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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nanolipoprotein particle (NLP) vaccine confers protection against Yersinia pestis aerosol challenge in a BALB/c mouse model

Introduction: Yersinia pestis is the etiological agent of plague, a disease that remains a concern as demonstrated by recent outbreaks in Madagascar. Infection with Y. pestis results in a rapidly progressing illness that can only be successfully treated with antibiotics given shortly after symptom onset. Live attenuated or whole cell inactivated vaccines confer protection against bubonic plague, but pneumonic plague has been more difficult to prevent. Novel effective subunit vaccine formulations may circumvent some of these shortfalls. Here, we compare the immunogenicity generated by an advanced subunit vaccine (F1V fusion protein) and a nanolipoprotein particle (NLP)-based vaccine. Methods: The NLP, a high-density lipoprotein mimetic, provides a nanoscale delivery platform for recombinant Y. pestis antigens LcrV (V) and F1. BALB/c mice were immunized via subcutaneous injection twice, three or four weeks apart. Four weeks later, splenocytes and sera were collected for immune profiling, and mice were challenged with aerosolized Y. pestis CO92. Results: Both formulations induced a strong IgG response against the F1 and V proteins, along with a robust memory B cell response and a balanced cell-mediated immune response as evidenced by both Th1- and Th2-related cytokines. The NLP-based vaccine induced a stronger cytokine response against F1, V, and F1V proteins relative to the F1V vaccine. As with F1V, the inclusion of Alhydrogel (Alu) in NLP vaccine formulations was critical for enhanced immunogenicity and protective efficacy. Mice that received two doses of F1:V:NLP + Alu and CpG were completely protected from a challenge with approximately eight median lethal doses of aerosolized Y. pestis CO92 and this protection confirmed the well-documented synergy between the F1 and V antigens in context of pneumonic plague. The NLPs have defined regions of polarity that facilitates the incorporation of a wide range of adjuvants and antigens with distinct physicochemical properties and are an excellent candidate platform for the development of multi-antigen vaccines.

F1↗
DOE OSTI2019

Adsorption of Nickel Ion in Aqueous Using Rubber-Based Hydrogel

This work reports about a rubber-based hydrogel from liquid natural rubber (LNR) and acrylic acid (AAc) by using potassium persulfate (KPS) as an initiator and N,N-methylenebisacrylamide (MBA) as a crosslinking agent. The structure, stability, and morphology of the hydrogel were confirmed by using Fourier transform infrared spectroscopy, thermogravimetric analysis, and scanning electron microscope. The optimisation of the swelling capacity and Ni{sup 2+} removal percentage by the rubber-based hydrogel was conducted by using 5-level-2-factor response surface methodology. The effect of AAc:LNR ratio (0.59–3.41 g/g) and MBA concentration (0.02–0.23 M) parameters was studied with constant KPS concentration (0.05 M) used. Quadratic models for both responses (swelling and Ni{sup 2+} removal percentage) were successfully developed by using statistical analysis. The swelling degree and Ni{sup 2+} removal percentage of hydrogel were improved when high AAc:LNR ratio and lower MBA concentration were used. The R{sup 2} values for these quadratic models were 0.9891 and 0.9939 (swelling and Ni{sup 2+} removal percentage), respectively, which showed that the models were well-fitted with the experimental data. From the analysis, the optimum conditions for maximum swelling capacity (1181.90%) and Ni{sup 2+} removal percentage (26.74%) were hydrogel with AAc:LNR ratio 3.00 g/g and 0.05 M of MBA.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mechanism of Catalysis by L -Asparaginase

