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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Novel Toxin Biosynthetic Gene Cluster in Harmful Algal Bloom-Causing Heteroscytonema crispum : Insights into the Origins of Paralytic Shellfish Toxins

Caused by both eukaryotic dinoflagellates and prokaryotic cyanobacteria, harmful algal blooms are events of severe ecological, economic, and public health consequence, and their incidence has become more common of late. Despite coordinated research efforts to identify and characterize the genomes of harmful algal bloom-causing organisms, the genomic basis and evolutionary origins of paralytic shellfish toxins produced by harmful algal blooms remain at best incomplete. The paralytic shellfish toxin saxitoxin has an especially complex genomic architecture and enigmatic phylogenetic distribution, spanning dinoflagellates and multiple cyanobacterial genera. Using filtration and extraction techniques to target the desired cyanobacteria from nonaxenic culture, coupled with a combination of short- and long-read sequencing, we generated a reference-quality hybrid genome assembly for Heteroscytonema crispum UTEX LB 1556, a freshwater, paralytic shellfish toxin-producing cyanobacterium thought to have the largest known genome in its phylum. We report a complete, novel biosynthetic gene cluster for the paralytic shellfish toxin saxitoxin. Leveraging this biosynthetic gene cluster, we find support for the hypothesis that paralytic shellfish toxin production has appeared in divergent Cyanobacteria lineages through widespread and repeated horizontal gene transfer. This work demonstrates the utility of long-read sequencing and metagenomic assembly toward advancing our understanding of paralytic shellfish toxin biosynthetic gene cluster diversity and suggests a mechanism for the origin of paralytic shellfish toxin biosynthetic genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Aerosolized Harmful Algal Bloom Toxin Microcystin-LR Induces Type 1/Type 17 Inflammation of Murine Airways

Harmful algal blooms are increasing globally and pose serious health concerns releasing cyanotoxins. Microcystin-LR (MC-LR), one of the most frequently produced cyanotoxins, has recently been detected in aerosols generated by the normal motions of affected bodies of water. MC-LR aerosol exposure has been linked to a pro-inflammatory influence on the airways of mice; however, little is understood about the underlying mechanism or the potential consequences. This study aimed to investigate the pro-inflammatory effects of aerosolized MC-LR on murine airways. C57BL/6 and BALB/c mice were exposed to MC-LR aerosols, as these strains are predisposed to type 1/type 17 and type 2 immune responses, respectively. Exposure to MC-LR induced granulocytic inflammation in C57BL/6 but not BALB/c mice, as observed by increased expression of cytokines MIP-1α, CXCL1, CCL2, and GM-CSF compared with their respective vehicle controls. Furthermore, the upregulation of interleukins IL-17A and IL-12 is consistent with Th1- and Th17-driven type 1/type 17 inflammation. Histological analysis confirmed inflammation in the C57BL/6 lungs, with elevated neutrophils and macrophages in the bronchoalveolar lavage fluid and increased pro-inflammatory and pro-resolving oxidized lipids. In contrast, BALB/c mice showed no significant airway inflammation. These results highlight the ability of aerosolized MC-LR to trigger harmful airway inflammation, requiring further research, particularly into populations with predispositions to type 1/type 17 inflammation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐ a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States

Abstract Excess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll‐aconcentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in‐lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll‐aacross the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll‐aconcentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll‐a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐afor ∼112,000 lakes across the CONUS. Risk for high chlorophyll‐aconcentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake‐specific results can help managers identify potential nutrient pollution and chlorophyll‐ahot spots that may fuel blooms, prioritize at‐risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.

Environmental Sciences & Ecology↗
DOE OSTI2025

A family of tubular pili from harmful algal bloom forming cyanobacterium Microcystis aeruginosa

Cyanobacteria are vital photosynthetic prokaryotes, but some form harmful algal blooms (cyanoHABs) that disrupt ecosystems and produce toxins. The mechanisms by which these blooms form have yet to be fully understood, particularly the role of extracellular components. Here, we present a 2.4 Å cryo-EM structure of a pilus, termed the cyanobacterial tubular (CT) pilus, found in the cyanoHAB-forming Microcystis aeruginosa. The pilin exhibits a unique protein fold, forming a tubular pilus structure with tight, double-layer anti-parallel β-sheet interactions. We show that CT pili are essential for buoyancy by facilitating the formation of micro-colonies, which increases drag force and prevents sinking. The CT pilus surface is heavily glycosylated with ten monosaccharide modifications per pilin. Furthermore, CT pili can enrich microcystin, potentially enhancing cellular resilience, and co-localize with iron-enriched extracellular matrix components. Thus, we propose that this pilus plays an important role in the proliferation of cyanoHABs. This just discovered pilus family appears to be widely distributed across several cyanobacterial orders. Our structural and functional characterization of CT pili provide insights into cyanobacterial cell morphology, physiology, and toxin interactions, and identify potential targets for disrupting bloom formation.

