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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Model of a Thin Current Sheet in the Earth’s Magnetotail with a Kinetic Description of Magnetized Electrons

Steady-state two-dimensional thin current sheets (TCSs) in collisionless space plasma, similar to the current sheet of the near-Earth magnetotail, are considered. The magnetic field of the sheet is orthogonal to the current and has a nonzero normal component, the electrons are magnetized, and the ions are unmagnetized. To solve the problem of kinetic description of electrons in such current sheets in a general form, they are described by the Vlasov equation in the drift approximation, the general solution to which is found in the form of a function of three independent integrals of the system of drift motion equations. An important case is considered in which the electron guiding centers obey a Maxwell–Boltzmann distribution in a stationary electromagnetic field. The obtained results make it possible to create one- and two-dimensional numerical− analytical models of current sheets in which unmagnetized ions are described by the Vlasov equation, which should be solved numerically, whereas the contribution of magnetized electrons is taken into account analytically. To numerically solve the time-independent Vlasov equation, a new method is proposed that allows one to perform the bulk of computations by using graphic processors. On the basis of the new theory, a one-dimensional numerical−analytical model of a steady-state TCS in the near-Earth magnetotail is presented, TCS configurations are calculated, and the role of electrostatic effects and electron pressure anisotropy is analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

A method for increasing expressivity of Gene Ontology annotations using a compositional approach

Background: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. Results: The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector–target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. Conclusions: The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism’s gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Differential geometry-based solvation and electrolyte transport models for biomolecular modeling: a review

This chapter reviews the differential geometry-based solvation and electrolyte transport for biomolecular solvation that have been developed over the past decade. A key component of these methods is the differential geometry of surfaces theory, as applied to the solvent-solute boundary. In these approaches, the solvent-solute boundary is determined by a variational principle that determines the major physical observables of interest, for example, biomolecular surface area, enclosed volume, electrostatic potential, ion density, electron density, etc. Recently, differential geometry theory has been used to define the surfaces that separate the microscopic (solute) domains for biomolecules from the macroscopic (solvent) domains. In these approaches, the microscopic domains are modeled with atomistic or quantum mechanical descriptions, while continuum mechanics models (including fluid mechanics, elastic mechanics, and continuum electrostatics) are applied to the macroscopic domains. This multiphysics description is integrated through an energy functional formalism and the resulting Euler-Lagrange equation is employed to derive a variety of governing partial differential equations for different solvation and transport processes; e.g., the Laplace-Beltrami equation for the solvent-solute interface, Poisson or Poisson-Boltzmann equations for electrostatic potentials, the Nernst-Planck equation for ion densities, and the Kohn-Sham equation for solute electron density. Extensive validation of these models has been carried out over hundreds of molecules, including proteins and ion channels, and the experimental data have been compared in terms of solvation energies, voltage-current curves, and density distributions. We also propose a new quantum model for electrolyte transport.

chemistry↗
DOE OSTI2024

GDB-9-Ex_TD-DFT-PBE0: Dataset containing Time Dependent Density Functional Theory (TDDFT) calculations for organic molecules of the GDB-9-Ex dataset.

This dataset contains data-intensive quantum chemical electronic structure calculations for 96,766 organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Time Dependent Density Functional Theory (TDDFT) first principles method using the ORCA software. It provides UV-vis spectra calculations of molecules with a high level of accuracy. The optical spectra behavior was collected based on the optimized molecular geometries in the DFTB method with 3ob parameters. All calculations utilized the def2-TZVP basis sets with the auxiliary def2/J and def2-TZVP/C basis sets. The time-dependent density-functional theory (TDDFT) approach with the PBE0 exchange-correlation functional and ORCAs default integration grid was employed. For the excitation energy calculations, the lowest 50 excitation states were calculated.

AI dataset↗
DOE OSTI2025

Topography restoration in white-light interferometry using an instrument transfer function evaluated with binary pseudo-random arrays

Accurate knowledge of the instrument transfer function (ITF) is vital for topography measurements using white-light interferometry (WLI). To this end, we derive a complete set of analytical expressions for the power spectral density (PSD) of a discretely sampled binary pseudo-random array (BPRA) as a theoretical benchmark. We then determine the ITF by comparing this theoretical PSD with the measured PSD of the BPRA. For the Zygo ZeGage Pro HR with a objective, the determined ITF closely matches the nominal modulation transfer function (MTF). Accordingly, we integrate the nominal MTF into Fourier-domain restoration filters and apply them to practical WLI topography data, yielding restored topographies that show improved agreement with atomic force microscopy measurements. Overall, our integrated BPRA-based ITF measurement and filtering methodology offers a robust yet practical means of characterizing WLI performance and enhancing the accuracy of surface measurements.

