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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Patterson function as auto-hologram and graph enables the direct solution to the phase problem for coherently illuminated atomistic structures

Abstract The coherent Patterson function, derived from the coherent scattering intensities from N atoms, can be described as an auto-holographic image, i.e., the superposition of N -holographic images in which each atom serves as the source of a different reference wave, and as a mathematical graph of the unknown structure. These insights indicate that the unknown structure is significantly over-determined by the inherent information content in a Patterson function by a factor of ( N − 1)/2 (for non-degenerate structures), independent of dimensionality. However, we also show that the ability to resolve the distinct features in the Patterson function depends strongly on details of the experimental design (data range, sampling frequency, and dimensionality). This re-interpretation suggests that the coherent Patterson function provides a natural context for describing the information content in coherent scattering, reveals that there is no inherent phase problem for coherently illuminated pointwise structures, and enables the design of an algorithm which retrieves the structure directly from the Patterson function, without using error metric minimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Quantifying Model Form Uncertainty of Epidemic Forecasting Models from Incidence Data

Objective We present a mathematical framework for non-parametric estimation of the force of infection, together with statistical upper and lower confidence bands. The resulting estimates allow to assess how well simpler models, such as SEIR, fit the observed time series of incidence data.IntroductionUncertainty Quantification (UQ), the ability to quantify the impact of sample-to-sample variations and model misspecification on predictions and forecasts, is a critical aspect of disease surveillance. While quantifying the impact of stochastic uncertainty in the data is well understood, quantifying the impact of model misspecification is significantly harder. For the latter, one needs a "universal model" to which more restrictive parametric models are compared too.MethodsThis talk presents a useful modeling framework for time series of incidence data from contagious diseases that enables one to identify and quantify the impact of model form uncertainty. Specifically, we propose to focus on estimating the timedependent force of infection. The latter is a universal parameters for all contagious disease model. Using a machine learning technique for estimating monotone functions, i.e., isotonic regression and its variants, one can estimate the force ofinfection without addtional assumptions. We note that most contagious disease model do satisfy this monotonicity assumption, due to a combination of factors: depletion of susceptibles, implementation of mitigation strategies, behavior change, etc. Comparing the resulting "non-parametric" estimate with parametric estimates, obtained by fitting an SEIR for example, can reveal model deficiencies and help quantify model form uncertainties.Finally, we discuss how ideas from "strict bound theory" can be used to develop upper and lower uncertainty bands for force of infection that acknowledge the intrinsic stochasticity in the data.ResultsWe demonstrate the application of the methodology to weekly Influenza Like Illness (ILI) incidence data from France andcompare the results to fitted SIR and SEIR models. This comparison can be seen as a nonparametric goodness of fit test, providing one with tools to do simple model selection.ConclusionsWe present a novel and flexible model to statistically describe the force of infection as a function of time. Comparing the fit to incidence data of that model with the fit of simpler parametric models enables the quantification of model form uncertainty and associated model selection.

Hengartner, Nicholas↗
DOE OSTI2023

Linguistic variation in functional types of statutory law

When the meaning of an ambiguous word, phrase or grammatical structure in a statutory provision is disputed, courts are tasked with identifying the best meaning of the contested language. A common method of resolving linguistic ambiguities is to investigate the meaning of the contested word or structure in statutory provisions with similar subject matter. While the subject matter of a text has a demonstrated effect on language use, register variation research shows that the function of a text is also highly influential in predicting linguistic variation. Thus far, the function of a statutory provision (e.g., obligation to act, authorization to act) has not been considered in legal interpretative research. In the present study, I investigate the extent to which function influences the lexico-grammatical characteristics of statutory texts. 2,573 statutory provisions from the Arizona State Code are individually assigned to one of seven categories representing their function: Duties, Permissions, Impersonal Rules, Operational Definitions, Prohibitions, Procedural Guidelines, and Criminal Offenses. Key feature analysis is used to identify and describe patterns of lexico-grammatical variation between the seven functional types. Results reveal a great deal of lexico-grammatical variation associated with function in the register of statutory law. Furthermore, some functional types of statutory provisions are more linguistically distinct than others. In conclusion, these findings suggest that it may be beneficial to consider communicative function when investigating legal interpretative questions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid-IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand-canonical density function theory (GC-DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O-coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, in this study, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 -based catalysts for acidic OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Spatial correlation functions of paracrystals with radial symmetry

Here, we develop a phenomenological model to describe the structure of radially symmetric paracrystals whose long-range order are destroyed by propagation of particle fluctuations. General expressions are derived for the spatial correlation functions in one-, two-, and three-dimensional spaces. And the spatial correlation in paracrystals in reciprocal space is further discussed and clarified. The developed method can be used to quantitatively analyze the microstructure of paracrystalline materials in both real and reciprocal spaces via scattering experiments and computer simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anisotropic interactions for continuum modeling of protein–membrane systems

