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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Identification of protein/mRNA network involving the PSORS1 locus gene CCHCR1 and the PSORS4 locus gene HAX1

Highlights: • CCHCR1 and HAX1 proteins directly interact. • CCHCR1 is a psoriasis candidate gene located on PSORS1 locus. • HAX1 gene is located on PSORS4 locus and is overexpressed in psoriasis. • CCHCR1 and HAX1 co-localize with and affect specific mRNAs in vesicles. • Novel protein/mRNA networks involving CCHCR1 and HAX1 could play a role in psoriasis. CCHCR1 (Coiled-Coil alpha-Helical Rod 1), maps to chromosomal region 6p21.3, within the major psoriasis susceptibility locus PSORS1. CCHCR1 itself is a plausible psoriasis candidate gene, however its role in psoriasis pathogenesis remains unclear. We previously demonstrated that CCHCR1 protein acts as a cytoplasmic docking site for RNA polymerase II core subunit 3 (RPB3) in cycling cells, suggesting a role for CCHCR1 in vesicular trafficking between cellular compartments. Here, we report a novel interaction between CCHCR1 and the RNA binding protein HAX1. HAX1 maps to chromosomal region 1q21.3 within the PSORS4 locus and is over-expressed in psoriasis. Both CCHCR1 and HAX1 share subcellular co-localization with mitochondria, nuclei and cytoplasmic vesicles as P-bodies. By a series of ribonucleoprotein immunoprecipitation (RIP) assays, we isolated a pool of mRNAs complexed with HAX1 and/or CCHCR1 proteins. Among the mRNAs complexed with both CCHCR1 and HAX1 proteins, there are Vimentin mRNA, previously described to be bound by HAX1, and CAMP/LL37 mRNA, whose gene product is over-expressed in psoriasis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Carboxylated Fullerene at the Oil/Water Interface

The self-assembly of carboxylated fullerene with poly(styrene-b-2-vinylpyridine) (PS-b-P2VP) with different molecular weights, poly-2-vinylpyridine, and amine-terminated polystyrene, at the interface between toluene and water was investigated. For all values of the pH, the functionalized fullerene interacted with the polymers at the water/toluene interface, forming a nanoparticle network, reducing the interfacial tension. At pH values of 4.84 and 7.8, robust, elastic films were formed at the interface, such that hollow tubules could be formed in situ when an aqueous solution of the functionalized fullerene was jetted into a toluene solution of PS-b-P2VP at a pH of 4.84. Lastly, with variation of the pH, the mechanical properties of the fullerene/polymer assemblies can be varied by tuning the strength of the interactions between the functionalized fullerenes and the PS-b-P2VP.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Cross-section Effects in the Super-Kamiokande Tau Appearance Analysis

In this talk, I explain the search for tau neutrino appearance in the atmospheric neutrino flux at Super-Kamiokande with a particular emphasis on the effect deep inelastic cross section uncertainties have on interpreting the result. In particular, I explain why the normalization of the DIS cross-section also needs to be treated as a parameter in the fit of tau normalization, and show how a neural net based on event parameters can separate various cross-section modes in the background sample.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Breeding of microbiomes conferring salt tolerance to plants

Microbiome breeding through host-mediated selection is a technique to artificially select for microbiomes conferring beneficial properties to plants. Using a systematic selection protocol that maximises the heritability of microbiome effects, transmission fidelity, and microbiome stability through multiple selection cycles, we previously developed root-associated microbial communities conferring sodium and aluminium tolerance to Brachypodium distachyon, a model for cereal crops. Here, we explore the physiological mechanisms underlying our selected microbiomes’ effect on plant fitness and analyse how our selection protocol shaped the composition and structure of these microbiomes. We analysed the effects of our selected microbiomes on plant fitness and tissue-nutrient concentration, then used 16S rRNA amplicon sequencing to examine microbial community composition and co-occurrence network patterns. Our sodium-selected microbiomes reduced leaf sodium concentration by ~ 50%, whereas the aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying the microbiome-mediated stress tolerance. By testing the selected microbiomes in a cross-fostering experiment, we show that our artificially selected microbiomes attained (a) ecological robustness contributing to transplantability (i.e. inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting salt-stress tolerance. Combined, these findings elucidate critical mechanisms underlying host-mediated artificial selection as a framework to breed microbiomes with targeted benefits for plants under salt stresses, with significant implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Vimentin intermediate filaments function as a physical barrier during intracellular trafficking of caveolin-1