Hirose, Shigenobu [Japan Agency for Marine Earth S↗
DOE OSTI2021

Fugitive methane detection using open-path stand-off chirped laser dispersion spectroscopy

We report an open-path chirped laser dispersion spectrometer capable of detecting the atmospheric methane concentration above the background using both specular and diffusive reflective surfaces via two distinct operation modes in a stand-off detection configuration. The system is integrated with simultaneous ranging functionality, which enables average concentration measurements for varying optical pathlengths. The system was first tested for accuracy and characterized to achieve sensitivity of 2.9 p p m - m / H z 1 / 2 and pathlength precision of 0.2 m / H z 1 / 2 with a controlled release of methane outside the laboratory. The instrument was subsequently field-deployed in the proximity of a natural gas compressor station for fugitive methane detection. The instrument successfully detected methane plumes and narrowed down the location of the plume through multi-path measurement. The field measurements were verified by a co-located reference mobile methane sensor.

Chen, Yifeng↗
DOE OSTI2024

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Entropy-Bayesian Inversion of Time-Lapse Tomographic GPR data for Monitoring Dielectric Permittivity and Soil Moisture Variations

In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniqueness and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability distribution functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSim) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes advantage of the spatial-temporal correlation of the state variables. We first apply the inversion framework to a static synthetic example and then to a time-lapse GPR tomographic dataset collected during a dynamic experiment conducted at the Hanford Site in Richland, WA. We demonstrate that the MRE-Bayesian inversion enables us to merge various data types, quantify uncertainty, evaluate nonlinear models, and produce more detailed and better resolved estimates than straight-ray based inversion; therefore, it has the potential to improve estimates of inter-wellbore dielectric permittivity and soil moisture content and to monitor their temporal dynamics more accurately.

58 GEOSCIENCES↗
DOE OSTI2013

Entropy-Bayesian Inversion of Time-Lapse Tomographic GPR data for Monitoring Dielectric Permittivity and Soil Moisture Variations

In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniqueness and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability density functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSIM) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes advantage of the spatial-temporal correlation of the state variables. We first apply the inversion framework to a static synthetic example and then to a time-lapse GPR tomographic dataset collected during a dynamic experiment conducted at the Hanford Site in Richland, WA. We demonstrate that the MRE-Bayesian inversion enables us to merge various data types, quantify uncertainty, evaluate nonlinear models, and produce more detailed and better resolved estimates than straight-ray based inversion; therefore, it has the potential to improve estimates of inter-wellbore dielectric permittivity and soil moisture content and to monitor their temporal dynamics more accurately.

Bayesian Inversion↗
DOE OSTI2013

The Mind Research Network - Mental Illness Neuroscience Discovery Grant

The scientific and technological programs of the Mind Research Network (MRN), reflect DOE missions in basic science and associated instrumentation, computational modeling, and experimental techniques. MRN's technical goals over the course of this project have been to develop and apply integrated, multi-modality functional imaging techniques derived from a decade of DOE-support research and technology development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Fundamental Studies of Recombinant Hydrogenases

