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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

X-ray Transient Absorption Studies of Exciton Self-Trapping

Here, we present optical pump/X-ray absorption probe studies to probe changes in electronic distribution and local structure upon formation of a self-trapped exciton. The experiments were carried out on the mixed-valence halide-bridged transition metal linear chain charge density wave material [Pt(en 2 )][Pt(en 2 )Cl 2 ]·(ClO 4 ) 4 . Photoinduced changes in the Pt L III XANES spectrum were measured on a picosecond time scale following generation of excitons via optical excitation of the intervalence charge transfer transition. Ab initio FEFF9 modeling of the spectra and the associated angular momentum projected density of states was used to interpret the response. We find photoinduced changes reflecting electronic redistribution and local lattice distortions that correspond to strong localization of the self-trapped state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine learning-assisted profiling of a kinked ladder polymer structure using scattering

Ladder polymers consisting of fused rings in the backbone have very limited conformational freedom, which results in very different properties from traditional linear polymers. However, accurately determining their size and chain conformations from solution scattering remains a challenge. Their chain conformations of kinked ladder polymers are largely governed by the structures and relative orientations or configurations of the repeat units, unlike conventional polymer chains whose bending angles between repeat units follow a unimodal Gaussian distribution. Meanwhile, traditional scattering models for polymer chains do not account for these unique structural features. This work introduces a novel approach that integrates machine learning with Monte Carlo simulations to construct a model that can describe the geometry of a type of kinked CANAL ladder polymers. We first develop a Monte Carlo simulation model for sampling the configuration space of CANAL ladder polymers, where each repeat unit is modeled as a biaxial segment. Then, we establish a machine learning-assisted scattering analysis framework based on Gaussian Process Regression. Finally, we conduct small-angle neutron scattering experiments on a CANAL ladder polymer solution to apply our approach. Our method uncovers structural features of such ladder polymers that conventional methods fail to capture.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2020

Localised electromagnetic waves in a rhombic waveguide array with competing nonlinearities

We consider a model of a discrete photonic system representing a quasi-one-dimensional rhombic array of waveguides, where, in addition to the positive cubic nonlinearity, the negative quintic nonlinearity is taken into account for the material of which the central chain of the waveguides is made. The other two waveguide chains are made of an optically linear material. A continual approximation is used to obtain a solution for a system of coupled waves, which describes a wave localised in the transverse direction. In a certain special case, the competition of nonlinearities leads to the formation of a step-shaped distribution of the field intensities over the waveguides. (integrated optics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Dynamics of almost strong edge modes in spin chains away from integrability

Results are presented for the dynamics of an almost strong edge mode which is the quasistable Majorana edge mode occurring in nonintegrable spin chains. The dynamics of the edge mode is studied using exact diagonalization, and compared with time evolution with respect to an effective semi-infinite model in Krylov space obtained from the recursion method. The effective Krylov Hamiltonian is found to resemble a spatially inhomogeneous Su-Schrieffer-Heeger model where the hopping amplitude increases linearly with distance into the bulk, typical of thermalizing systems, but also has a staggered or dimerized structure superimposed on it. Here, the nonperturbatively long lifetime of the edge mode is shown to be due to this staggered structure which diminishes the effectiveness of the linearly growing hopping amplitude. On taking the continuum limit of the Krylov Hamiltonian, the edge mode is found to be equivalent to the quasistable mode of a Dirac Hamiltonian on a half line, with a mass which is nonzero over a finite distance, before terminating into a gapless metallic bulk. The analytic estimates are found to be in good agreement with the numerically obtained lifetimes of the edge mode.

1-dimensional systems↗
DOE OSTI2024

A Simple Comparison of Biochemical Systems Theory and Metabolic Control Analysis

This paper explores some basic concepts of Biochemical Systems Theory (BST) and Metabolic Control Analysis (MCA), two frameworks developed to understand the behavior of biochemical networks. Initially introduced by Savageau, BST focuses on system stability and employs power laws in modeling biochemical systems. On the other hand, MCA, pioneered by authors such as Kacser and Burns and Heinrich and Rapoport, emphasizes linearization of the governing equations and describes relationships (known as theorems) between different measures. Despite apparent differences, both frameworks are shown to be equivalent in many respects. Through a simple example of a linear chain, the paper demonstrates how BST and MCA yield identical results when analyzing steady-state behavior and logarithmic gains within biochemical pathways. This comparative analysis highlights the interchangeability of concepts such as kinetic orders, elasticities and other logarithmic gains.