Two bacterial type II L -asparaginases, from Escherichia coli and Dickeya chrysanthemi, have played a critical role for more than 40 years as therapeutic agents against juvenile leukemias and lymphomas. Despite a long history of successful pharmacological applications and the apparent simplicity of the catalytic reaction, controversies still exist regarding major steps of the mechanism. In this report, we provide a detailed description of the reaction catalyzed by E. coli type II L -asparaginase (EcAII). Our model was developed on the basis of new structural and biochemical experiments combined with previously published data. The proposed mechanism is supported by quantum chemistry calculations based on density functional theory. In this work, we provide strong evidence that EcAII catalyzes the reaction according to the double-displacement (ping-pong) mechanism, with formation of a covalent intermediate. Several steps of catalysis by EcAII are unique when compared to reactions catalyzed by other known hydrolytic enzymes. Here, the reaction is initiated by a weak nucleophile, threonine, without direct assistance of a general base, although a distant general base is identified. Furthermore, tetrahedral intermediates formed during the catalytic process are stabilized by a never previously described motif. Although the scheme of the catalytic mechanism was developed only on the basis of data obtained from EcAII and its variants, this novel mechanism of enzymatic hydrolysis could potentially apply to most (and possibly all) L -asparaginases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1972

Mechanisms of deterioration of intermediate moisture food systems

A study of shelf stability in intermediate moisture foods was made. Major efforts were made to control lipid oxidation and nonenzymatic browning. In order to determine means of preventing these reactions, model systems were developed having the same water activity content relationship of intermediate moisture foods. Models were based on a cellulose-lipid and protein-lipid system with glycerol added as the humectant. Experiments with both systems indicate that lipid oxidation is promoted significantly in the intermediate moisture range. The effect appeared to be related to increased mobility of either reactants or catalysts, since when the amount of water in the system reached a level where capillary condensation occurred and thus free water was present, the rates of oxidation increased. With added glycerol, which is water soluble and thus increases the amount of mobile phase, the increase in oxidation rate occurs at a lower relative humidity. The rates of oxidation were maximized at 61% RH and decreased again at 75% RH probably due to dilution. No significant non-enzymatic browning occurred in the protein-lipid systems. Prevention of oxidation by the use of metal chelating agents was enhanced in the cellulose system, whereas, with protein present, the lipid soluble chain terminating antioxidants (such as BHA) worked equally as well. Preliminary studies of foods adjusted to the intermediate moisture range bear out the results of oxidation in model systems. It can be concluded that for most fat containing intermediate moisture foods, rancidity will be the reaction most limiting stability.

Labuza, T. P.↗
NASA NTRS2002

Purification method for recombinant proteins based on a fusion between the target protein and the C-terminus of calmodulin

Calmodulin (CaM) was used as an affinity tail to facilitate the purification of the green fluorescent protein (GFP), which was used as a model target protein. The protein GFP was fused to the C-terminus of CaM, and a factor Xa cleavage site was introduced between the two proteins. A CaM-GFP fusion protein was expressed in E. coli and purified on a phenothiazine-derivatized silica column. CaM binds to the phenothiazine on the column in a Ca(2+)-dependent fashion and it was, therefore, used as an affinity tail for the purification of GFP. The fusion protein bound to the affinity column was then subjected to a proteolytic digestion with factor Xa. Pure GFP was eluted with a Ca(2+)-containing buffer, while CaM was eluted later with a buffer containing the Ca(2+)-chelating agent EGTA. The purity of the isolated GFP was verified by SDS-PAGE, and the fluorescence properties of the purified GFP were characterized.

Non-NASA Center↗
NASA NTRS1989

A prototype autonomous agent for crew and equipment retrieval in space

The ground-based demonstration of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: perception, world model, reasoning, sensing, and acting. The design provides for supervised autonomy as the primary mode of operation with teleoperation as the backup mode. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable operation.