Highlights: • Vimentin intermediate filaments interact with caveolin-1. • In cytoplasm, where there is pronounced vimentin network, there is less caveolin-1 positive vesicles. • Caveolin-1 positive vesicles show less mobility in vimentin-enriched area. • Vimentin depletion do not affect the protein expression levels of caveolae components. • Vimentin depletion affects the mobility distribution of the cytoplasmic caveolin-1. Both the cytoskeletal intermediate filaments (IFs) and cytoplasmic caveolae contribute to active processes such as cell migration, morphogenesis and vesicular trafficking, but the interplay between these two systems has remained elusive. Here, we find that vimentin and nestin IFs interact with caveolae central component caveolin-1 (CAV-1) and importantly, restrain the intracellular trafficking of CAV-1 positive vesicles by serving as a physical barrier. Consequently, CAV-1 vesicles show less density and mobility in vimentin IFs enriched region, which is a substrate stiffness independent process. Moreover, depletion of vimentin IFs releases the slow movement proportion of CAV-1 positive vesicles and thus increases their cytoplasmic dynamics, whereas the expression of caveolae-associated protein CAV-1, CAV-2 and cavin-1 were unaffected. Collectively, these results reveal a negative role of IFs in regulating the trafficking of intracellular CAV-1 vesicles in live cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A Multicomponent Blend as a Diesel Fuel Surrogate for Compression Ignition Engine Applications

A mixture of n-dodecane and m-xylene is investigated as a diesel fuel surrogate for compression ignition engine applications. Compared to neat n-dodecane, this binary mixture is more representative of diesel fuel because it contains an alkyl-benzene which represents an important chemical class present in diesel fuels. A detailed multi-component mechanism for n-dodecane and m-xylene was developed by combining a previously developed n-dodecane mechanism with a recently developed mechanism for xylenes. The xylene mechanism is shown to reproduce experimental ignition data from a rapid compression machine and shock tube, speciation data from the jet stirred reactor and flame speed data. This combined mechanism was validated by comparing predictions from the model with experimental data for ignition in shock tubes and for reactivity in a flow reactor. The combined mechanism, consisting of 2885 species and 11754 reactions, was reduced to a skeletal mechanism consisting 163 species and 887 reactions for 3D diesel engine simulations. The mechanism reduction was performed using directed relation graph (DRG) with expert knowledge (DRG-X) and DRG-aided sensitivity analysis (DRGASA) at a fixed fuel composition of 77% of n-dodecane and 23% m-xylene by volume. The sample space for the reduction covered pressure of 1 – 80 bar, equivalence ratio of 0.5 – 2.0, and initial temperature of 700 – 1600 K for ignition. The skeletal mechanism was compared with the detailed mechanism for ignition and flow reactor predictions. Finally, the skeletal mechanism was validated against a spray flame dataset under diesel engine conditions documented on the Engine Combustion Network (ECN) website. These multidimensional simulations were performed using a Representative Interactive Flame (RIF) turbulent combustion model. In conclusion, encouraging results were obtained compared to the experiments with regards to the predictions of ignition delay and lift-off length at different ambient temperatures.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Realization of two-dimensional discrete time crystals with anisotropic Heisenberg coupling

A discrete time crystal (DTC) is an out-of-equilibrium phase of matter that spontaneously breaks discrete time-translation symmetry. Previous studies have been limited to a set of models with Ising-like couplings - and mostly only in one dimension - thus precluding our understanding of the existence (or not) of DTCs in models with more realistic interactions. In this work, by combining the latest generation of IBM quantum processors with state-of-the-art tensor network methods, we demonstrate the existence of a DTC in a two-dimensional system governed by anisotropic Heisenberg interactions. We uncover a rich phase diagram encompassing spin-glass, ergodic, and time-crystalline phases, and identify the interplay of initialization, interaction anisotropy, and driving protocols in stabilizing the DTC phase. By extending the study of Floquet matter beyond simplified models, we lay the groundwork for exploring how driven systems bridge the gap between quantum coherence and emergent non-equilibrium thermodynamics.

Phase transitions and critical phenomena↗
DOE OSTI2014

Secure control systems with application to cyber-physical systems

Control systems are computer-based systems with networked units consisting of sensors, actuators, control processing units, and communication devices. The role of control system is to interact, monitor, and control physical processes. Reactive power control is a fundamental issue in ensuring the security of the power network. It is claimed that Synchronous Condensers (SC) have been used at both distribution and transmission voltage levels to improve stability and to maintain voltages within desired limits under changing load conditions and contingency situations. Performance of PI controller corresponding to various tripping faults are analyzed for SC systems. Most of the eort in protecting these systems has been in protection against random failures or reliability. However, besides failures these systems are subject to various signal attacks for which new analysis are discussed here. When a breach does occur, it is necessary to react in a time commensurate with the physical dynamics of the system as it responds to the attack. Failure to act swiftly enough may result in undesirable, and possibly irreversible, physical eects. Therefore, it is meaningful to evaluate the security of a cyber-physical system, especially to protect it from cyber-attack. Illustrative numerical examples are provided together with an application to the SC systems.