Cryoelectron microscopy↗
DOE OSTI2024

'Omics and Big Data in Harmful Algal Bloom Research

Phytoplankton, a group including eukaryotic microalgae and cyanobacteria, play a crucial climate role converting CO 2 into organic carbon through global primary production. They support a wide range of life, both freshwater and marine, from zooplankton to fish and mammals. While they are essential in nutrient cycles, certain phytoplankton species can proliferate excessively under favorable conditions, leading to harmful algal blooms (HABs) that pose significant threats to human and ecosystem health through the toxins they produce.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Linking Spatiotemporal Biological Data to Predict Harmful Algal Blooms

Cyanobacterial Harmful Algal Blooms (cHABs) have significant impacts on an affected region’s economy, ecology, and human health. The blooms can release toxins that kill fish and poison water for people and animals. The global adverse effects of cHABs are exacerbated by the consequences of climate change and increased pollution. Though the phenomena are well documented, scientists’ efforts to mitigate the damage are hampered by insufficient predictive models and incomplete granular knowledge of cHAB community structure. With a goal of leveraging bioinformatics and machine learning tools to better understand and predict cHABs, we are first exploring water sample data sets. Using nearly four thousand samples from the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) across 16 years with latitude and longitude embedded in the metadata, we mapped the location of the samples onto a Lake Erie shape file. We combined information about location, date, and community taxa in the NCBI samples to discover factors that determine cHAB features. The data are separated into three distinct zones, with the majority pooled at the southwest end of the lake and occurring in 2017. The samples are rich in biological data; our next steps are to carry out whole genome sequence analysis and use the community profiles as part of our predictive machine learning model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Taming harmful bursts and heat flux in high-confinement tokamak plasmas

A major challenge in tokamak fusion research is first-wall erosion caused by steady heat loads and sudden energy bursts known as edge-localized modes. Divertor detachment reduces steady-state heat flux, while resonant magnetic perturbations can suppress these instabilities. However, integrating the two has been difficult because they require conflicting operating conditions. Here we demonstrate simultaneous achievement of resonant magnetic perturbations mitigated small edge-localized modes and impurity seeded partial divertor detachment in plasmas with an ITER-similar shape on the DIII-D tokamak. Experiments and simulations show that resonant magnetic perturbations facilitate detachment by redistributing particles, lowering the core density and increasing the scrape-off layer density, thereby reducing the amount of injected gas required. Cooling-gas injection eliminates the secondary heat-flux peak created by three-dimensional magnetic lobes, while edge cooling weakens the plasma response to the applied magnetic fields. These advances illustrate a viable pathway for integrating edge stability control with power exhaust in future fusion reactors.

magnetically confined plasmas↗
DOE OSTI2026

Searching for the Most Harmful Field Errors in the HSR IR Superconducting Magnets

In this project, we improve beam stability for the Electron-Ion Collider. Magnetic field errors can reduce beam stability, making it essential to identify the field errors that have the greatest impact on accelerator performance. However, this is particularly challenging because beam stability depends on the complex interactions of many magnetic field errors, resulting in a high-dimensional and nonlinear optimization problem. We determine which field errors are the most influential for the large physical aperture superconducting magnet B2PF, a critical magnet in the Interaction Region (IR) in the Hadron Storage Ring (HSR). We complete and analyze nearly 30,000 simulations on the Brookhaven National Laboratory Linux Cluster by varying 18 nonlinear magnetic field errors. We evaluate beam stability using the dynamic aperture and the tune diffusion. We identify the field errors that most strongly influence beam stability and establish quantitative field error tolerances that improve accelerator performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Diversifying the Materials and Technologies for the Future of Energy Storage

