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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identification and Exploration of a Series of SARS-Cov-2 M Pro Cyano-Based Inhibitors Revealing Ortho-Substitution Effects within the P3 Biphenyl Group

Starting from a simple scaffold hopping exercise based on our previous exploration of cysteine protease inhibitors against legumain, compound 6a was identified as a starting point for the development of a SARS-CoV-2 main protease (M Pro ) inhibitor. Compound 6a displayed submicromolar biochemical potency in the ultrasensitive assay developed by Drag and coworkers. Through an iterative structure−activity relationship campaign, we discovered an unexpected improvement in both biochemical and cellular potency through the incorporation of an ortho substituent within the P3 benzamide. X-ray crystallography revealed that incorporation of the ortho substituent caused a subtle but important binding enhancement of the P1 glutamate group within the M Pro S1 pocket. While incorporation of the ortho substituent improved the potency, the off-target selectivity against a panel of cysteine proteases and cell activity remained suboptimal. Further scanning of the P2 core revealed that incorporation of the 3.1.0 proline could address these issues and afford compound 22e, a highly potent and cellularly active M Pro inhibitor.

COVID-19 infection↗
DOE OSTI2024

Identification of Kelvin-Helmholtz generated vortices in magnetised fluids

The Kelvin-Helmholtz Instability (KHI), arising from velocity shear across the magnetopause, plays a significant role in the viscous-like transfer of mass, momentum, and energy from the shocked solar wind into the magnetosphere. While the KHI leads to growth of surface waves and vortices, suitable detection methods for these applicable to magnetohydrodynamics (MHD) are currently lacking. A novel method is derived based on the well-established λ-family of hydrodynamic vortex identification techniques, which define a vortex as a local minimum in an adapted pressure field. The J × B Lorentz force is incorporated into this method by using an effective total pressure in MHD, including both magnetic pressure and a pressure-like part of the magnetic tension derived from a Helmholtz decomposition. The λ MHD method is shown to comprise of four physical effects: vortical momentum, density gradients, fluid compressibility, and the rotational part of the magnetic tension. A local three-dimensional MHD simulation representative of near-flank magnetopause conditions (plasma β’s 0.5 – 5 and convective Mach numbers M f ∼ 0.4) under northward interplanetary magnetic field (IMF) is used to validate λ MHD . Analysis shows it correlates well with hydrodynamic vortex definitions, though the level of correlation decreases with vortex evolution. Overall, vortical momentum dominates λ MHD at all times. During the linear growth phase, density gradients act to oppose vortex formation. By the highly nonlinear stage, the formation of small-scale structures leads to a rising importance of the magnetic tension. Compressibility was found to be insignificant throughout. Finally, a demonstration of this method adapted to tetrahedral spacecraft observations is performed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

SHAPER: can you hear the shape of a jet?

The identification of interesting substructures within jets is an important tool for searching for new physics and probing the Standard Model at colliders. Many of these substructure tools have previously been shown to take the form of optimal transport problems, in particular the Energy Mover’s Distance (EMD). In this work, we show that the EMD is in fact the natural structure for comparing collider events, which accounts for its recent success in understanding event and jet substructure. We then present a Shape Hunting Algorithm using Parameterized Energy Reconstruction (SHAPER), which is a general framework for defining and computing shape-based observables. SHAPER generalizes N-jettiness from point clusters to any extended, parametrizable shape. This is accomplished by efficiently minimizing the EMD between events and parameterized manifolds of energy flows representing idealized shapes, implemented using the dual-potential Sinkhorn approximation of the Wasserstein metric. We show how the geometric language of observables as manifolds can be used to define novel observables with built-in infrared-and-collinear safety. We demonstrate the efficacy of the SHAPER framework by performing empirical jet substructure studies using several examples of new shape-based observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2020

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Distributed fiber sensor and machine learning data analytics for pipeline protection against extrinsic intrusions and intrinsic corrosions

This paper presents an integrated technical framework to protect pipelines against both malicious intrusions and piping degradation using a distributed fiber sensing technology and artificial intelligence. A distributed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (φ-OTDR) was used to detect acoustic wave propagation and scattering along pipeline structures consisting of straight piping and sharp bend elbow. Signal to noise ratio of the DAS system was enhanced by femtosecond induced artificial Rayleigh scattering centers. Data harnessed by the DAS system were analyzed by neural network-based machine learning algorithms. The system identified with over 85% accuracy in various external impact events, and over 94% accuracy for defect identification through supervised learning and 71% accuracy through unsupervised learning.