Erickson, J. D.↗
DOE OSTI2018

Minority Serving Institutions Partnership Program (MSIPP) - 18108

The DOE-EM recognizes that successfully completing its legacy environmental cleanup mission will require maintaining a well-trained, technically skilled, and diverse workforce. Minority representation in critical science and engineering fields is an important part of EM's vision for the future workforce. The Minority Serving Institutions Partnership Program (MSIPP) has been created and designed to increase the numbers of minorities with science and engineering experience in areas important to the success of the DOE-EM mission. MSIPP will provide financial assistance for science, technology, engineering, and mathematics (STEM) activities at Minority Serving Institutions (MSI) engaged in research and related STEM efforts supporting EM's needs. The program offers research internship opportunities at DOE National Laboratories across the DOE complex. MSIPP also encourages research collaborations between MSI Universities and DOE National Laboratories by funding research in areas relevant to DOE-EM needs. Based on current DOE-EM missions, there are two research focus areas: Tank Waste and Site Restoration. Tank Waste includes priority areas of current DOE tank waste and waste processing approaches, alternative DOE tank waste processing options, and tank management and closure. Site Restoration research concentrates in the areas of Soil and Groundwater with priority areas of attenuation-based remedies for the subsurface, deep vadose zone, remediation of mercury and industrial contaminants, and advanced simulation capability for environmental management; and, in the areas of Deactivation and Decommissioning, with priority areas of unique sensor networks for remote monitoring of entombed facilities and tanks, interactions between radiological and chemical contaminants of concern to DOE and facility materials, incombustible fixatives and decontamination agents, acceptability of DeconGel and various contaminant mixtures and robotics, remote systems with plug-and-play interchangeable components, and models for facility decommissioning. This paper gives an overview of the opportunities available to MSI students and universities and outlines the progress this program has made since its inception, and the path forward to further enhance efforts to create a pipeline into the DOE-EM workforce. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Imaging in Diagnostic Nuclear Medicine

Single-photon emission computed tomography (SPECT) and positron emission tomography (PET) are modern methods for visualization in diagnostic nuclear medicine. SPECT is known as a workhorse in cardiology, and PET is the gold standard in oncology. The development of nuclear medicine is provided by cooperation of physicists, mathematicians, biologists, medical doctors, and radio-chemists. In spite of extensive clinical applications, several problems may lead to false diagnoses. In particular, the correction of attenuation of gamma radiation in human organs must be taken into account. For interpretation and evaluation of such an effect on the clinical results, we perform physico-mathematical simulation of the SPECT diagnostics in cardiology in the absence and presence of the correction of attenuation. A brief review of the state-of-the art is presented. The simulation employs the first Russian anthropomorphic mathematical phantom that describes the distribution of radio-pharmacological agent ({sup 99m }Tc-methoxyisobutylisonitrile) in chest organs of a typical male patient. A model for calculation of raw images is developed with allowance for attenuation of radiation in biological tissues and the effect of collimator and detector. The results of the proposed models and calculated images are compared with clinical images obtained at the Meshalkin Institute of Circulation Pathology (Novosibirsk) and Myasnikov Institute of Clinical Cardiology (Moscow). Statistical algorithms are developed for the solution of the inverse problem of image reconstruction based on the entropy principle. The clinical and physico-mathematical approaches are compared in the evaluation of the effect of correction on the quality of reconstructed images of the left ventricle of myocardium.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Surrogates for Valve-Controlled Pipe Flow: Accelerating Nuclear Reactor Design

Neural surrogate models are developed to replace expensive steady-state RANS CFD simulations for valve-controlled pipe flow in nuclear reactor design. Using parametric CFD data generated with MOOSE Pronghorn across a range of valve geometry and flow conditions, three approaches are compared: a POD-based reduced-order model, a structured UNet on a cylindrical grid, and unstructured models (DeepONet and BiStride MeshGraphNet) on nondimensionalized point clouds. POD achieves the highest accuracy (99%) with fast inference but requires storing all solution snapshots, while the DeepONet and BSMS-GNN both achieve ~89% accuracy at sub-second inference, with the BSMS-GNN offering superior geometric generalizability. These surrogates enable rapid ranking of candidate valve designs and can warm-start CFD solvers to accelerate convergence, supporting agentic design iteration on the Prometheus platform.