FOS: Biological sciences↗
DOE OSTI2023

An exploratory steady–state redox model of photosynthetic linear electron transport for use in complete modelling of photosynthesis for broad applications

A photochemical model of photosynthetic electron transport (PET) is needed to integrate photophysics, photochemistry, and biochemistry to determine redox conditions of electron carriers and enzymes for plant stress assessment and mechanistically link sun-induced chlorophyll fluorescence to carbon assimilation for remotely sensing photosynthesis. Towards this goal, we derived photochemical equations governing the states and redox reactions of complexes and electron carriers along the PET chain. These equations allow the redox conditions of the mobile plastoquinone pool and the cytochrome b 6 f complex (Cyt) to be inferred with typical fluorometry. The equations agreed well with fluorometry measurements from diverse C 3 /C 4 species across environments in the relationship between the PET rate and fraction of open photosystem II reaction centres. We found the oxidation of plastoquinol by Cyt is the bottleneck of PET, and genetically improving the oxidation of plastoquinol by Cyt may enhance the efficiency of PET and photosynthesis across species. Redox reactions and photochemical and biochemical interactions are highly redundant in their complex controls of PET. Although individual reaction rate constants cannot be resolved, they appear in parameter groups which can be collectively inferred with fluorometry measurements for broad applications. The new photochemical model developed enables advances in different fronts of photosynthesis research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Targeted metabolomic analysis identifies increased serum levels of GABA and branched chain amino acids in canine diabetes

Introduction Dogs with naturally occurring diabetes mellitus represent a potential model for human type 1 diabetes, yet signifcant knowledge voids exist in terms of the pathogenic mechanisms underlying the canine disorder. Untargeted metabolomic studies from a limited number of diabetic dogs identifed similarities to humans with the disease. Objective To expand and validate earlier metabolomic studies, identify metabolites that difer consistently between diabetic and healthy dogs, and address whether certain metabolites might serve as disease biomarkers. Methods Untargeted metabolomic analysis via liquid chromatography-mass spectrometry was performed on serum from diabetic (n=15) and control (n=15) dogs. Results were combined with those of our previously published studies using identical methods (12 diabetic and 12 control dogs) to identify metabolites consistently diferent between the groups in all 54 dogs. Thirty-two candidate biomarkers were quantifed using targeted metabolomics. Biomarker concentrations were compared between the groups using multiple linear regression (corrected P<0.0051 considered signifcant). Results Untargeted metabolomics identifed multiple persistent diferences in serum metabolites in diabetic dogs compared with previous studies. Therefore, targeted metabolomics showed increases in gamma amino butyric acid, valine, leucine, isoleucine, citramalate, and 2-hydroxyisobutyric acid in diabetic versus control dogs while indoxyl sulfate, N-acetyl-L-aspartic acid, kynurenine, anthranilic acid, tyrosine, glutamine, and tauroursodeoxycholic acid were decreased. Conclusion Several of these fndings parallel metabolomic studies in both human diabetes and other animal models of this disease. Given recent studies on the role of GABA and branched chain amino acids in human diabetes, the increase in serum concentrations in canine diabetes warrants further study of these metabolites as potential biomarkers, and to identify similarity in mechanisms underlying this disease in humans and dogs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in reference two. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized* data are perfect; 2. Normality: The prior and posterior PDF are normal; and 3. Linearity: The model is linear. In this work we outline how the framework in 1 could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in 1 to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implement- ing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS, and the stochastic method, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Superdiffusive transport of energy in one-dimensional metals

Metals in one spatial dimension are described at the lowest energy scales by the Luttinger liquid theory. It is well understood that this free theory, and even interacting integrable models, can support ballistic transport of conserved quantities including energy. In contrast, realistic one-dimensional metals, even without disorder, contain integrability-breaking interactions that are expected to lead to thermalization and conventional diffusive linear response. We argue that the expansion of energy when such a nonintegrable Luttinger liquid is locally heated above its ground state shows superdiffusive behavior (i.e., spreading of energy that is intermediate between diffusion and ballistic propagation), by combining an analytical anomalous diffusion model with numerical matrix-product–state calculations on a specific perturbed spinless fermion chain. Different metals will have different scaling exponents and shapes in their energy spreading, but the superdiffusive behavior is stable and should be visible in time-resolved experiments.