Peng, Zhaoqiang↗
NASA NTRS1979

The terrestrial cratering record. I - Current status of observations

The location, size and principle characteristics of the currently known proven and probable terrestrial impact craters are compiled. A crater is classified as proven if the structure is associated with meteoritic fragments, and probable if shock metamorphic effects are observed in the target rocks. Proven impact structures have been found to be Pleistocene to Recent in age, while probable impact structures range from Precambrian to Pleistocene. Diameter and age relationships are used to show that a 20 km impact structure will be recognizable as a crater for up to 600 million years, and smaller structures will have shorter lifetimes. Depth-diameter relationships for terrestrial craters show them to be intrinsically shallower than their lunar counterparts, and a transition in crater morphology from simple, or bowl-shaped with an uplifted rim, to complex, with an uplifted center and a depressed rim, is observed with increasing diameter. Shock metamorphic studies have lead to the identification of the type of bolide at a number of probable impact craters, supporting meteoritic origins.

Grieve, R. A. F.↗
NASA NTRS1988

Diffraction imaging (topography) with monochromatic synchrotron radiation

Structural information of special interest to crystal growers and device physicists is now available from high resolution monochromatic synchrotron diffraction imaging (topography). In the review, the importance of superior resolution in momentum transfer and in space is described, and illustrations are taken from a variety of crystals: gallium arsenide, cadmium telluride, mercuric iodide, bismuth silicon oxide, and lithium niobate. The identification and understanding of local variations in crystal growth processes are shown. Finally, new experimental opportunities now available for exploitation are indicated.

Steiner, Bruce↗
NASA NTRS1998

Analysis of Phase Separation in Czochralski Grown Single Crystal Ilmenite

Ilmenite (FeTiOs) is a wide bandgap semiconductor with an energy gap of 2.58 eV. Ilmenite has properties suited for radiation tolerant applications, as well as a variety of other electronic applications. Single crystal ilmenite has been grown from the melt using the Czochralski method. Growth conditions have a profound effect on the microstructure of the samples. Here we present data from a variety of analytical techniques which indicate that some grown crystals exhibit distinct phase separation during growth. This phase separation is apparent for both post-growth annealed and unannealed samples. Under optical microscopy, there appear two distinct areas forming a matrix with an array of dots on order of 5 pm diameter. While appearing bright in the optical micrograph, atomic force microscope (AFM) shows the dots to be shallow pits on the surface. Magnetic force microscope (MFM) shows the dots to be magnetic. Phase identification via electron microprobe analysis (EMPA) indicates two major phases in the unannealed samples and four in the annealed samples, where the dots appear to be almost pure iron. This is consistent with micrographs taken with a scanning probe microscope used in the magnetic force mode. Samples that do not exhibit the phase separation have little or no discernible magnetic structure detectable by the MFM.