In this work, a model for anisotropic interactions between proteins and cellular membranes is proposed for large-scale continuum simulations. The framework of the model is based on dynamic density functional theory, which provides a formalism to describe the lipid densities within the membrane as continuum fields while still maintaining the fidelity of the underlying molecular interactions. Within this framework, we extend recent results to include the anisotropic effects of protein–lipid interactions. As applications, we consider two membrane proteins of biological interest: a RAS–RAF complex tethered to the membrane and a membrane embedded G protein-coupled receptor. A strong qualitative and quantitative agreement is found between the numerical results and the corresponding molecular dynamics simulations. Combining the scope of continuum level simulations with the details from molecular level particle simulations enables research into protein–membrane behaviors at a more biologically relevant scale, which crucially can also be accessed via experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100°C to 300°C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels - 19294

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100 deg. C to 300 deg. C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles. (authors)

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

The Curie–Weiss model with Complex Temperature: Phase Transitions

We study the partition function of the Curie–Weiss model with complex temperature, and partially describe its phase transitions. As a consequence, we obtain information on the locations of zeros of the partition function (the Fisher zeros).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Reduction of Stored NOx with CO/H2 and Hydrocarbons: A Spatial Resolution Analysis

Lean NOx traps (LNT) are multi-function multi-component catalysts which operate in an integral and transient reactor mode to reduce NOx in the exhaust from diesel or lean-burn gasoline engines. This chapter addresses the regeneration phase of the LNT operation, discussing various types of reductants and reactions involved. We describe how reductants of different reactivity influence catalyst functions, reactions, and overall regeneration efficiency. The presented examples highlight the importance of understanding the spatial and temporal development of key reactions and their interplay to rationalize the global performance of practical LNTs which are generally honeycomb-shaped ceramic monoliths. The emphasis is on explaining global NOx removal performance (i.e., activity and selectivity) based on the insights gained through spatially resolved techniques, including initial distribution and redistribution of stored NOx; oxygen storage and reduction; transformation of feed reductants; and formation and utilization of reduction intermediates. Pathways leading to N2O and NH3 byproduct formation as well as mitigation strategies are also discussed.

Choi, Jae-Soon↗
DOE OSTI2024

Parametric description of intermittent probability distribution functions in solar wind and magnetohydrodynamic turbulence

ABSTRACT In this work, we find empirical evidence that the scale-dependent statistical properties of solar wind and magnetohydrodynamic (MHD) turbulence can be described in terms of a family of parametric probability distribution functions (PDFs) known as Normal Inverse Gaussian (NIG). Understanding these PDFs is one of the most important goals in turbulence theory, as they are inherently connected to the intermittent properties of solar wind turbulence. We investigate the properties of PDFs of Elsasser increments based on a large statistical sample from solar wind observations and high-resolution numerical simulations of MHD turbulence. In order to measure the PDFs and their corresponding properties, three experiments are presented: fast and slow solar wind for experimental data and a simulation of reduced MHD (RMHD) turbulence. Conditional statistics on a 23-yr-long sample of WIND data near 1 au and high-resolution pseudo-spectral simulation of steadily driven RMHD turbulence on a $2048^3$ mesh are used to construct scale-dependent PDFs. The empirical PDFs are fitted to NIG distributions, which depend on four free parameters. Our analysis shows that NIG distributions accurately capture the evolution of the PDFs, with scale-dependent parameters, from large scales characterized by a Gaussian distribution, turning to exponential tails within the inertial range and stretched exponentials at dissipative scales. We also show that empirically-measured NIG parameters exhibit well-defined scaling properties that are similar across the three empirical data sets, which may be indicative of universal behaviour.

Astronomy & Astrophysics↗
DOE OSTI2022

Photoresponsive Azobenzene-Functionalized Shell Cross-Linked Micelles for Selective Asymmetric Transfer Hydrogenation

We describe the substrate-selective asymmetric transfer hydrogenation of aromatic ketones using rhodium complexes immobilized on a photoresponsive nanoreactor. The nanoreactor is based on multifunctional amphiphilic poly(2-oxazoline)s that are covalently cross-linked with functionalized azobenzene after micelle formation in water. The nanoreactor switches its morphology upon light irradiation in a wavelength-selective manner as confirmed by dynamic light scattering. Kinetic studies show that the gated behavior induced by the phototriggered reversible isomerization of trans- azobenzene to cis- azobenzene in the cross-linking layer is key to discriminate among substrates and reagents during catalysis. Under UV light irradiation, the diffusion of larger substrates into the core is slower in comparison to smaller substrates. The nanoreactor displays substrate selectivity, converting smaller ketone-substrates faster to the corresponding secondary alcohols.

