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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Cloud-Based Demodulation and Data Distribution of a Satellite Downlink

Ground station networks connected to the cloud allow space missions to have global communications coverage without operating their own infrastructure. In this work, we describe the communications architecture for the TechEdSat-13 mission, which performed the first in-space characterization of a neuromorphic processor. The mission utilizes a commercial provider for S-band downlinks. A suite of cloud services and open-source software such as GNU Radio are leveraged to demodulate signals received by an AWS ground station during passes with TechEdSat-13 and store recovered data. Once a pass is scheduled, the entire process takes place without human intervention. On-orbit results the past year of operations are presented, demonstrating the advantages of this approach over traditional operator-owned ground stations. Use of software-defined radio makes possible custom signal processing. The homogeneity of apertures and their interfaces to the cloud simplifies scaling across many sites. This abundance of candidate links lays the groundwork for intelligent scheduling agents to optimize pass selection across several factors, automatically recover from failed contacts, and gather metrics to learn from past performance.

cloud demodulation↗
DOE OSTI2024

Distribution Grid Incentive Design with Unknown Agent Behavior

Motivation: During extreme events, traditional grid regulation methods (e.g., energy prices, net power injection limits) may be insufficient. While system operators typically lack control over end-user grid interactions, (e.g., energy demand), incentives can influence behavior - for example, a user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. Problem: Optimize for the best incentive subject to system stability constraints. However, user behavior is unknown to the SO - i.e., for a given incentive, the amount of curtailed load or control variables exposed is unknown.

feedback based control↗
NASA NTRS2004

Distributed network scheduling

Distributed Network Scheduling is the scheduling of future communications of a network by nodes in the network. This report details software for doing this onboard spacecraft in a remote network. While prior work on distributed scheduling has been applied to remote spacecraft networks, the software reported here focuses on modeling communication activities in greater detail and including quality of service constraints. Our main results are based on a Mars network of spacecraft and include identifying a maximum opportunity of improving traverse exploration rate a factor of three; a simulation showing reduction in one-way delivery times from a rover to Earth from as much as 5 to 1.5 hours; simulated response to unexpected events averaging under an hour onboard; and ground schedule generation ranging from seconds to 50 minutes for 15 to 100 communication goals.

planning↗
DOE OSTI2026

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗
DOE OSTI2024

Combatting melioidosis with chemical synthetic lethality

Burkholderia thailandensishas emerged as a nonpathogenic surrogate forBurkholderia pseudomallei, the causative agent of melioidosis, and an important Gram-negative model bacterium for studying the biosynthesis and regulation of secondary metabolism. We recently reported that subinhibitory concentrations of trimethoprim induce vast changes in both the primary and secondary metabolome ofB. thailandensis. In the current work, we show that the folate biosynthetic enzyme FolE2 is permissive under standard growth conditions but essential forB. thailandensisin the presence of subinhibitory doses of trimethoprim. Reasoning that FolE2 may serve as an attractive drug target, we screened for and identified ten inhibitors, including dehydrocostus lactone (DHL), parthenolide, and β-lapachone, all of which are innocuous individually but form a chemical-synthetic lethal combination with subinhibitory doses of trimethoprim. We show that DHL is a mechanism-based inhibitor of FolE2 and capture the structure of the covalently inhibited enzyme using X-ray crystallography. In vitro, the combination of subinhibitory trimethoprim and DHL is more potent than Bactrim, the current standard of care against melioidosis. Moreover, unlike Bactrim, this combination does not affect the growth of most commensal and beneficial gut bacteria tested, thereby providing a degree of specificity againstB. pseudomallei. Our work provides a path for identifying antimicrobial drug targets and for utilizing binary combinations of molecules that form a toxic cocktail based on metabolic idiosyncrasies of specific pathogens.