This research addressed the long term goals of understanding the assembly and organization of hydrogenase enzymes, of reducing them in size and complexity, of determining structure/function relationships, including energy conservation via charge separation across membranes, and in screening for novel H2 catalysts. A key overall goal of the proposed research was to define and characterize minimal hydrogenases that are produced in high yields and are oxygen-resistant. Remarkably, in spite of decades of research carried out on hydrogenases, it is not possible to readily manipulate or design the enzyme using molecular biology approaches since a recombinant form produced in a suitable host is not available. Such resources are essential if we are to understand what constitutes a “minimal” hydrogenase and design such catalysts with certain properties, such as resistance to oxygen, extreme stability and specificity for a given electron donor. The model system for our studies is Pyrococcus furiosus, a hyperthermophile that grows optimally at 100°C, which contains three different nickel-iron [NiFe-] containing hydrogenases. Hydrogenases I and II are cytoplasmic while the other, MBH, is an integral membrane protein that functions to both evolve H2 and pump protons. Three important breakthroughs were made during the funding period with P. furiosus soluble hydrogenase I (SHI). First, we produced an active recombinant form of SHI in E. coli by the co-expression of sixteen genes using anaerobically-induced promoters. Second, we genetically-engineered P. furiosus to overexpress SHI by an order of magnitude compared to the wild type strain. Third, we generated the first ‘minimal’ form of SHI, one that contained two rather than four subunits. This dimeric form was stable and active, and directly interacted with a pyruvate-oxidizing enzyme with any intermediate electron carrier. The research resulted in five peer-reviewed publications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Materials for Consideration in Standardized Canister Design Activities.

This document identifies materials and material mitigation processes that might be used in new designs for standardized canisters for storage, transportation, and disposal of spent nuclear fuel. It also addresses potential corrosion issues with existing dual-purpose canisters (DPCs) that could be addressed in new canister designs. The major potential corrosion risk during storage is stress corrosion cracking of the weld regions on the 304 SS/316 SS canister shell due to deliquescence of chloride salts on the surface. Two approaches are proposed to alleviate this potential risk. First, the existing canister materials (304 and 316 SS) could be used, but the welds mitigated to relieve residual stresses and/or sensitization. Alternatively, more corrosion-resistant steels such as super-austenitic or duplex stainless steels, could be used. Experimental testing is needed to verify that these alternatives would successfully reduce the risk of stress corrosion cracking during fuel storage. For disposal in a geologic repository, the canister will be enclosed in a corrosion-resistant or corrosion-allowance overpack that will provide barrier capability and mechanical strength. The canister shell will no longer have a barrier function and its containment integrity can be ignored. The basket and neutron absorbers within the canister have the important role of limiting the possibility of post-closure criticality. The time period for corrosion is much longer in the post-closure period, and one major unanswered question is whether the basket materials will corrode slowly enough to maintain structural integrity for at least 10,000 years. Whereas there is extensive literature on stainless steels, this evaluation recommends testing of 304 and 316 SS, and more corrosion-resistant steels such as super-austenitic, duplex, and super-duplex stainless steels, at repository-relevant physical and chemical conditions. Both general and localized corrosion testing methods would be used to establish corrosion rates and component lifetimes. Finally, it is unlikely that the aluminum-based neutron absorber materials that are commonly used in existing DPCs would survive for 10,000 years in disposal environments, because the aluminum will act as a sacrificial anode for the steel. We recommend additional testing of borated and Gd-bearing stainless steels, to establish general and localized corrosion resistance in repository-relevant environmental conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

ATLAS DBM Module Qualification

This is a technical scope of work (TSW) between the Fermi National Accelerator Laboratory (Fermilab) and the experimenters of Jozef Stefan Institute, CERN, and University of Toronto who have committed to participate in beam tests to be carried out during the 2014 Fermilab Test Beam Facility program. Chemical Vapour Deposition (CVD) diamond has a number of properties that make it attractive for high energy physics detector applications. Its large band-gap (5.5 eV) and large displacement energy (42 eV/atom) make it a material that is inherently radiation tolerant with very low leakage currents and high thermal conductivity. CVD diamond is being investigated by the RD42 Collaboration for use very close to LHC interaction regions, where the most extreme radiation conditions are found. This document builds on that work and proposes a highly spatially segmented diamond-based luminosity monitor to complement the time-segmented ATLAS Beam Conditions Monitor (BCM) so that, when Minimum Bias Trigger Scintillators (MTBS) and LUCID (LUminosity measurement using a Cherenkov Integrating Detector) have difficulty functioning, the ATLAS luminosity measurement is not compromised.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Vigilance: A Review of the Literature and Applications to Sentry Duty

Vigilance, or sustained attention, involves the ability to maintain focus and remain alert for prolonged periods of time. Problems associated with the ability to sustain attention were first identified in real-world combat situations during World War II, and they continue to abound and evolve as new and different types of situations requiring vigilance arise. This paper provides a review of the vigilance literature that describes the primary psychophysical, task, environmental, pharmacological, and individual factors that impact vigilance performance. The paper also describes how seminal findings from vigilance research apply specifically to the task of sentry duty. The strengths and weaknesses of a human sentry and options to integrate human and automated functions for vigilance tasks are discussed. Finally, techniques that may improve vigilance performance for sentry duty tasks are identified.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Engineering Bioelectronic Signal Transduction Using the Bacterial Type III Secretion Apparatus