Dong, Jin↗
DOE OSTI2022

The molecular mechanism of load adaptation by branched actin networks

Branched actin networks are self-assembling molecular motors that move biological membranes and drive many important cellular processes, including phagocytosis, endocytosis, and pseudopod protrusion. When confronted with opposing forces, the growth rate of these networks slows and their density increases, but the stoichiometry of key components does not change. The molecular mechanisms governing this force response are not well understood, so we used single-molecule imaging and AFM cantilever deflection to measure how applied forces affect each step in branched actin network assembly. Although load forces are observed to increase the density of growing filaments, we find that they actually decrease the rate of filament nucleation due to inhibitory interactions between actin filament ends and nucleation promoting factors. The force-induced increase in network density turns out to result from an exponential drop in the rate constant that governs filament capping. The force dependence of filament capping matches that of filament elongation and can be explained by expanding Brownian Ratchet theory to cover both processes. We tested a key prediction of this expanded theory by measuring the force-dependent activity of engineered capping protein variants and found that increasing the size of the capping protein increases its sensitivity to applied forces. In summary, we find that Brownian Ratchets underlie not only the ability of growing actin filaments to generate force but also the ability of branched actin networks to adapt their architecture to changing loads.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need to capture uncertainty and risk using appropriate probabilistic, statistical and optimization concepts. The main difficulty arising in addressing these issues is the dramatic increase in the computational complexity of the resulting optimization problems. This project studied novel models and methodologies for risk-averse network optimization- specifically, network design, network flows and cluster detection problems under uncertainty. The approach taken was to incorporate a quantitative risk measure known as conditional value-at-risk that is widely used in financial applications. This approach presents a viable alternate modeling and optimization framework to chance-constrained optimization and mean-variance optimization, one that also facilitates the detection of risk-averse solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

A Line Weighted Frequency Droop Controller for Decentralized Enforcement of Transmission Line Power Flow Constraints in Inverter-Based Networks

Recent works have shown that networks of voltagesource inverters implementing frequency droop control may be analyzed as consensus-like networks. Based on this understanding, we show that enforcement of network line power flows can be viewed as an edge-preservation problem in a -disk dynamic interaction graph. Inspired by other works solving similar problems in other domains, we propose a line weighted frequency droop controller such that a network of all active buses implementing this controller enforces the specified line power flow constraints without need for communication. We provide simulation results verifying that our proposed controller limits line power to enforce constraints, and otherwise acts as a traditional droop controller.

Distributed control↗
DOE OSTI2026

Solvent Reorganization and Surface–Species Interactions Control Transfer Hydrogenation Rates in Sn-Beta Zeolites

Reorganization of confined alcohol networks reshapes adsorption and activation thermodynamics in Lewis acid zeolites, yet the roles of adsorbate sterics and non-H-bonding cosolvents remain unclear. Here, we investigate transfer hydrogenation of methyl- (mCH) and tert-butylcyclohexanone (tbCH) with 2-butanol over hydrophobic Sn-Beta. First-order rates per defect-open Sn site are 2–5× higher for mCH than tbCH, but converge in the zero-order regime (333–393 K), indicating that solvent reorganization entropically drives adsorption, while bond activation is insensitive to ketone structure. Reactions in toluene or acetonitrile (with 1 M 2-butanol) show that intraporous solvent organization governs transition-state stabilization: on hydrophobic Sn-Beta, apparent enthalpies and entropies rise with decreasing solvent polarity, whereas hydrophilic zeolites display nearly constant barriers across solvents. Liquid-phase IR spectroscopy corroborates these trends, showing that hydrophilic pores enforce 2-butanol-like solvation environments even in toluene. Together, these results reveal how zeolite pores regulate the intraporous solvent structure, whose reorganization upon adsorption reshapes the thermodynamic landscape of Lewis acid catalysis

Adsorption↗
DOE OSTI2020

ECP Report: Update on Proxy Applications and Vendor Interactions

The ExaLearn miniGAN team (Ellis and Rajamanickam) have released miniGAN, a generative adversarial network(GAN) proxy application, through the ECP proxy application suite. miniGAN is the first machine learning proxy application in the suite (note: the ECP CANDLE project did previously release some benchmarks) and models the performance for training generator and discriminator networks. The GAN's generator and discriminator generate plausible 2D/3D maps and identify fake maps, respectively. miniGAN aims to be a proxy application for related applications in cosmology (CosmoFlow, ExaGAN) and wind energy (ExaWind). miniGAN has been developed so that optimized mathematical kernels (e.g., kernels provided by Kokkos Kernels) can be plugged into to the proxy application to explore potential performance improvements. miniGAN has been released as open source software and is available through the ECP proxy application website (https://proxyapps.exascaleproject.ordecp-proxy-appssuite/) and on GitHub (https://github.com/SandiaMLMiniApps/miniGAN). As part of this release, a generator is provided to generate a data set (series of images) that are inputs to the proxy application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Universal quantum computation with ordered spin-chain networks