42 - ENGINEERING↗
DOE OSTI2018

Special Issue “Mathematical Modeling of Viral Infections”

How an infection will progress in the body is dependent on myriad factors: the rate of spread of the agent, the immune response, what treatment may be applied, .... Clinically following the progression of the disease is limited to snapshots at discrete time points (longitudinally in an individual or in an in vitro/animal model if that is available, but most often from cross-sectional data over cohorts of individuals), and in many cases the data obtained are from a body compartment that is not the site of replication of the disease. We then infer disease progression by putting these discrete data together based on our biological knowledge of the systems involved. However, based on these snapshots, it is not straightforward to work out important disease properties, such as the rate of progression, pathogenicity, and treatment and immune response effects. Mathematical modelling provides a scientifically sound, reproducible method to describe the underlying dynamics that produce these data, as well as a means to investigate new scenarios, such as the effect of a new drug. Its impact has been demonstrated on a number of diseases, for example, contributing to a better understanding of the speed with which human immunodeficiency virus (HIV) replicates [1,2], the dynamics of different drug classes for HIV [3], the main mode of action of interferon in hepatitis C virus (HCV) [4], the effects of direct-acting antivirals in HCV [5], potential effects of the immune response [6], and many others [7–11].

Murray, John↗
DOE OSTI2020

Estimation of Large-Scale Wind Field Characteristics Using Supervisory Control and Data: Preprint

As the wind energy industry continues to pushfor increased power production and lower cost of energy, thefocus of research has expanded from individual turbines toentire wind farms. Among a host of interesting problems to besolved when considering the wind farm as a whole, we considerthe challenge of scalar field estimation, based on informationalready collected at the individual turbine level. We aim toestimate the large-scale, low-frequency characteristics of thewind field, such as the mean wind direction and the overalldecrease in wind speed across the farm, and employ a Kalmanfilter that models the wind field using a polynomial function.We compare the proposed method’s performance to both asimple averaging technique and filtering of individual turbinemeasurements. The method presented is not limited to windturbines and is applicable in other situations where multipleremote agents are used to estimate a scalar field.

large scale↗
DOE OSTI2019

Complementary bimodal approach to monitoring of photodynamic therapy with targeted nanoconstructs: numerical simulations

We propose a new approach to monitoring photodynamic therapy (PDT) of glioblastoma with the use of targeted nanoconstructs containing a photosensitiser (PS) [benzoporphyrin derivative (BPD)] and IRDye800 dye, antibodies for efficient accumulation of the drug in a tumour, and a chemotherapeutic agent for combined effect on tumour cells. Application of IRDye800 is determined by the shift of its absorption and fluorescence spectra to the near-IR range with respect to BPD that ensures a higher imaging depth. Monitoring of PDT is based on the simultaneous fluorescence and optoacoustic (OA) imaging. Fluorescence imaging provides visualisation of fluorescence agents with high molecular sensitivity and monitoring of the effectiveness of PDT by PS photobleaching. OA allows one to examine the vascular pattern of the tumour environment, as well as assess the depth of the tumour. IRDye800 is a better contrast agent in comparison to BPD due to red-shifted spectral characteristics and a higher fluorescence quantum yield. Monte Carlo simulations combined for OA simulations with K-wave modelling allowed the feasibility of the complementary approach to be studied and demonstrated that this combination allows one to localise a tumour with a size of 2 mm at depths from 100 μm to 2 mm. (paper)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Localization of fluorescent targets in deep tissue with expanded beam illumination for studies of cancer and the brain

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Principles for Integrating Mars Analog Science, Operations, and Technology Research

During the Apollo program, the scientific community and NASA used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. Human factors studies (Harrison, Clearwater, & McKay 1991; Stuster 1996) have focused on the effects of isolation in extreme environments. More recently, with the advent of wireless computing, we have prototyped advanced EVA technologies for navigation, scheduling, and science data logging (Clancey 2002b; Clancey et al., in press). Combining these interests in a single expedition enables tremendous synergy and authenticity, as pioneered by Pascal Lee's Haughton-Mars Project (Lee 2001; Clancey 2000a) and the Mars Society s research stations on a crater rim on Devon Island in the High Canadian Arctic (Clancey 2000b; 2001b) and the Morrison Formation of southeast Utah (Clancey 2002a). Based on this experience, the following principles are proposed for conducting an integrated science, operations, and technology research program at analog sites: 1) Authentic work; 2) PI-based projects; 3) Unencumbered baseline studies; 4) Closed simulations; and 5) Observation and documentation. Following these principles, we have been integrating field science, operations research, and technology development at analog sites on Devon Island and in Utah over the past five years. Analytic methods include work practice simulation (Clancey 2002c; Sierhuis et a]., 2000a;b), by which the interaction of human behavior, facilities, geography, tools, and procedures are formalized in computer models. These models are then converted into the runtime EVA system we call mobile agents (Clancey 2002b; Clancey et al., in press). Furthermore, we have found that the Apollo Lunar Surface Journal (Jones, 1999) provides a vast repository or understanding astronaut and CapCom interactions, serving as a baseline for Mars operations and quickly highlighting opportunities for computer automation (Clancey, in press).