Bulchandani, Vir B.↗
NASA NTRS1993

Automating spectral unmixing of AVIRIS data using convex geometry concepts

Spectral mixture analysis, or unmixing, has proven to be a useful tool in the semi-quantitative interpretation of AVIRIS data. Using a linear mixing model and a set of hypothesized endmember spectra, unmixing seeks to estimate the fractional abundance patterns of the various materials occurring within the imaged area. However, the validity and accuracy of the unmixing rest heavily on the 'user-supplied' set of endmember spectra. Current methods for emdmember determination are the weak link in the unmixing chain.

Boardman, Joseph W.↗
DOE OSTI2024

Sequential Monte Carlo for Cut-Bayesian Posterior Computation

We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We prove finite sample concentration bounds for estimators derived from the proposed method along with a linear tempering extension and apply these results to a realistic setting where a computer model is misspecified. We then illustrate the SMC method for inference in a modular chemical reactor example that includes submodels for reaction kinetics, turbulence, mass transfer, and diffusion. The samples obtained are commensurate with a direct-sampling approach that consists of running multiple Markov chains, with computational efficiency gains using the SMC method. Overall, the SMC method presented yields a novel, rigorous approach to computing with cut-Bayesian posterior distributions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

A new animal model for modulating myosin isoform expression by altered mechanical activity

The purpose of this study was to develop a new rodent model that is capable of delineating the importance of mechanical loading on myosin heavy chain (MHC) isoform expression of the plantar and dorsi flexor muscles of the ankle. The essential components of this system include 1) stimulating electrodes that are chronically implanted into a muscle, allowing for the control of the activation pattern of the target muscle(s); 2) a training apparatus that translates the moment of the ankle into a linear force; and 3) a computer-controlled Cambridge 310 ergometer. The isovelocity profile of the ergometer ensured that the medial gastrocnemius (MG) produced forces that were > 90% of maximal isometric force (Po), and the eccentric contractions of the tibialis anterior (TA) were typically 120% of Po. Both the concentric and eccentric training programs produced statistically significant increases in the muscle mass of the MG (approximately 15%) and TA (approximately 7%) as well as a decrease in myofibrillar adenosinetriphosphatase activity. Both the white and red regions of the MG and TA exhibited significant increases in the relative content of the type IIa MHC and concomitant decreases in type IIb MHC expression. Although the red regions of the MG and red TA contained approximately 10% type I MHC, the training programs did not affect this isoform. It appears that when a fast-twitch muscle is stimulated at a high frequency (100 Hz) and required to contract either concentrically or eccentrically under high loading conditions, the expression of the type IIa MHC isoform will be upregulated, whereas that of the type IIb MHC will be concomitantly downregulated.