It is increasingly important to meet the growing global energy demand driven by factors such as population growth, electrification, and the rapid development of emerging economies, while minimizing the environmental harm caused by carbon dioxide emissions. Although fossil fuels remain an abundant and inexpensive energy source, there is a global consensus on the critical importance of addressing climate change and an increasing urgency to reduce carbon dioxide emissions without hindering economic growth. This challenge is particularly daunting due to the significant transformations required in electricity generation systems, transportation, and industrial processes. A significant portion of our energy still comes from burning fossil fuels, which poses harmful effects on the environment. Transitioning to renewable energy sources like solar and wind is essential, as these sources provide a low-carbon pathway for power generation and have become increasingly cost-competitive with fossil fuels. However, they face the inherent challenge of intermittency. Thus, energy storage systems (ESS) are essential not only to address this issue but also to accommodate the increasing adoption of electric vehicles (EVs). Lithium-ion batteries (LIBs) are still the predominant ESS used for these applications; however, they suffer from issues related to scarce and harmful resources, safety, and socio-economic impacts. This underscores the need for alternative energy storage systems beyond LIBs. Here, in this review, we discuss the diversification, repurposing, and recycling of ESS to meet the projected energy demand while minimizing environmental harm.

batteries↗
DOE OSTI2025

Organophosphorus Binding Thermodynamics in Metal–Organic Frameworks: Interplay between Oxidation State, Lewis Acidity, and Node Structure

Organophosphorus compounds, including nerve agents and pesticides, represent a class of toxic chemicals causing harm to troops, civilians, and the environment. Metal–organic frameworks (MOFs) have emerged as a class of highly porous, crystalline, tunable materials adept at both capturing and catalytically neutralizing these harmful toxins. In particular, MOFs whose nodes display strong Lewis acidic character can hydrolyze such chemicals nearly instantaneously. However, without the help of a basic buffer to regenerate the active site, the benign organophosphorus product strongly binds to the node and prevents catalyst turnover. Here, we investigate a series of MOFs whose nodes contain metals of varying Lewis acidities and employ isothermal titration calorimetry (ITC) to directly measure the heat from the binding of an organophosphorus probe molecule, allowing the construction of a full thermodynamic binding profile (ΔH, ΔS, ΔG, K a ). We couple this with potentiometric titrations and solid state 31 P magic angle spinning (MAS) NMR to gain a clearer picture of how node identity, structure, and Lewis acidity interplay to impact binding strength and favorability. Furthermore, this study is the first to integrate these three complementary techniques to investigate binding interactions in MOFs, further showcasing the viability of ITC for probing MOF systems, which is still relatively underexplored.

Lewis acidity↗
DOE OSTI2025

Introducing bioderived solvents for safer and more sustainable 19 F benchtop NMR analysis of pyrolysis oils

The development of increasingly sustainable analytical chemistry techniques is a growing area of research. Detailed knowledge of bio-oil composition is crucial for the wider use of this alternative, sustainable fuel product, whether by guiding and optimising the pyrolysis processes or for indicating appropriate upgrading methods. The oxygen-containing species in the oil are most important to analyse as they are key to the long-term stability and further processing of the oil. A common analytical method is derivatisation, inserting 19 F nuclei only into specific compounds in the sample, so that a sparser NMR spectrum of a subset of the compounds present can be acquired with even a benchtop NMR spectrometer. However, the derivatisation reactions themselves are not benign, with the most commonly used method relying on DMF throughout. While DMF is highly effective in facilitating the derivatisation reaction, it is not only harmful but increasingly restricted in use. By substituting DMF with ethyl lactate, the reaction is rendered safer and more sustainable. The change in solvent does not affect the NMR results, with estimates of total carbonyl content comparable with those produced by titration. The spectra acquired are detailed enough to also allow the quantification of the different carbonyl functional groups present. By switching to ethyl lactate, it is possible to increase the amount of water in the solvent mixture, further reducing the environmental impact, user risks and cost of the analytical method. By replacing harmful solvents with greener alternatives, benchtop NMR analyses of pyrolysis oils are increasingly safer to run, increasingly cheaper to run, and increasingly more accessible to a wide range of different users.

Tang, Bridget [Aston University, Birmingham (Unite↗
DOE OSTI2024

Enhancing Network Anomaly Detection Using Graph Neural Networks

In the world of Internet of Things (IoT) networks, where devices are constantly communicating, keeping them secure from cyber threats is critical. This paper introduces a novel approach to detecting unusual and potentially harmful activities in these networks using graph neural networks (GNNs). We combine two specific types of GNNs-GraphSAGE and graph attention networks (GAT)-to create a model that understands and represents the behaviors and interactions in a network. GraphSAGE creates an embedding of network activities by examining local data interactions, while GAT directs the model's focus to the most critical interactions. By integrating these two methods in a single model that considers different types of interactions (both host and flow nodes), we aim to create a system that accurately represents the current state of a network and can also spot anomalies effectively while reducing false positives and negatives. Our innovative approach has demonstrated promising results, achieving an accuracy of 98% on the UNSW-NB15 dataset, significantly outperforming standalone GraphSAGE and GAT models. This underscores its potential as a robust framework for securing IoT networks against cyber threats and anomalies.

