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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

GOATOOLS: A Python library for Gene Ontology analyses

The biological interpretation of gene lists with interesting shared properties, such as up- or downregulation in a particular experiment, is typically accomplished using gene ontology enrichment analysis tools. Given a list of genes, a gene ontology (GO) enrichment analysis may return hundreds of statistically significant GO results in a “fat” list, which can be challenging to summarize. It can also be difficult to keep pace with rapidly expanding biological knowledge, which often results in daily changes to any of the over 47,000 gene ontologies that describe biological knowledge. GOATOOLS, a Python-based library, makes it more efficient to stay current with the latest ontologies and annotations, perform gene ontology enrichment analyses to determine over- and under-represented terms, and organize results for greater clarity and easier interpretation using a novel GOATOOLS GO grouping method. We performed functional analyses on both stochastic simulation data and real data from a published RNA-seq study to compare the enrichment results from GOATOOLS to two other popular tools: DAVID and GOstats. GOATOOLS is freely available through GitHub: https://github.com/ tanghaibao/goatools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Insight into Fluorocarbon Adsorption in Metal-Organic Frameworks via Experiments and Molecular Simulations

Abstract The improvement in adsorption/desorption of hydrofluorocarbons has implications for many heat transformation applications such as cooling, refrigeration, heat pumps, power generation, etc. The lack of chlorine in hydrofluorocarbons minimizes the lasting environmental damage to the ozone, with R134a (1,1,1,2-tetrafluoroethane) being used as the primary industrial alternative to commonly used Freon-12. The efficacy of novel adsorbents used in conjunction with R134a requires a deeper understanding of the host-guest chemical interaction. Metal-organic frameworks (MOFs) represent a newer class of adsorbent materials with significant industrial potential given their high surface area, porosity, stability, and tunability. In this work, we studied two benchmark MOFs, a microporous Ni-MOF-74 and mesoporous Cr-MIL-101. We employed a combined experimental and simulation approach to study the adsorption of R134a to better understand host-guest interactions using equilibrium isotherms, enthalpy of adsorption, Henry’s coefficients, and radial distribution functions. The overall uptake was shown to be exceptionally high for Cr-MIL-101, >140 wt% near saturation while >50 wt% at very low partial pressures. For both MOFs, simulation data suggest that metal sites provide preferable adsorption sites for fluorocarbon based on favorable C-F ··· M + interactions between negatively charged fluorine atoms of R134a and positively charged metal atoms of the MOF framework.

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

A regression algorithm for accelerated lattice QCD that exploits sparse inference on the D-Wave quantum annealer

We propose a regression algorithm that utilizes a learned dictionary optimized for sparse inference on a D-Wave quantum annealer. In this regression algorithm, we concatenate the independent and dependent variables as a combined vector, and encode the high-order correlations between them into a dictionary optimized for sparse reconstruction. On a test dataset, the dependent variable is initialized to its average value and then a sparse reconstruction of the combined vector is obtained in which the dependent variable is typically shifted closer to its true value, as in a standard inpainting or denoising task. Here, a quantum annealer, which can presumably exploit a fully entangled initial state to better explore the complex energy landscape, is used to solve the highly non-convex sparse coding optimization problem. The regression algorithm is demonstrated for a lattice quantum chromodynamics simulation data using a D-Wave 2000Q quantum annealer and good prediction performance is achieved. The regression test is performed using six different values for the number of fully connected logical qubits, between 20 and 64. The scaling results indicate that a larger number of qubits gives better prediction accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Accurate and confident prediction of electron beam longitudinal properties using spectral virtual diagnostics

Abstract Longitudinal phase space (LPS) provides a critical information about electron beam dynamics for various scientific applications. For example, it can give insight into the high-brightness X-ray radiation from a free electron laser. Existing diagnostics are invasive, and often times cannot operate at the required resolution. In this work we present a machine learning-based Virtual Diagnostic (VD) tool to accurately predict the LPS for every shot using spectral information collected non-destructively from the radiation of relativistic electron beam. We demonstrate the tool’s accuracy for three different case studies with experimental or simulated data. For each case, we introduce a method to increase the confidence in the VD tool. We anticipate that spectral VD would improve the setup and understanding of experimental configurations at DOE’s user facilities as well as data sorting and analysis. The spectral VD can provide confident knowledge of the longitudinal bunch properties at the next generation of high-repetition rate linear accelerators while reducing the load on data storage, readout and streaming requirements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Automatic parameter selection for electron ptychography via Bayesian optimization

Abstract Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and to study electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior to those processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.