Science & Technology - Other Topics↗
DOE OSTI2022

GOOML - Finding Optimization Opportunities for Geothermal Operations: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach. We have used this framework to develop digital twins that provide steamfield operators with an operational environment to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management for real world applications. The GOOML modeling software is built on a generic component-based systems framework that allows for both historical and forecast analysis. A GOOML model can perform historical data-assimilation using first-principal thermodynamics to create a meaningful data model. Historical production data can then be coupled with a forecast framework to train machine-learning models of steamfield components to predict future outputs. This modeling environment enables digital exploration of steamfield design configurations and operational scenarios. GOOML digital twins have been developed for steamfields in New Zealand and the United States representing differing power generation and field conditions. These digital twins have been validated by comparing hindcast predictions against historical production data. Reinforcement learning experiments were conducted to demonstrate the ability to programmatically explore the operations space using machine learning agents. Our initial results are compelling; two to five percent increases in annual energy production were demonstrated by the GOOML models with no additional infrastructure build required. GOOML offers a new approach to geothermal operations by applying state-of-the-art machine learning algorithms, comprehensive data analytics, and interaction with digital twins. Through application of these tools, operators will realize greater availability and higher net generation which will increase the cost effectiveness of geothermal energy projects.

access↗
DOE OSTI2024

Copper and bismuth-based sorbent characterization in simulated iodine off-gas streams

The effective capture of volatile radioiodine, a fission product present in used nuclear fuel (UNF), is of paramount importance for development of used fuel reprocessing schemes to prevent release of radioiodine during unit operations and to meet regulatory standards for air emissions. A well-studied method for iodine capture in off-gas streams is the use of silver-functionalized zeolite phases (AgZ), which exploit chemisorption of I to Ag. Advances into other Ag-functionalized materials, including aerogels and metal organic frameworks (MOFs), are underway [1]. Additional metals with the capability to chemisorb iodine, including Cu, Bi, and Sn, [1] are being evaluated as alternatives to Ag for potential applicability to iodine management in off-gas systems. The design of novel functionalized sorbents with Cu and Bi, including composites with metal particles embedded in PAN substrates [2] and composites with metal sulfides embedded in PAN [3], is an ongoing area of study for improved iodine capture. Previously reported work on novel PAN-based metal sorbents has provided the synthesis, characterization, and iodine capture efficiency of this new class of sorbent. Specifically, the metal sulfide PAN composites are found to be easy to produce and reproduce, as well as having a high iodine loading potential under static conditions [3]. Due to the favorable testing previously performed with metal sulfide PAN composites, further testing into the performance of these composites under gas streams containing I2(g) in combination with NO2(g) and H2O(g) is needed. Humid streams of NO2(g) may arise from dissolver off-gas streams, when used fuel is dissolved in HNO3(aq) [4]. NO2(g) has been found to reduce AgZ sorption capacity for I because of oxidation of Ag, the chemisorbing agent, to Ag2O [5]. It follows that performance evaluation of novel sorbents under highly oxidizing conditions such as NO2(g) streams is critical. Therefore, the objective of this study is to determine the effect of flowing NO2(g) and H2O(g) streams on iodine sorption capacity and sorbent performance. This work utilizes custom-built gas handling capabilities for sorbent exposure along with solid-state characterization techniques to assess the physical and chemical properties of sorbents before and after exposure.

copper, bismuth, iodine capture, iodine sorbent, p↗
NASA NTRS1991

Fiber optic-based biosensor

The NRL fiber optic biosensor is a device which measures the formation of a fluorescent complex at the surface of an optical fiber. Antibodies and DNA binding proteins provide the mechanism for recognizing an analyze and immobilizing a fluorescent complex on the fiber surface. The fiber optic biosensor is fast, sensitive, and permits analysis of hazardous materials remote from the instrumentation. The fiber optic biosensor is described in terms of the device configuration, chemistry for protein immobilization, and assay development. A lab version is being used for assay development and performance characterization while a portable device is under development. Antibodies coated on the fiber are stable for up to two years of storage prior to use. The fiber optic biosensor was used to measure concentration of toxins in the parts per billion (ng/ml) range in under a minute. Immunoassays for small molecules and whole bacteria are under development. Assays using DNA probes as the detection element can also be used with the fiber optic sensor, which is currently being developed to detect biological warfare agents, explosives, pathogens, and toxic materials which pollute the environment.