NASA Discipline Musculoskeletal↗
DOE OSTI2022

Combustion chemistry of alkenes and alkadienes

Alkenes formed, during the refining of crude oil, by cracking the heavier fractions are present in transportation fuels in significant amounts, up to as much as 15–20% in gasoline. Moreover, alkenes are also the major intermediate products of the oxidation of alkanes, which play a significant role in autoignition chemistry. This review has assessed the recent progress in gas-phase detailed kinetic model development for species with C=C double bond, mostly C2–C10 alkenes and 1,3-butadiene. The compiled knowledge on alkene combustion chemistry enabled a better understanding of the influence of the number and the position of the C=C double bond on the chemical kinetics and hence combustion behavior of alkenes in engines. At first, the article gives an extensive overview of fundamental combustion experiments by considering studies of C2–C10 alkenes and 1,3-butadiene in shock tubes, rapid compression machines, laminar flames, and jet-stirred and flow reactors. The value of the data from such experiments is critically discussed. Secondly, this article highlights the important reaction classes involved in alkene oxidation over low-, intermediate- and high-temperature ranges. Combustion chemistry covering C2 to C10 alkenes, with a special emphasis on C2 to C7 isomers is discussed by presenting a large body of experimental and modeling investigations. Detailed chemistry differences between alkene isomers and also between alkenes and alkanes are also addressed. Thirdly, the article presents important reaction pathways for PAH precursor formation in different alkenes. Finally, a summary of the distinguishing features of alkene combustion chemistry and an outlook towards future research in this area are presented. In conclusion, this review is focused on linear and branched chain alkenes, and the chemistry of cyclo-alkenes is not included.

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

Climate Impact of Primary Plastic Production

Plastics show the strongest production growth of all bulk materials over the last decade. The industry’s current growth trajectory is exponential and plastic production is expected to double or triple by 2050. The rapidly increasing production of plastics and the continued reliance on fossil fuels for production, have contributed to numerous environmental problems and health harms. As a result, plastic pollution has become an increasing threat to natural ecosystems, human health and climate. However, there is a lack of granularity on the contribution of the primary plastics specifically to greenhouse gas (GHG) emissions and their impact on the remaining global carbon budget needed to stay below a 1.5°C or 2°C global average temperature rise. In this report, we explore the contribution of primary plastic production to climate change disaggregated by polymer and technology. To this end, we have developed comprehensive bottom-up modeling of GHG emissions from global primary plastic production, with a special focus on polymer value chains. We have analyzed the results under various growth scenarios in the context of carbon budgets compatible with a 1.5°C global trajectory. Modeling includes the material flows of all production stages, processes and technologies used in primary plastic production value chains, including from the extraction of fossil fuels required for production to shaping the final product. We specifically focus on nine major types of fossil fuelbased plastic polymers that are produced and consumed in large quantities: three types of polyethylene (PE) – low-density (LDPE), linear low-density (LLDPE), and high-density (HDPE) – as well as polypropylene (PP); polyethylene terephthalate (PET); polyvinyl chloride (PVC); polystyrene (PS) and other key styrene-based plastics such as styrene acrylonitrile (SAN) and acrylonitrile butadiene styrene (ABS), and polyurethane (PU). Together these account for about 80% of plastics production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Droplet Deformation in an Extensional Flow: The Role of Surfactant Physical Chemistry

Surfactant-induced Marangoni effects strongly alter the stresses exerted along fluid particle interfaces. In low gravity processes, these stresses can dictate the system behavior. The dependence of Marangoni effects on surfactant physical chemistry is not understood, severely impacting our ability to predict and control fluid particle flows. A droplet in an extensional flow allows the controlled study of stretching and deforming interfaces. The deformations of the drop allow both Marangoni stresses, which resist tangential shear, and Marangoni elasticities, which resist surface dilatation, to develop. This flow presents an ideal model system for studying these effects. Prior surfactant-related work in this flow considered a linear dependence of the surface tension on the surface concentration, valid only at dilute surface concentrations, or a non-linear framework at concentrations sufficiently dilute that the linear approximation was valid. The linear framework becomes inadequate for several reasons. The finite dimensions of surfactant molecules must be taken into account with a model that includes surfaces saturation. Nonideal interactions between adsorbed surfactant molecules alter the partitioning of surfactant between the bulk and the interface, the dynamics of surfactant adsorptive/desorptive exchange, and the sensitivity of the surface tension to adsorbed surfactant. For example, cohesion between hydrocarbon chains favors strong adsorption. Cohesion also slows the rate of desorption from interfaces, and decreases the sensitivity of the surface tension to adsorbed surfactant. Strong cohesive interactions result in first order surface phase changes with a plateau in the surface tension vs surface concentration. Within this surface concentration range, the surface tension is decoupled from surface concentration gradients. We are engaged in the study of the role of surfactant physical chemistry in determining the Marangoni stresses on a drop in an extensional flow in a numerical and experimental program. Using surfactants whose dynamics and equilibrium behavior have been characterized in our laboratory, drop deformation will be studied in ground-based experiment. In an accompanying numerical study, predictive drop deformations will be determined based on the isotherm and equation of state determined in our laboratory. This work will improve our abilities to predict and control all fluid particle flows.