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

The N-terminal domains of NLR immune receptors exhibit structural and functional similarities across divergent plant lineages

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins are a prominent class of intracellular immune receptors in plants. However, our understanding of plant NLR structure and function is limited to the evolutionarily young flowering plant clade. Here, we describe an extended spectrum of NLR diversity across divergent plant lineages and demonstrate the structural and functional similarities of N-terminal domains that trigger immune responses. We show that the broadly distributed coiled-coil (CC) and toll/interleukin-1 receptor (TIR) domain families of nonflowering plants retain immune-related functions through translineage activation of cell death in the angiosperm Nicotiana benthamiana. We further examined a CC subfamily specific to nonflowering lineages and uncovered an essential N-terminal MAEPL motif that is functionally comparable with motifs in resistosome-forming CC-NLRs. Consistent with a conserved role in immunity, the ectopic activation of CC MAEPL in the nonflowering liverwort Marchantia polymorpha led to profound growth inhibition, defense gene activation, and signatures of cell death. Moreover, comparative transcriptomic analyses of CC MAEPL activity delineated a common CC-mediated immune program shared across evolutionarily divergent nonflowering and flowering plants. Collectively, our findings highlight the ancestral nature of NLR-mediated immunity during plant evolution that dates its origin to at least ~500 million years ago.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Beyond sequence similarity: toward function-based screening of nucleic acid synthesis

Synthetic nucleic acids are a key input to modern biotechnology, yet they represent dual-use materials that require robust screening to mitigate biosecurity risks. The prevailing screening paradigm, which identifies sequences of concern (SoCs) through sequence similarity to controlled pathogens and toxins, may not fully capture risks posed by AI tools that can decouple biomolecular function from reliance on known sequences. Rapidly advancing biodesign capabilities enable the generation of genes and proteins that might evade sequence-based detection. We highlight the critical need for function-based screening approaches that can detect sequences capable of hazardous biological functions, regardless of similarity to known SoCs. We examine the feasibility of function-based screening with an initial focus on proteins, arguing that, while protein sequence space is vast, biologically functional proteins are significantly constrained by biophysical and biochemical requirements that can be learned and modeled. We propose a concrete implementation framework organized along a continuum of complexity, starting with toxins as the most tractable targets before expanding to more complex pathogenic functions. We then discuss open challenges and describe a research and development strategy to address them.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Integrated system failure analysis software toolchain (IS-FAST)

Systems and methods are provided for generating faults and analyzing fault propagation and its effects. Starting from the ontologies of components, functions, flows, and faults, systems and methods are provided that describe, generate and track faults in a computer system across multiple domains throughout design and/or development. In order to construct the system and fault models, a series of concepts is introduced in the form of ontologies and their dependencies. An investigation is performed into the faults, including their type, cause, life-cycle aspects, and effect. Principles and rules are created to generate various faults based on system configurations. After the modeling process, a simulation engine is described to execute actions and simulate the process of fault generation and propagation. As a result, fault paths that impact components and functions can be obtained.

Diao, Xiaoxu↗
DOE OSTI2023

Targeting Aspergillus allergen oryzin with a chemical probe at atomic precision

We report the molecular basis of Aspergillus fumigatus oryzin, allergen Asp f 13, or alkaline proteinase ALP1, containing the sequence motif His–Asp–Ser of the subtilisin family, structure, and function at atomic detail. Given the resolution of the data (1.06 Å), we use fragment molecular replacement with ideal polyalanine α-helices to determine the first crystal structure of oryzin. We probe the catalytic serine through formation of an irreversible bond to a small molecule compound, specifically labeling it, describing the amino acid residues performing the catalytic function. Defined by a self-processed pro-peptide, the active site architecture shapes up pocket-like subsites that bind to and unveil the S1′–S4′ substrate binding preferences. We use molecular modeling to dock a model of the pro-peptide in the S1–S4 region and to dock collagen along the active site cleft. Opposite to the face harboring the catalytic serine, the enzyme binds to a calcium ion in a binding site created by backbone flipping. We use thermal unfolding to show that this metal ion provides structural stability. With no known host inhibitor identified thus far, this structure may hasten the progress of developing new therapeutic agents for diseases caused by pathogenic fungi.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Third Quantization and Emergence of the Quasiclassical Wave Function of the Universe

Quantized solutions of the Wheeler–DeWitt (WDW) equation describing a closed Friedmann–Robertson–Walker universe with a Λ term and a set of massless scalar fields are studied. It is shown that when Λ≪1 units and the standard in-vacuum state is considered, the wave function of the universe Ψ behaves as a random quasiclassical field at rather large a, namely, 1≪a≪e{sup (2/(3Λ))} [1].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Addressing Function Allocation for the Digital Transformation of Existing Nuclear Power Plants

The existing nuclear power plants in the United States (U.S.) have a vital role in providing carbon-free electricity. For the existing nuclear power plant fleet to remain economically viable, a significant digital transformation that fundamentally changes the way in which these plants are operated, maintained, and supported ought to be seriously considered. Safe and reliable automation is needed. This work describes important considerations and challenges that come with function allocation for the adoption of new automation at existing nuclear power plants. Specifically, this work reviews the state-of-the-art in function allocation guidance and highlights how it can be used within the U.S. nuclear industry. An objective of this work is to present the current challenges and proposed approaches to the human factors community to support future research and development that ultimately supports the effective use of function allocation in the digital transformation of existing nuclear power plants.

99 GENERAL AND MISCELLANEOUS↗