Ligler, Frances S.↗
DOE OSTI2022

Nitrile-Containing Renewable Polymers Based on Lignin, (CRADA) No. NFE 1807437 (CRADA Final Report)

Lignin remains one of the world’s largest sources of renewable carbon, with significant potential to positively impact our carbon footprint by replacing fossil-fuel derived materials, including engineering thermoplastics and their composites. Efforts to incorporate significant quantity of lignin into engineering thermoplastics as anything other than an inert filler have to date been largely unsuccessful, however due to limitations imposed by the degradation temperature of the lignin (220 °C) and poor compatibility between the lignin and non-polar or slightly polar polymers. Recent work at Oak Ridge National Laboratory has however shown under the right conditions excellent compatibility between lignin and nitrile containing rubber compounds such as nitrile-butadiene rubber (NBR). The present work extends these findings to the incorporation of lignin into acrylonitrile-butadiene-styrene (ABS) engineering plastics. While simple binary mixing of lignin into commercial ABS resins leads to poor interfacial adhesion and resultant low toughness and ductility, appropriate matching of the lignin and ABS components, and as appropriate compatibilizing agents, leads to polymer blends incorporating 20-35% by weight lignin with a useful range of mechanical properties for many current ABS applications. By modifying the composition, the balance of properties can be readily tailored to meet the demands of specific end-user applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Matrix Metalloproteinases as Candidate Antigenic Determinants for Anti‐Tumor Autoantibodies in Human Ovarian Cancer: A Post Hoc Analysis

Circulating antibodies in patients with cancer can facilitate the identification of accessible epitopes on autoantigens expressed by tumors. To identify previously unrecognized protein targets in ovarian cancer, we computationally assessed a heptapeptide consensus motif (VPELGHE, flanked by two cysteine residues yielding a cyclic nonapeptide under oxidizing conditions) previously discovered via phage display-based epitope mapping of autoantibodies in patients. Eight proteins associated with ovarian cancer encompass amino acid sequences similar to the consensus motif and were, therefore, considered as candidate native autoantigens. Among these candidate targets, however, matrix metalloproteinase 14 (MMP14) demonstrates gene expression that is both high and negatively correlated with survival in ovarian cancer patient cohorts. MMP14 protein levels are also stable in tumor versus non-tumor tissues. Moreover, the corresponding heptapeptide mimic in MMP14 occurs within an α-helical secondary structural element observed in its catalytic domain. These findings demonstrate that a subset of patient-derived autoantibodies may interact with a previously unknown antigenic epitope found in MMP14 and other MMPs, thereby providing opportunities for the development of new targeted agents.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Neutron Response of the EJ-254 Boron-Loaded Plastic Scintillator

Organic scintillators doped with capture agents provide a detectable signal for neutrons over a broad energy range. This work characterizes the fast and slow neutron response of EJ-254, an organic plastic scintillator with 5 loading by weight. For fast neutrons, the primary mechanism for light generation in organic scintillators is n-p elastic scattering. To study the fast neutron response, the proton light yield of EJ-254 was measured at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. Using a broad-spectrum neutron source and a double time-of-flight technique, the EJ-254 proton light yield was obtained over the energy range of approximately 270 keV to 4.5 MeV and determined to be in agreement with other plastic scintillators comprised of the same polymer base. To isolate the slow neutron response, an AmBe source with polyethylene moderator was made incident on the EJ-254 scintillator surrounded by an array of EJ-309 observation detectors. Events in the EJ-254 target coincident with the signature 477.6 keV γ ray (resulting from de-excitation of the residual 7Li nucleus following boron neutron capture) were identified. Pulse shape discrimination was used to evaluate the temporal differences in the response of EJ-254 scintillation signals arising from γ-ray and fast/slow neutron interactions. Clear separation between γ-ray and fast neutrons signals was not achieved and the neutron capture feature was observed to overlap both the γ-ray and fast neutron bands. Taking into account the electron light nonproportionality, the neutron capture light yield in EJ-254 was determined to be 89.4±1.1 keVee.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Robustness of cement-based materials: From dosage variations to yield stress fluctuations