Stebe, Kathleen J.↗
NASA NTRS1993

Analysis of rocket beacon transmissions for computerized reconstruction of ionospheric densities

Three methods are described to obtain ionospheric electron densities from transionospheric, rocket-beacon TEC data. First, when the line-of-sight from a ground receiver to the rocket beacon is tangent to the flight trajectory, the electron concentration can be obtained by differentiating the TEC with respect to the distance to the rocket. A similar method may be used to obtain the electron-density profile if the layer is horizontally stratified. Second, TEC data obtained during chemical release experiments may be interpreted with the aid of physical models of the disturbed ionosphere to yield spatial maps of the modified regions. Third, computerized tomography (CT) can be used to analyze TEC data obtained along a chain of ground-based receivers aligned along the plane of the rocket trajectory. CT analysis of TEC data is used to reconstruct a 2D image of a simulated equatorial plume. TEC data is computed for a linear chain of nine receivers with adjacent spacings of either 100 or 200 km. The simulation data are analyzed to provide an F region reconstruction on a grid with 15 x 15 km pixels. Ionospheric rocket tomography may also be applied to rocket-assisted measurements of amplitude and phase scintillations and airglow intensities.

Bernhardt, P. A.↗
NASA NTRS1994

A computational approach to the relationship between radiation induced double strand breaks and translocations

A theoretical framework is presented which provides a quantitative analysis of radiation induced translocations between the ab1 oncogene on CH9q34 and a breakpoint cluster region, bcr, on CH 22q11. Such translocations are associated frequently with chronic myelogenous leukemia. The theory is based on the assumption that incorrect or unfaithful rejoining of initial double strand breaks produced concurrently within the 200 kbp intron region upstream of the second abl exon, and the 16.5 kbp region between bcr exon 2 and exon 6 interact with each other, resulting in a fusion gene. for an x-ray dose of 100 Gy, there is good agreement between the theoretical estimate and the one available experimental result. The theory has been extended to provide dose response curves for these types of translocations. These curves are quadratic at low doses and become linear at high doses.

NASA Discipline Radiation Health↗
DOE OSTI2024

Climate Impact of Primary Plastic Production

Plastics show the strongest production growth of all bulk materials over the last decade. The industry’s current growth trajectory is exponential and plastic production is expected to double or triple by 2050. The rapidly increasing production of plastics and the continued reliance on fossil fuels for production, have contributed to numerous environmental problems and health harms. As a result, plastic pollution has become an increasing threat to natural ecosystems, human health and climate. However, there is a lack of granularity on the contribution of the primary plastics specifically to greenhouse gas (GHG) emissions and their impact on the remaining global carbon budget needed to stay below a 1.5°C or 2°C global average temperature rise. In this report, we explore the contribution of primary plastic production to climate change disaggregated by polymer and technology. To this end, we have developed comprehensive bottom-up modeling of GHG emissions from global primary plastic production, with a special focus on polymer value chains. We have analyzed the results under various growth scenarios in the context of carbon budgets compatible with a 1.5°C global trajectory. Modeling includes the material flows of all production stages, processes and technologies used in primary plastic production value chains, including from the extraction of fossil fuels required for production to shaping the final product. We specifically focus on nine major types of fossil fuel-based plastic polymers that are produced and consumed in large quantities: three types of polyethylene (PE) – low-density (LDPE), linear low-density (LLDPE), and high-density (HDPE) – as well as polypropylene (PP); polyethylene terephthalate (PET); polyvinyl chloride (PVC); polystyrene (PS) and other key styrene-based plastics such as styrene acrylonitrile (SAN) and acrylonitrile butadiene styrene (ABS), and polyurethane (PU). Together these account for about 80% of plastics production.

54 ENVIRONMENTAL SCIENCES↗