42 ENGINEERING↗
DOE OSTI2024

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Universality in size-driven evolution towards bulk polarizability of metals

The properties and characteristics of materials on the subnano/nano scale are very different from those of their bulk counterparts. The evolution of materials properties with size is the holy grail of nanoscience. An intriguing question then is: Can one predict what type of material (metal, semiconductor or insulator) an unidentified element will be, when in bulk quantities, solely from the properties it exhibits over a limited range of the subnano/nano size-regime? We demonstrate here that for nominally metallic elements ( i.e. , elements that are metals in bulk quantities) the answer to this question is “yes”, and the very identity of the element also can be established. Most importantly, we show that the phenomenon of size-induced transition to metallicity, as gauged by polarizability, is characterized by features and trends that are universal for all metals. Finally, combining numerical simulation data with an analytical model we introduce a universal constant and derive equations that express the universality explicitly.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fault-tolerant grid frequency measurement algorithm during transients

Many critical electric grid operations rely on accurate grid frequency measurements. Unfortunately, the measurement accuracy can be easily undermined by power system transient faults. During a power system transient fault, the power grid voltages and currents are usually highly distorted by high-frequency components. What is worse, the power grid signals could have discontinuity during some system transient faults such as phase angle jump, and the discontinuity could result in large measurement errors to state-of-the-art grid measurement algorithms. In this study, a fault-tolerant grid frequency measurement algorithm during transients is proposed. The new algorithm consists of two stages. The first stage is a transient detector, and it can detect the occurrence of system transient faults instantaneously. The second stage is the intelligent frequency estimator, and it will adapt its measurements according to the transient detector. The performance of the algorithm is evaluated under different steady-state and transient conditions. Both dependability and security of the fault-tolerant algorithm are assessed by using PSCAD simulation data and IEEE Standard test data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Cataloging accreted stars within Gaia DR2 using deep learning

The goal of this study is to present the development of a machine learning based approach that utilizes phase space alone to separate the Gaia DR2 stars into two categories: those accreted onto the Milky Way from those that are in situ. Traditional selection methods that have been used to identify accreted stars typically rely on full 3D velocity, metallicity information, or both, which significantly reduces the number of classifiable stars. The approach advocated here is applicable to a much larger portion of Gaia DR2. Methods. A method known as “transfer learning” is shown to be effective through extensive testing on a set of mock Gaia catalogs that are based on the F IRE cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies. The machine is first trained on simulated data using only 5D kinematics as inputs and is then further trained on a cross-matched Gaia /RAVE data set, which improves sensitivity to properties of the real Milky Way. Results. The result is a catalog that identifies ~767 000 accreted stars within Gaia DR2. This catalog can yield empirical insights into the merger history of the Milky Way and could be used to infer properties of the dark matter distribution.

Astronomy & Astrophysics↗
DOE OSTI2020

TDCOSMO. I. An exploration of systematic uncertainties in the inference of $H_0$ from time-delay cosmography

Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H0. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the “bulge-halo” conspiracy, H0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H0 = 74.0−1.8+1.7 km s−1 Mpc−1, while the power-law model yields 74.2−1.6+1.6 km s−1 Mpc−1. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Convective shells in the interior of Cepheid variable stars: Overshooting models based on hydrodynamic simulations