Wilkins, R.↗
NASA NTRS2001

Familial orthostatic tachycardia due to norepinephrine transporter deficiency

Orthostatic intolerance (OI) or postural tachycardia syndrome (POTS) is a syndrome primarily affecting young females, and is characterized by lightheadedness, palpitations, fatigue, altered mentation, and syncope primarily occurring with upright posture and being relieved by lying down. There is typically tachycardia and raised plasma norepinephrine levels on upright posture, but little or no orthostatic hypotension. The pathophysiology of OI is believed to be very heterogeneous. Most studies of the syndrome have focused on abnormalities in norepinephrine release. Here the hypothesis that abnormal norepinephrine transporter (NET) function might contribute to the pathophysiology in some patients with OI was tested. In a proband with significant orthostatic symptoms and tachycardia, disproportionately elevated plasma norepinephrine with standing, impaired systemic, and local clearance of infused tritiated norepinephrine, impaired tyramine responsiveness, and a dissociation between stimulated plasma norepinephrine and DHPG elevation were found. Studies of NET gene structure in the proband revealed a coding mutation that converts a highly conserved transmembrane domain Ala residue to Pro. Analysis of the protein produced by the mutant cDNA in transfected cells demonstrated greater than 98% reduction in activity relative to normal. NE, DHPG/NE, and heart rate correlated with the mutant allele in this family. CONCLUSION: These results represent the first identification of a specific genetic defect in OI and the first disease linked to a coding alteration in a Na+/Cl(-)-dependent neurotransmitter transporter. Identification of this mechanism may facilitate our understanding of genetic causes of OI and lead to the development of more effective therapeutic modalities.

Review, Tutorial↗
NASA NTRS2012

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites). At the same time, new image manipulation and display capabilities are available within AWIPS II, the next generation of the NWS forecaster decision support system. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and articulate an integrated and collaborative path forward with Raytheon AWIPS II development staff for integrating current and future capabilities that support new satellite instrumentation and the AWIPS II decision support system.

Molthan, Andrew L.↗
DOE OSTI2021

Identification of bioprivileged molecules: expansion of a computational approach to broader molecular space

As interest in biobased chemicals grows, and their application space expands, computational tools to navigate molecule space as a complement to experimental approaches are imperative. This work expands upon previous work that identified candidate bioprivileged molecules from the C 6 H x O y (C6) subspace. It refines the framework that was developed previously to better refine the molecules according to their biological origin and applies it to three new subspaces of chemical structure: C 4 H x O y (C4), C 5 H x O y (C5), and C 7 H x O y (C7). For C5 and C7, roughly the top 100 bioprivileged candidates were identified, and the enhanced framework was applied to recast slightly the previous list of the top 100 C6 molecules. In addition, all top candidates were analyzed for their key functional moieties using a random forest model, and this algorithm was applied to compare the functional group space occupied by bioprivileged molecules of various databases of molecules with a focus on evaluating how closely the molecules were aligned with those known to biology. Furthermore, with the present work's focus on automation and data science principles, the framework can be easily expanded to include other chemical formulae to screen for bioprivileged candidates. As a result, this in turn facilitates the retrosynthesis process inherent in the framework to identify those bioprivileged intermediates in other subspaces that lead to target molecules.

42 ENGINEERING↗
DOE OSTI2022

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Geophysical Methods for Stratigraphic Identification

The goal of this work is to identify geophysical methods that can be used to delineate (in 3D) a large-scale paleochannel that has been inferred to exist between the 200 West and 200 East Areas of the Hanford Site’s Central Plateau . This paleochannel is of particular importance because it will significantly impact flow and contaminant transport from 200 West to 200 East. Its high permeability can both accelerate contaminant transport and lower contaminant concentrations through spreading. Information about the spatial extent and structure of such features is needed to inform subsurface flow and contaminant transport models that support remedy decisions at Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2003

Physical Alteration of Martian Dust Grains, Its Influence on Detection of Clays and Identification of Aqueous Processes on Mars

Clays, if present on Mars, have been illusive. Determining whether or not clay minerals and other aqueous alteration species are present on Mars provides key information about the extent and duration of aqueous processes on Mars. The purpose of this study is to characterize in detail changes in the mineral grains resulting from grinding and to assess the influence of physical processes on clay minerals on the surface of Mars. Physical alteration through grinding was shown to greatly affect the structure and a number of properties of antigorite and kaolinite. This project builds on an initial study and includes a combination of SEM, HRTEM, reflectance and M ssbauer spectroscopies. Grain size was found to decrease, as expected, with grinding. In addition, nanophase carbonate, Si-OH and iron oxide species were formed.