Marfo, William↗
DOE OSTI2026

Dataset of U.S. School Bus Depots

A large body of public health literature describes how undesirable or dangerous facilities, such as truck depots and industrial plants, located in or near communities can lead to health harms. Research also describes the high levels of traffic-related air and noise pollution that is linked to health harms and may be disproportionately distributed near many schools. Therefore, a primary use case for this dataset is to analyze the location of school bus depots and to create an evidence base that would better enable the work of community members, advocates, and other stakeholders toward improving air quality and public health. Other possible uses for this school bus depot dataset include electricity grid planning and reliability, given recent momentum toward school bus electrification. This dataset was created using an object-based approach with remote sensing data. The primary source of aerial imagery was the National Agriculture Imagery Program (NAIP) dataset. NAIP imagery was analyzed to locate individual school buses based on their color and size, and then classified clusters of school buses as potential depots, which were then verified visually. The resulting dataset contains 11,309 depots across the 48 contiguous U.S. states and Washington, D.C. Fifty-one percent (5,730 depots) are at schools, defined as being 350 meters or less from the nearest school. The accuracy of the dataset was assessed by comparing it with independent reference datasets containing 506 depots from the records of two school transportation companies. We found good agreement, with an omission error rate of 15.2% (77 depots). This dataset represents one of the only remote sensing projects to conduct object detection using data at the sub-meter to 1-meter resolution for a continental-scale application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Connecting Nitrogen Transformations Mediated by the Rhizosphere Microbiome to Perennial Cropping System Productivity in Marginal Lands

The demand for energy from biofuel production is increasing, prompting concerns about the environmental impact and long-term sustainability of bioenergy cropping systems. These cropping systems will make up much of our future landscapes, and threaten to take the place of food cropping systems. Many life cycle analyses of bioenergy sustainability focus on carbon accrual and budgets, since they want to maximize carbon accrual while producing alternative fuel. Less attention has been given to nitrogen (N) dynamics in these systems. N is the most commonly limiting nutrient for plants, but applying nitrogen fertilizer- as we do for most cropping systems – is harmful to the environment, energetically costly, and produces greenhouse gases. In other words, adding nitrogen by fertilizer bioenergy systems could add to the very problems (climate change) it is trying to address. This is especially true for the areas that are proposed for bioenergy systems: marginal lands. These more degraded lands do not complete with food crops, but do have limited nitrogen. If we are to use these marginal lands for bioenergy, we need to understand the mechanisms regulating nutrient acquisition, and identify ways that bioenergy crops can get nitrogen in sustainable ways. Nutrient acquisition in the soil is performed by microbes in the root zone, or rhizosphere. Microbes can either mineralize nitrogen in the soil (from organic forms) or fix nitrogen from the air, in a process called nitrogen fixation. The goal of our project was thus to understand how the rhizosphere microbiome provides nutrients to bioenergy crops on marginal lands. We focus especially on the process of nitrogen fixation, since it has potential to get “fertilizer for free” that has much less environmental harm. We investigated this goal using sites from the DOE Great Lakes Bioenergy Research Center (GLBRC) in the upper Midwest, and associated lab and ‘omics methods. We group our findings into three major areas. First, we showed that nitrogen fixation, the conversion of N2 gas from the air to ammonium that is usable by plants, is performed in bioenergy soils, and benefits switchgrass crops. While more well-studied in leguminous plants, free-living nitrogen fixation can occur in some systems, and represents a potential opportunity to gain ‘free’ sustainable nitrogen source. We identified the nitrogen fixing bacteria that were most active in providing switchgrass with N, and showed that the drivers of nitrogen fixation occurred at a microscale; it is not well-predicted by bulk variables like soil moisture or plant phenology. Second, we showed that nitrogen fixation is not suppressed by long-term fertilizer. We expected that plentiful nitrogen would reduce the symbiotic relationship between nitrogen fixers and plants, and ‘downregulate’ fixation. We did not find evidence for this, either after long-term fertilizer in the field, or short-term fertilizer in the greenhouse. Finally, we identified the root exudates, carbon compounds that are emitted from the root, that best stimulate nitrogen fixation. We found that carbohydrates were better at stimulating fixation than organic acids. We expected these exudates to be emitted from the plant in periods of high N demand, but we found they are emitted when N is plentiful. This suggests that the stimulation of N fixation by plants is a passive process. Overall, we show that nitrogen fixation has potential to support bioenergy cropping system, and future management could develop ways to maximize it. However, this may not be best achieved via the plant – we found very little evidence of a ‘transactional’ system by which plants are controlling when and where nitrogen fixation is stimulated. It will be better to understand how management practices like planting and fertilizer application affect the microscale soil dynamics, which will determine nitrogen fixation rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Assessing Historical Extreme Weather Event Impacts

