised responses of the plant-microbial holobiont to phosphate stresses by profiling root exudate metabolomes, and microbial communities in the root endosphere and rhizosphere. We also performed plate assays to quantify phosphate-solubilizing microorganisms from the rhizosphere. Although root exudate metabolite profiles were distinct between the teosinte and modern maize under high phosphate, both plants shifted exudate compositions in response to phosphate stress toward a common metabolite profile. Root and rhizosphere microbial communities also responded significantly to both plant type and the phosphate availability. A subset of bacterial and fungal taxa were differentially abundant under the different phosphate conditions, with each of the three conditions favoring different taxa. Both teosinte and maize rhizospheres harbored phosphate-solubilizing microorganisms under all growth conditions. These results suggest that the root exudation response to phosphate stress was conserved through the domestication of maize from teosinte, shifting exudation levels of specific metabolites. Although microbial communities also shifted, plate-based assays did not detect selective recruitment of phosphate solubilizers in response to phosphate availability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Utilizing HYSPLIT for Emergency Response Modeling at SRS

The threat of a disaster happening at the Savannah River Site (SRS) is low, but not zero. When an emergency arises, emergency responders utilize a variety of tools to detect, track, and mitigate the disaster. HYSPLIT is a community atmospheric dispersion model that is highly configurable and has been used operationally to simulate particle, chemical, and radionuclide releases. We have developed a preliminary user interface (UI) that configures HYSPLIT to run for a variety of Emergency Action Level (EAL) scenarios at SRS. Using a hypothetical EAL scenario of an accidental release of Pu-238 in H-area and K-area onsite, an analysis was done to show how a preliminary UI framework allows HYSPLIT to be run on a terminal without the need form an active network connection. The study was successful in multiple aspects. For the preliminary UI, users were able to input certain characteristics of the hypothetical EAL such as hours of emission (how long was Pu-238 being released), curies of release, release start time (when does the model run start), and type of radionuclide directly into the terminal. For HYSPLIT, the model was successful in being able to take the UI input, calculate the results from the inputs and output multiple figures of both total volumetric airborne concentrations and surface deposition. We used the Pu-238 Derived Intervention Level (DIL) deposition thresholds for produce, dairy, and beef for visualization of the surface deposition, showing how a release would impact ingestion pathways.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Deep Learning Scene Classification Experiments in Automatic Detection of Slums on Planetscope Imagery

Population growth is increasingly happening in slum settlements of the large urban centers in the Global South. The term "slum" encompasses a wide range of communities, located mostly in underserved areas, and often exhibiting distinct structural and functional informalities with a relatively high concentration of marginalized populations. To address the issues confronting slums for effective planning and development, including the realistic estimation of the resident population, identifying them accurately is fundamental. Given the disagreements over a universal definition, diverse characteristic features, and socio-political limitations, global detection of slums is a veritable challenge. In this paper, we present experiments in slum detection using a scene classification algorithm and 3-meter spatial resolution satellite imagery. We train and evaluate the model for slum detection in Mumbai, India for the year 2023 and test the temporal generalization of the trained model on Mumbai in 2020 and 2018. In addition, we explore the pathways toward geographic generalization to Kolkata and Delhi (India). We discuss several limitations in the workflow and model, situate our findings in the existing literature, and suggest improvements and alternatives. With this, we establish baseline methods and experiments as a first step towards developing an image-based global slum detection framework and algorithm. This work adds to the community discussion on methods, data challenges, and open questions related to the detection of slums globally. With this research, we hope to improve our understanding of human settlements, especially in critical areas, improve population estimates, and help measure progress towards the sustainable development goals.

Arndt, Jacob↗
DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗
DOE OSTI2022

Climate warming causes photobiont degradation and carbon starvation in a boreal climate sentinel lichen

The long-term potential for acclimation by lichens to changing climates is poorly known, despite their prominent roles in forested ecosystems. Although often considered “extremophiles,” lichens may not readily acclimate to novel climates well beyond historical norms. In a previous study, Evernia mesomorpha transplants in a whole-ecosystem climate change experiment showed drastic mass loss after 1 yr of warming and drying; however, the causes of this mass loss were not addressed. We examined the causes of this warming-induced mass loss by measuring physiological, functional, and reproductive attributes of lichen transplants. Severe loss of mass and physiological function occurred above +2°C of experimental warming. Loss of algal symbionts (“bleaching”) and turnover in algal community compositions increased with temperature and were the clearest impacts of experimental warming. Enhanced CO 2 had no significant physiological or symbiont composition effects. The functional loss of algal photobionts led to significant loss of mass and specific thallus mass (STM), which in turn reduced water-holding capacity (WHC). Although algal genotypes remained detectable in thalli exposed to higher stress, within-thallus photobiont communities shifted in composition toward greater diversity. The strong negative impacts of warming and/or lower humidity on Evernia mesomorpha were driven by a loss of photobiont activity. Analogous to the effects of climate change on corals, the balance of symbiont carbon metabolism in lichens is central to their resilience to changing conditions.

54 ENVIRONMENTAL SCIENCES↗