Engineering efficient methods for living systems to transfer electrical energy to non-living systems, at relevant size scales, continues to challenge our knowledge of materials and biology. Our goal was to enable signal transduction between cells and inorganic materials, using controlled electron transport as the energy transfer mechanism. We envision using the cell as a living battery, providing a set of environmental signals to trigger synthetic biological networks that divert intracellular electron transport pathways to inorganic extracellular structures. Conversely, changing electron influxes could guide cellular responses. It is challenging, however, to precisely engineer nanostructured materials to achieve controllable catalytic or electronic properties and connect them with biological energy sources. Our approach to this problem is to engineer protein scaffolds, taking advantage of the native recognition, selectivity and self-assembly properties of these nano-scale building blocks as well as their native intracellular localization patterns. We are using a type III secretion system (T3SS) needle protein from Salmonella enterica, PrgI, as a template for metal nanowire synthesis for biosensing and bioenergy applications. We demonstrate that purified PrgI monomers spontaneously self assemble into long filaments, and that high-affinity peptide tags specific for attachment to functionalized particles can be integrated into the N-terminal region of PrgI. The resulting filaments selectively bind to gold, whether the filaments are assembled in vitro, sheared from cells, or remain attached to live S. enterica cell membranes. Chemical reduction of the gold modified PrgI variants results in structures that are several microns in length and which incorporate a contiguous gold surface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Final Report for FE0032098: Improving the cost-effectiveness of algal CO2 utilization by synergistic integration with power plant and wastewater treatment operations

The overall goal of this project was to demonstrate an engineering-scale open raceway pond algae cultivation system (approximately 180 m²), including the integration of technologies that utilized carbon dioxide (CO₂) from a coal-fired power plant and wastewater-derived nutrient inputs for cost-effective and environmentally friendly biomass production. The key advantages associated with the innovative algae cultivation system and its integration with wastewater treatment functions, as described herein, had been demonstrated in previous bench- and pilot-scale work by the project team partners. This project combined those approaches to maximize practical benefits and available synergies, resulting in a significant reduction in the net cost of producing algal biomass products. The primary target algal species for the project was Spirulina, which served as a high-protein content ingredient for food and animal feed. Spirulina was selected because it had already been approved by the FDA, was in use as a food ingredient, and commanded prices of up to $30/kg. It had a typical protein content of 50–75%, comparable to other high-protein concentrates, featured high digestibility without requiring pretreatment, and offered a high conversion ratio in animal feed applications. In addition, Spirulina had a relatively high content of the blue pigment phycocyanin, which could be extracted as a high-value co-product prior to using the remaining biomass for nutritional purposes.

Schideman, Lance [University of Illinois]↗
DOE OSTI2025

Development of Li–S Battery Cells with High Energy Density and Long Cycling Life

Lithium–sulfur (Li–S) batteries are considered one of the most promising next-generation energy storage technologies for electric vehicles, owing to their high energy density (up to three times greater than current lithium-ion batteries) and the low cost of sulfur (approximately 100 times cheaper than conventional cobalt oxide). However, several challenges hinder their commercial viability, including the electronically and ionically insulating nature of sulfur, polysulfide dissolution, and lithium dendrite growth. These issues significantly limit battery energy density and cycle life and must be addressed to enable successful commercialization. Current strategies involving porous carbon structures, additives, and electrocatalyst engineering have not fully resolved the polysulfide dissolution problem. While polysulfide-free cathode materials offer a promising solution, they often suffer from low sulfur content, leading to reduced discharge capacity and sluggish reaction kinetics. To overcome these limitations, we have developed novel soluble-polysulfide-free sulfur cathode active materials with a high sulfur content (>50 wt%). By integrating these cathodes with functional binders, optimized electrolyte formulations, and refined electrode fabrication techniques, we demonstrate Li–S batteries with both high energy density and long cycle life. This advancement brings the realization of low-cost, high-energy Li–S batteries significantly closer to practical application.

25 ENERGY STORAGE↗