It is shown that anisotropic spin chains with gapped bulk excitations and magnetically ordered ground states offer a promising platform for quantum computation, which bridges the conventional single-spin-based qubit concept with recently developed topological Majorana-based proposals. We show how to realize the single-qubit Hadamard, phase, and {pi}/8 gates as well as the two-qubit controlled-not (cnot) gate, which together form a fault-tolerant universal set of quantum gates. The gates are implemented by judiciously controlling Ising exchange and magnetic fields along a network of spin chains, with each individual qubit furnished by a spin-chain segment. A subset of single-qubit operations is geometric in nature, relying on control of anisotropy of spin interactions rather than their strength. We contrast topological aspects of the anisotropic spin-chain networks to those of p-wave superconducting wires discussed in the literature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2020

Genetic Algorithm for Optimization of Neural Networks for Bayesian Inference of Model Uncertainty

The objective of this work was to develop a genetic optimization algorithm that can design a neural network capable of producing uncertainty estimates along with predictions. This algorithm is necessary because the inclusion of uncertainty modeling in a neural network greatly complicates the network’s design space, making the development of a converging model extremely difficult and time consuming. The genetic algorithm presented in this work uses a number of value ranges for various configurable neural network parameters to create a randomly generated population of network architectures. The initially generated population is then evolved over the course of several generations, with the best performing models breeding to produce novel network configurations. Mutations are randomly applied to the network designs to facilitate the development of adaptations beneficial to the task being performed. An experiment was conducted to validate the proposed algorithm, in which the genetic optimizer was tasked with producing a neural network capable of predicting the sound pressure level (SPL) resulting from jet-surface interaction (JSI) noise. The data used for this task was generated at the NASA Glenn Research Center in the Aero-Acoustic Propulsion Laboratory. Starting with an initial population size of 35 randomly generated networks, and evolved over the course of 10 generations, the genetic algorithm produced a design able to predict SPL as a result of JSI noise within 0.272 dB, on average.

Genetic algorithm↗
DOE OSTI2012

MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. We have developed a semi-automatic, web-based platform (MicrobesFlux) for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites) of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes) and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported in the SBML format (The Systems Biology Markup Language). Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions) for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG database. Our system facilitates users to reconstruct metabolic networks of organisms based on experimental information. Through human-computer interaction, MicrobesFlux provides users with reasonable predictions of microbial metabolism via flux balance analysis. This prototype platform can be a springboard for advanced and broad-scope modeling of complex biological systems by integrating other “omics” data or 13 C- metabolic flux analysis results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Gas transport characteristics of supramolecular networks of metal-coordinated highly branched Poly(ethylene oxide)

Model systems are developed and investigated to better understand the effect of polyether-metal ion interactions on gas separation characteristics. These systems help answer current questions raised by the substantial body of research on metal-organic frameworks (MOFs) dispersed in polyethers to improve gas separation performance, where favorable interactions between the metal centers and polyethers are preferred to improve interfacial compatibility. Specifically, we investigate CO 2 /gas transport properties of supramolecular networks comprising cross-linked poly(ethylene oxide) (XLPEO) and dissociable salts, including LiClO 4 , Ni(BF 4 ) 2 , and Cu(BF 4 ) 2 . Increasing the salt content increases the glass transition temperature (T g ) and generally decreases gas diffusivity and permeability, which can be successfully described using a T g -integrated free volume model with an expression similar to the Vogel-Tammann-Fulcher (VTF) equation. Surprisingly, low loadings of LiClO 4 and Cu(BF 4 ) 2 (2 mass% or less) can increase gas permeability by 30%–70% without affecting the CO 2 /gas selectivity. This increase correlates with polyether-metal ion dynamics as measured by dielectric spectroscopy. Understanding how interaction-mediated dynamics affect gas transport will be instrumental to designing MOF-based mixed matrix materials for gas separations.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Interactive Visual Analysis of High Throughput Text Streams

The scale, velocity, and dynamic nature of large scale social media systems like Twitter demand a new set of visual analytics techniques that support near real-time situational awareness. Social media systems are credited with escalating social protest during recent large scale riots. Virtual communities form rapidly in these online systems, and they occasionally foster violence and unrest which is conveyed in the users language. Techniques for analyzing broad trends over these networks or reconstructing conversations within small groups have been demonstrated in recent years, but state-of- the-art tools are inadequate at supporting near real-time analysis of these high throughput streams of unstructured information. In this paper, we present an adaptive system to discover and interactively explore these virtual networks, as well as detect sentiment, highlight change, and discover spatio- temporal patterns.

sentiment analysis↗