The idea behind the present work is to assess robustness of fresh cement-based materials (i.e. their ability to display the same properties when submitted to variations in the way they are produced) from a generic and analytical point of view. First, analytical models from literature relating components proportions and yield stress are combined into a multi-scale and physical approach and compared to our experimental yield stress measurements. In the second part, the derivation of these analytical relationships is used to assess robustness as a function of components proportions, which allows for the most sensitive variations to be mapped onto component dosage from a yield stress point of view. In the case of fluid concretes, this approach showcases the interest of working at slightly higher water content and slightly lower aggregates fraction along with benefits of viscosity modifying agents / plasticizers combination.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Genome Sequence of the Chestnut Blight Fungus Cryphonectria parasitica EP155: A Fundamental Resource for an Archetypical Invasive Plant Pathogen

Cryphonectria parasitica is the causal agent of chestnut blight, a fungal disease that almost entirely eliminated mature American chestnut from North America over a 50-year period. Here, we formally report the genome of C. parasitica EP155 using a Sanger shotgun sequencing approach. After finishing and integration with simple-sequence repeat markers, the assembly was 43.8 Mb in 26 scaffolds (L 50 = 5; N 50 = 4.0Mb). Eight chromosomes are predicted: five scaffolds have two telomeres and six scaffolds have one telomere sequence. In total, 11,609 gene models were predicted, of which 85% show similarities to other proteins. Finally, this genome resource has already increased the utility of a fundamental plant pathogen experimental system through new understanding of the fungal vegetative incompatibility system, with significant implications for enhancing mycovirus-based biological control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Pharmacological Profiling of a Brugia malayi Muscarinic Acetylcholine Receptor as a Putative Antiparasitic Target

The diversification of anthelmintic targets and mechanisms of action will help ensure the sustainable control of nematode infections in response to the growing threat of drug resistance. G protein-coupled receptors (GPCRs) are established drug targets in human medicine but remain unexploited as anthelmintic substrates despite their important roles in nematode neuromuscular and physiological processes. Bottlenecks in exploring the druggability of parasitic nematode GPCRs include a limited helminth genetic toolkit and difficulties establishing functional heterologous expression. In an effort to address some of these challenges, we profile the function and pharmacology of muscarinic acetylcholine receptors in the human parasite Brugia malayi, an etiological agent of human lymphatic filariasis. While acetylcholine-gated ion channels are intensely studied as targets of existing anthelmintics, comparatively little is known about metabotropic receptor contributions to parasite cholinergic signaling. Using multivariate phenotypic assays in microfilariae and adults, we show that nicotinic and muscarinic compounds disparately affect parasite fitness traits. We identify a putative G protein-linked acetylcholine receptor of B. malayi (Bma-GAR-3) that is highly expressed across intramammalian life stages and adapt spatial RNA in situ hybridization to map receptor transcripts to critical parasite tissues. Tissue-specific expression of Bma-gar-3 in Caenorhabditis elegans (body wall muscle, sensory neurons, and pharynx) enabled receptor deorphanization and pharmacological profiling in a nematode physiological context. Finally, we developed an image-based feeding assay as a reporter of pharyngeal activity to facilitate GPCR screening in parasitized strains. We expect that these receptor characterization approaches and improved knowledge of GARs as putative drug targets will further advance the study of GPCR biology across medically important nematodes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A near-infrared optical nanosensor for measuring aerobic respiration in microbial systems