Context. Because Cepheid variable stars have long been used as a cosmic benchmark for scaling distances in our Galaxy and beyond, the accuracy of stellar evolution models for Cepheids have wide-reaching effects. However, our understanding of the dynamics in the interiors of these physically complex stars is limited. Aims. Our goal is to provide a detailed multi-dimensional picture of hydrodynamic convection and convective boundary mixing in the interior of Cepheids. Methods. Using the Modules for Experiments in Stellar Astrophysics (MESA), we studied the structure of intermediate-mass stars that cross the instability strip. Then, we performed two-dimensional hydrodynamic simulations of six stars with the fully compressible Multidimensional Stellar Implicit Code (MUSIC). Our simulations did not model the radial pulsations but focused on the interior structure of this family of stars. We developed and applied a new statistical analysis to examine convection and convective boundary mixing in the interior of these stellar simulations. Results. Based on a grid of MESA models, we demonstrated that a common structure for intermediate mass Cepheids includes an interior convective shell as well as a thin outer convective envelope. Using the extreme value theory approach to analyze our MUSIC simulation data, we found that overshooting above the convective shell fills the space between these convectively unstable layers. We developed a new statistical analysis that provides a clearer picture of how overshooting fills this layer; it also allowed us to formulate a detailed comparison between overshooting above and below the convective shell. Our analysis effectively decomposes the overshooting layer into two layers: a weak overshooting layer and a strong overshooting layer. Statistically, this is accomplished by decomposing the strongly non-Gaussian probability density function into a mixture of gamma distributions. Using our mixture model, we showed that the ratio of overshooting lengths above and below the convective shell depends directly on the radial extent of the convective shell as well as its depth in the star. We proposed a new form for the diffusion coefficient that addresses the need for overlapping overshooting layers between convective shells. We introduced the idea of a “super-mixing layer” where overshooting from both the convective shell and the convective envelope results in efficient mixing and could be viewed as merging the two adjacent convective zones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Temperature effect on the small-to-large crossover lengthscale of hydrophobic hydration

The thermodynamics of hydration is expected to change gradually from entropic for small solutes to enthalpic for large ones. The small-to-large crossover lengthscale of hydrophobic hydration depends on the thermodynamic conditions of the solvent such as temperature, pressure, presence of additives, etc. We attempt to shed some light on the temperature dependence of the crossover lengthscale by using a probabilistic approach to water hydrogen bonding that allows one to obtain an analytic expression for the number of bonds per water molecule as a function of both its distance to a solute and solute radius. Incorporating that approach into the density functional theory, one can examine the solute size effects on its hydration over the entire small-to-large lengthscale range at a series of different temperatures. Knowing the dependence of the hydration free energy on the temperature and solute size, one can also obtain its enthalpic and entropic contributions as functions of both temperature and solute size. These functions can provide some interesting insight into the temperature dependence of the crossover lengthscale of hydrophobic hydration. The model was applied to the hydration of spherical particles of various radii in water in the temperature range from T = 293.15 K to T = 333.15 K. The model predictions for the temperature dependence of the hydration free energy of small hydrophobes are consistent with the experimental and simulational data on the hydration of simple molecular solutes. Three alternative definitions for the small-to-large crossover length-scale of hydrophobic hydration are proposed, and their temperature dependence is obtained. Depending on the definition and temperature, the small-to-large crossover in the hydration mechanism is predicted to occur for hydrophobes of radii from one to several nanometers. Independent of its definition, the crossover length-scale is predicted to decrease with increasing temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A six-channel pediatric coil array for detection of children spinal pathologies by MRI at 1.5 Tesla

Nowadays, magnetic resonance (MR) in Mexico has become a standard technique for clinical imaging. Although most of the times the MR systems contain only coils oriented for adults. Radiologists use these coils for children studies due to the non-availability of pediatric coils. Image quality is decreased due to the low signal to noise ratio delivered to the system. The development of RF coils is always focused towards increasing SNR and optimizing the RF penetration into the sample. Moreover, spinal pathologies in children, which are an important topic in pediatric care, cover congenital and neuromuscular disorders that occur in childhood. In this work, the design of a dedicated six-channel coil for detection of spinal pathologies at 1.5 Tesla is addressed. Numerical electromagnetic simulations were performed in order to evaluate their magnetic field performance at (63.6 MHz) 1.5 Tesla. The magnetic field uniformity as well as the RF penetration depth of the coil configurations was evaluated in order to find the best/optimized coil array configuration. The coil is comprised of three rows, one with 4 coil elements and two with only one coil element. Phantom and in vivo images were acquired with the six-channel pediatric coil array. The phantom images agree with the simulated data. In vivo images acquired with the 6-channel pediatric coil array have shown very good penetration depth and homogeneity, which allow better image quality throughout the whole FOV. In addition, the parallel imaging capabilities of the array allow the acceleration of the experiments avoiding possible motion artifacts.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Structure and osmotic pressure of ionic microgel dispersions