Janice L Bishop↗
DOE OSTI2020

Identification of highly active surface iron sites on Ni(OOH) for the oxygen evolution reaction by atomic layer deposition

Atomic layer deposition (ALD) has become a versatile tool in catalysis, allowing for precise synthesis of catalysts useful for gaining fundamental understanding of complex systems. In this work, ALD was used to perform surface-directed modification of Ni(OH) 2 /Ni(OOH) electrocatalysts for the oxygen evolution reaction (OER) to elucidate the different roles of iron as a surface dopant and as iron distributed throughout the NiOOH structure. Electrochemical and material characterization of FeO x ALD-modified Ni(OH) 2 indicates that iron is deposited on the surface of Ni(OH) 2 sheets without modifying its bulk properties. Sub-monolayer amounts of iron were deposited on the surface of Ni(OH) 2 using low cycle numbers of ALD. This surface iron results in high OER activity, characteristic of Ni-Fe(OOH) catalysts. Ni(OH) 2 /Ni(OOH) catalysts modified to incorporate iron throughout the structure were prepared by depositing large cycle numbers of FeO x ALD, which results in the deposition of a Fe 2 O 3 overlayer. Corrosion of this Fe 2 O 3 overlayer during electrochemical cycling in alkaline electrolyte leads to the incorporation of iron throughout the structure of Ni(OH) 2 /Ni(OOH) while leaving some Fe at the surface. Incorporation of iron throughout the Ni(OH) 2 /Ni(OOH) structure was found to increase OER geometric activity for thick, high surface area Ni(OH) 2 /Ni(OOH) catalysts. Lastly, NiFeO x electrocatalysts synthesized fully by ALD were investigated for the OER; these catalysts demonstrated high OER activity and potential for photocatalysis applications.

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

Identification of durable and non-durable FeN x sites in Fe–N–C materials for proton exchange membrane fuel cells

We report that while Fe–N–C materials are a promising alternative to platinum for catalysing the oxygen reduction reaction in acidic polymer fuel cells, limited understanding of their operando degradation restricts rational approaches towards improved durability. Here we show that Fe–N–C catalysts initially comprising two distinct FeN x sites (S1 and S2) degrade via the transformation of S1 into iron oxides while the structure and number of S2 were unmodified. Structure–activity correlations drawn from end-of-test 57 Fe Mössbauer spectroscopy reveal that both sites initially contribute to the oxygen reduction reaction activity but only S2 substantially contributes after 50 h of operation. From in situ 57 Fe Mössbauer spectroscopy in inert gas coupled to calculations of the Mössbauer signature of FeN x moieties in different electronic states, we identify S1 to be a high-spin FeN 4 C 12 moiety and S2 a low- or intermediate-spin FeN 4 C 10 moiety. These insights lay the groundwork for rational approaches towards Fe–N–C cathodes with improved durability in acidic fuel cells.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Identification of mechanisms driving heterogeneous void growth in ductile aluminum

Void growth plays a central role in ductile fracture, yet the specific mechanisms that control this remain obscure. Classical models, such as those proposed by Rice and Tracey in 1969, are able to capture average rates of void growth, but cannot capture the heterogeneity of individual void growth. Building on recent work, the present study employs laboratory-based diffraction contrast tomography and in-situ x-ray computed tomography to investigate the effect of grain structure and other microstructural factors on void growth in an Al-2219 alloy. Crystal plasticity finite element (CP-FE) modeling is used alongside experimental data to evaluate the contributions of local mechanical states, grain orientation, grain size, and neighboring microstructural features. No strong linear relationships are found with any of the considered descriptors and void growth rate. Potential complex nonlinear relationships are explored with the use of a random forest regression model, which identifies initial void volume, void aspect ratio, local normal stress state, local shear stress state, and local equivalent plastic strain (EQPS) as features that most improve void growth rate predictions. The combination of these analyses suggests that these features should be prioritized to improve models of void growth.

Diffraction contrast tomography (DCT)↗