Clancey, William J.↗
NASA NTRS2021

Developing a Set of Indicators to Identify, Monitor, and Track Impacts and Change in Forests of the United States

United States forestland is an important ecosystem type, land cover, land use, and economic resource that is facing several drivers of change including climatic. Because of its significance, forestland was identified through the National Climate Assessment(NCA) as a key sector and system of concern to be included in a system of climate indicators as part of a sustained assessment effort. Here, we describe 11 informative core indicators of forests and climate change impacts with metrics available or nearly available for use in the NCA efforts. The recommended indicators are based on a comprehensive conceptual model which recognizes forests as a land use, an ecosystem, and an economic sector. The indicators cover major forest attributes such as extent, structural components such as biomass, functions such as growth and productivity, and ecosystem services such as biodiversity and outdoor recreation. Interactions between humans and forests are represented through indicators focused on the wildland-urban interface, cost to mitigate wildfire risk, and energy produced from forest-based biomass. Selected indicators also include drought and disturbance from both wildfires and biotic agents. The forest indicators presented are an initial set that will need further refinement in coordination with other NCA indicator teams. Our effort ideally will initiate the collection of critical measurements and observations and lead to additional research on forest-climate indicators.

U.S. forests↗
DOE OSTI2022

In Situ EXAFS-Based Nanothermometry of Heterodimer Nanocrystals under Induction Heating

The ability to heat nanocrystalline materials through magnetic induction has been used in the fields of catalysis, biomedical sciences, and polymer degradation. However, the working temperature to which the inductively coupled material rises is still poorly understood. Herein, we use extended X-ray absorption fine structure spectroscopy in conjunction with thermal imaging to improve the understanding of heating in inductively coupled systems. After extraction of the Debye–Waller factor from the spectroscopy, we obtain the temperature of inductively heated nanocrystals from the correlated Debye model. We combine carbon-supported iron oxide nanocrystals as induction heating agents with platinum nanocrystals as thermal probes. By testing these nanocrystal species as both unattached nanocrystals and heterodimers, we report that nanostructured systems show a significant temperature difference of up to 73.60 °C when compared to their local support environment. Furthermore, this result has implications for inductively heated catalysis, magnetic hyperthermia for targeted cell death, and polymer synthesis.

09 BIOMASS FUELS↗
DOE OSTI2024

Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries

The rapid growth of automated and autonomous instrumentation brings forth opportunities for the co-orchestration of multimodal tools that are equipped with multiple sequential detection methods or several characterization techniques to explore identical samples. This is exemplified by combinatorial libraries that can be explored in multiple locations via multiple tools simultaneously or downstream characterization in automated synthesis systems. In co-orchestration approaches, information gained in one modality should accelerate the discovery of other modalities. Correspondingly, an orchestrating agent should select the measurement modality based on the anticipated knowledge gain and measurement cost. Herein, we propose and implement a co-orchestration approach for conducting measurements with complex observables, such as spectra or images. The method relies on combining dimensionality reduction by variational autoencoders with representation learning for control over the latent space structure and integration into an iterative workflow via multi-task Gaussian Processes (GPs). This approach further allows for the native incorporation of the system's physics via a probabilistic model as a mean function of the GPs. We illustrate this method for different modes of piezoresponse force microscopy and micro-Raman spectroscopy on a combinatorial Sm-BiFeO3 library. However, the proposed framework is general and can be extended to multiple measurement modalities and arbitrary dimensionality of the measured signals.

47 OTHER INSTRUMENTATION↗