We investigate structural and thermodynamic properties of aqueous dispersions of ionic microgels—soft colloidal gel particles that exhibit unusual phase behavior. Starting from a coarse-grained model of microgel macroions as charged spheres that are permeable to microions, we perform simulations and theoretical calculations using two complementary implementations of Poisson-Boltzmann (PB) theory. Within a one-component model, based on a linear-screening approximation for effective electrostatic pair interactions, we perform molecular dynamics simulations to compute macroion-macroion radial distribution functions, static structure factors, and macroion contributions to the osmotic pressure. For the same model, using a variational approximation for the free energy, we compute both macroion and microion contributions to the osmotic pressure. Within a spherical cell model, which neglects macroion correlations, we solve the nonlinear PB equation to compute microion distributions and osmotic pressures. By comparing the one-component and cell model implementations of PB theory, we demonstrate that the linear-screening approximation is valid for moderately charged microgels. By further comparing cell model predictions with simulation data for osmotic pressure, we chart the cell model’s limits in predicting osmotic pressures of salty dispersions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Muon neutrino charged current inclusive charged pion (CCπ{sup ±}) production in MINERνA

The production of charged pions by neutrinos interacting on nuclei is of great interest in nuclear physics and neutrino oscillation experiments. The MINERνA experiment is working towards releasing the world’s first high statistics neutrino pion production measurements in a few-GeV neutrino beam. We describe MINERνA’s CCπ{sup ±} analysis event selection in both the neutrino and antineutrino beams, noting reconstruction resolutions and kinematic limits. We also show area-normalized data-simulation comparisons of the reconstructed muon and charged pion kinetic energy distributions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A broadband gamma-ray spectrometry using novel unfolding algorithms for characterization of laser wakefield-generated betatron radiation

We present a high-flux, broadband gamma-ray spectrometry capable of characterizing the betatron radiation spectrum over the photon energy range from 10 keV to 20 MeV with respect to the peak photon energy, spectral bandwidth, and unique discrimination from background radiations, using a differential filtering spectrometer and the unfolding procedure based on the Monte Carlo code GEANT4. These properties are experimentally verified by measuring betatron radiation from a cm-scale laser wakefield accelerator (LWFA) driven by a 1-PW laser, using a differential filtering spectrometer consisting of a 15-filter and image plate stack. The gamma-ray spectra were derived by unfolding the photostimulated luminescence (PSL) values recorded on the image plates, using the spectrometer response matrix modeled with the Monte Carlo code GEANT4. The accuracy of unfolded betatron radiation spectra was assessed by unfolding the test PSL data simulated with GEANT4, showing an ambiguity of less than 20% and clear discrimination from the background radiation with less than 10%. The spectral analysis of betatron radiation from laser wakefield-accelerated electron beams with energies up to 3 GeV revealed radiation spectra characterized by synchrotron radiation with the critical photon energy up to 7 MeV. The gamma-ray spectrometer and unfolding method presented here facilitate an in-depth understanding of betatron radiation from LWFA process and a novel radiation source of high-quality photon beams in the MeV regime.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Lagrangian technique to calculate window interface velocity from shock velocity measurements: Application for quartz windows

Measurement of the window interface velocity is a common technique for investigating the dynamic response materials at high strain rates. However, these measurements are limited in pressure to the range where the window remains transparent. The most common window material for this application is lithium fluoride, which under single shock compression becomes opaque at ~200 GPa. To date, no other window material has been identified for use at higher pressures. Here, we present a Lagrangian technique to calculate the interface velocity from a continuously measured shock velocity, with application to quartz. The quartz shock front becomes reflective upon melt, at ~100 GPa, enabling the use of velocity interferometry to continuously measure the shock velocity. This technique overlaps with the range of pressures accessible with LiF windows and extends the region where wave profile measurements are possible to pressures in excess of 2000 GPa. Lastly, we show through simulated data that the technique accurately reproduces the interface velocity within 20% of the initial state, and that the Lagrangian technique represents a significant improvement over a simple linear approximation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigating shear flow through continuum gyrokinetic simulations of limiter biasing in the Texas Helimak

Previous limiter-biasing experiments on the Texas Helimak, a simple magnetized torus, have been inconclusive on the effect of flow shear on turbulence levels. To explore this, the first gyrokinetic simulations of limiter biasing in the Helimak using the plasma physics code Gkeyll have been carried out, and results are presented here. For the scenarios considered, turbulence is mostly driven by the interchange instability, which depends on gradients of steady state density profiles. An analysis of both experimental and simulation data demonstrates that shear rates are mostly less than than local linear growth rates, and not all requirements for shear stabilization are met. Yet, the mostly vertical shear flow has an important effect on bulk transport and experimental steady-state density profiles, and changes to the gradients correspond to changes in turbulence levels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