We developed a ratiometric oxygen-sensitive nanosensor and demonstrated application in monitoring metabolic oxygen consumption in microbial samples over time. Based on a near-infrared (NIR) emitting oxygen-quenched luminophore, platinum(II) octaethylporphine ketone (PtOEPK), along with a stable dioctadecyl dicarbocyanine reference dye (DiD), this nanosensor system provides an advantageous approach for overcoming imaging issues in biological systems, such as autofluorescence and optical scattering in the visible wavelength region. The dyes are encapsulated within a polymer-based nanoparticle matrix to maintain them at a constant ratio in biological samples, precluding the need for complex synthetic approaches. With this constant ratio of the two dyes, the nanosensor response can be measured as a ratio of their two signals, accounting for nanosensor concentration artifacts in measurements. The nanosensors are reversible, which enabled us to temporally monitor systems in which dissolved oxygen concentrations both increase and decrease. These sensors were applied for the monitoring of oxygen in samples of Saccharomyces cerevisiae (brewing yeast) in a 96-well optical fluorescence plate reader format over 60 h. By mixing the nanosensors directly into the sample well with the yeast, we were able to dynamically track metabolic activity changes over time due to varying cell concentration and exposure to an antimicrobial agent. As a result, this system could be a potential platform for high-throughput screening of various species or variants of microbes with unknown metabolic rates in response to external stimuli (antimicrobials, metabolites, etc.).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Quantum model learning agent: characterisation of quantum systems through machine learning

Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distil empirically. Here, we report an algorithm—the quantum model learning agent (QMLA)—to reverse engineer Hamiltonian descriptions of a target system. We test the performance of QMLA on a number of simulated experiments, demonstrating several mechanisms for the design of candidate Hamiltonian models and simultaneously entertaining numerous hypotheses about the nature of the physical interactions governing the system under study. QMLA is shown to identify the true model in the majority of instances, when provided with limited a priori information, and control of the experimental setup. Our protocol can explore Ising, Heisenberg and Hubbard families of models in parallel, reliably identifying the family which best describes the system dynamics. We demonstrate QMLA operating on large model spaces by incorporating a genetic algorithm to formulate new hypothetical models. The selection of models whose features propagate to the next generation is based upon an objective function inspired by the Elo rating scheme, typically used to rate competitors in games such as chess and football. In all instances, our protocol finds models that exhibit F 1 score ≥ 0.88 when compared with the true model, and it precisely identifies the true model in 72% of cases, whilst exploring a space of over 250 000 potential models. By testing which interactions actually occur in the target system, QMLA is a viable tool for both the exploration of fundamental physics and the characterisation and calibration of quantum devices.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

In-Vitro Induced Immunosuppression in a Rotary Cell Culture System

The function of the innate immune system is to provide a first-line of defense against infectious organisms, via control of bacterial and viral growth using antigen nonspecific means. These nonspecific immune effectors include macrophages and Natural Killing (NK) cells, and certain cytokines elicited in response to "super antigens" on the infectious agents. This innate system usually keeps most infectious agents from rapidly growing while the adaptive immune system is generating a specific response complete with immunologic memory. Compelling evidence suggests that space flight results in various immunosuppressive effects, including reduced innate and adaptive immune responses. We were particularly concerned with reduced NK activity at landing, and have asked whether the microgravity component of space flight could be responsible for the previously observed NK defect. We have conclusively demonstrated that simulated microgravity as provided by the Synthecon bioreactors does not inhibit the NK function nor the IL-2 activation of lymphokine-activated killing (LAK). Interleukin-2 is the key cytokine responsible for activation of NK cells to express LAK, as well as to support differentiation of lymphocytes during adaptive immune responses. Therefore, we have disproved our original hypothesis based on poor NK in many of the astronauts upon landing.

Grimm, Elizabeth A.↗