Resilience planning, particularly energy and water resilience planning, has been a key priority for the federal government for many years, leading federal agencies to develop processes for identifying and addressing critical resilience gaps at their facilities and sites. Furthermore, recent federal policy is driving agencies to prioritize climate change impacts as a more central component of their resilience planning efforts. To achieve this, federal sites must understand their vulnerability to climate change, which involves identifying climate hazards projected to impact the site (known as exposure), as well as understanding the sensitivity (the degree to which a site, including its people and the things they value, could be harmed by that exposure), and adaptive capacity of the site (the degree to which the site could lessen bathe potential for harm by taking action to reduce exposure and sensitivity). To assess and understand sensitivity and adaptive capacity, it is important to first obtain a baseline and understand how a site has been impacted by past events, in addition to considering the potential for unprecedented impacts based on climate projections. This information paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points. The purpose of this paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Success Path Method: Conformance with Safety Management Systems

All industrial facilities deal with safety hazards such as equipment failures, chemical and toxic releases, and fires and explosions just to name a few. A disciplined framework for managing the integrity of operating systems and processes that handle hazardous substances by applying good design principles, engineering, and operating practices is called process safety. The goal of such framewoks is to prevent the release of energy or material that could cause harm to people or damage to equipment and/or environment. Process safety covers all aspects of facility operation also including design, maintenance, and human and organizational factors that could possibly have effect on process safety. As it will be seen from the discussion below, process safety is just one of the pieces of the much bigger matter, a safety culture. Many industries have long recognized the importance of safety culture in their day-to-day operation. Although the definition of safety culture can slightly differ from organization to organization, in general, a safety culture is how things are done to demonstrate a commitment to safety by everyone involved. An organization acquires safety culture over time as the product of individual and group values, actions, and behaviors toward overall safety. It is important to note that safety culture should not be viewed as some static state that an organization wants to reach. It is more like a constantly evolving level of “how things are done when nobody is watching.” Safety culture is an inherent characteristic of an organization, it is always present, but the level can range on a continuum from undesirable to desirable or more commonly used, from negative to positive. An example for an undesirable, negative safety culture would be a company in which accidents resulting in harm (physical and/or emotional) of its employees, equipment or surrounding environment and community occur frequently. At the other end of the spectrum would be a company in which such accidents are rare or do not occur at all (desired or positive safety culture). Every company/industry exists somewhere within this spectrum.

42 ENGINEERING↗
DOE OSTI2025

ARCADE Analysis Methods & Validation Pathway

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) provides an automated analysis system which supports risk-informed performance based (RIPB) evaluations of nuclear control systems. Every possible cyber threat which could lead to consequence is identified by simulating the unsafe control action sequences which transform digital harm into physical harm. Eliminating the simulation of complex digital cyber attack chains cuts out unnecessary computational overhead and focuses directly on the physics of cyber-physical attacks. This focus enables designers to make informed decisions which can entirely eliminate categories of cyber threats against advanced reactors through the physical nature of the plant design. This narrowing of cyber threat against nuclear power plants through the physics of the system is intended to make any remaining threat management and cost efficient. This is the goal of the Tiered Cyber Analysis (TCA) outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors. ARCADE has been custom developed to meet the demands of the rigorous analysis required in Tier 1 of the TCA, which forms the foundation of the TCA process. Currently, ARCADE is still under development, but has made significant leaps in capability. A pilot analysis on the opensource Asherah simulator was performed which demonstrated key functionality goals. The next stage of ARCADE development involves improvements to the applications which support the analysis system, and enabling the analysis system to utilize the full suite of unsafe control action simulations. Since the analysis method’s core functions are complete, validation of the analysis method will be started concurrent to the next development stages. The automated analysis ARCADE will provide can radically change the cybersecurity design process for advanced reactors, reducing the cost of security implementation while enhancing cyber resilience. The pathway for ARCADE’s development to this goal has become much clearer. The majority of technical hurdles have been cleared, and the remaining development needs have been solidified. ARCADE is now capable of assisting the advanced reactor design process and directly support advanced reactor industry RIPB practices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