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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Kelvin-Helmholtz instability as one of the key features for fast and efficient emulsification by hydrodynamic cavitation

The paper investigates the oil–water emulsification process inside a micro-venturi channel. More specifically, the possible influence of Kelvin-Helmholtz instability on the emulsification process. High-speed visualizations were conducted inside a square venturi constriction with throat dimensions of 450 µm by 450 µm, both under visible light and X-Rays. We show that cavity shedding caused by the instability results in the formation of several cavity vortices. Their rotation causes the deformation of the oil stream into a distinct wave-like shape, combined with fragmentation into larger drops due to cavitation bubble collapse. Later on, the cavity collapse further disperses the larger drops into a finer emulsion. Thus, it turns out that the Kelvin-Helmholtz instability is similarly characteristic for hydrodynamic cavitation emulsification inside a microchannel as is the Rayleigh-Taylor instability for acoustically driven emulsion formation.

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

The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

Abstract Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based general-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data diversity, we visualize it with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5 M density functional theory calculations, while the ANI-1ccx data set contains 500 k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM calculated properties for the chemical elements C, H, N, and O are provided: energies, atomic forces, multipole moments, atomic charges, etc. We provide this data to the community to aid research and development of ML models for chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

The Transfer Function Model as a Tool to Study and Describe Space Weather Phenomena

The Transfer Function Model (TFM) is a semi-analytical, linear model that is designed especially to describe thermospheric perturbations associated with magnetic storms and substorm. activity. It is a multi-constituent model (N2, O, He H, Ar) that accounts for wind induced diffusion, which significantly affects not only the composition and mass density but also the temperature and wind fields. Because the TFM adopts a semianalytic approach in which the geometry and temporal dependencies of the driving sources are removed through the use of height-integrated Green's functions, it provides physical insight into the essential properties of processes being considered, which are uncluttered by the accidental complexities that arise from particular source geometrie and time dependences. Extending from the ground to 700 km, the TFM eliminates spurious effects due to arbitrarily chosen boundary conditions. A database of transfer functions, computed only once, can be used to synthesize a wide range of spatial and temporal sources dependencies. The response synthesis can be performed quickly in real-time using only limited computing capabilities. These features make the TFM unique among global dynamical models. Given these desirable properties, a version of the TFM has been developed for personal computers (PC) using advanced platform-independent 3D visualization capabilities. We demonstrate the model capabilities with simulations for different auroral sources, including the response of ducted gravity waves modes that propagate around the globe. The thermospheric response is found to depend strongly on the spatial and temporal frequency spectra of the storm. Such varied behavior is difficult to describe in statistical empirical models. To improve the capability of space weather prediction, the TFM thus could be grafted naturally onto existing statistical models using data assimilation.

Porter, Hayden S.↗
DOE OSTI2021

Imaging Charged Exciton Localization in van der Waals WSe 2 /MoSe 2 Heterobilayers

Exciton localization in transition-metal dichalcogenide monolayers is behind a variety of interesting phenomena and applications, including broad-spectrum solar cells and singlephoton emissions. Strain fields at the periphery of topographically distinct features such as nanoscopic bubbles were recently associated with localized charge-neutral excitons. Here, we use tip-enhanced photoluminescence (PL) to visualize excitons in WSe 2 /MoSe 2 heterobilayers (HBL). We find strong optical emission from charged excitons, particularly positively charged trions, in HBL supported by interlayer charge transfer. Our results reveal strong trion confinement, with a localization length scale comparable to the trion size, at the apex region inside individual nanoscopic bubbles. Nano-PL mapping also shows sub-10 nm spatial variations in the localized trion emission spectra, which stem from atomic-scale potential energy fluctuations. These findings demonstrate the possibility of confining charged exciton complexes that are electrically tunable, opening up further opportunities to probe many-body exciton physics, and to explore additional possible sites for strong exciton localization that can lead to quantum emissions.

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

X-ray Linear Dichroism in Apatite

The recent observation in parrotfish teeth of X-ray linear dichroism motivated an in-depth investigation into this spectroscopic effect in various apatite crystals, including geologic hydroxyapatite (Ca 5 (PO 4 ) 3 OH), fluorapatite (Ca 5 (PO 4 ) 3 F), and their biogenic counterparts in human bone, mouse enamel, and in parrotfish bone, dentin, and enameloid, the equivalent of dental enamel in certain fish. These data are important because they now enable visualization of the nano- to microscale structure of apatite crystals in teeth and bone. Polarization-dependent imaging contrast (PIC) maps of lamellar bone, obtained with a new method that minimizes space-charge and charging effects, show the expected rotating apatite crystal orientations. PIC maps of mouse enamel reveal a complex arrangement of hydroxyapatite crystals perpendicular to the dentin-enamel junction, with rods arranged in a decussation pattern in inner enamel and nearly parallel to one another in outer enamel. In both inner and outer enamel crystal c-axes are not always aligned with the rod elongation direction.

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

Investigating the effect of supramolecular gel phase crystallization on gel nucleation

Supramolecular gel phase crystallization offers a new strategy for drug polymorph screening and discovery. In this method, the crystallization outcome depends on the interaction between solute and gel fibre. While supramolecular gels have shown success in producing new polymorphs and crystals with novel morphologies, role of the gel and nature of gel–solute interaction remains largely unexplored. The present study aims to provide a comprehensive picture of the structural evolution of a supramolecular gel produced from a bis(urea) based gelator (G) in the presence of a polymorphic drug carbamazepine (CBZ). The structural aspects of the gel have been assessed by single crystal X-ray analysis, X-ray powder diffraction (XRPD) and solid state NMR spectroscopy. Small Angle Neutron Scattering (SANS) has been used to follow the changes in gel structure in the presence of CBZ. Visual evidence from morphological study and structural evolution observed at a macroscopic level from rheological measurements, shows good agreement with the SANS results. The concentration of the gelator and the relative proportion of G to CBZ were found to be crucial factors in determining the competitive nucleation events involving gelation and crystallization. At a critical G to CBZ ratio the effect of CBZ on gel structure was maximum and fiber bundling in the gel was found to be critically affected. Here, this study offers important information about how the interplay of gelator assembly and gel–solute interactions can fine-tune the nucleation events in a supramolecular gel phase crystallization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗
DOE OSTI2019

Electric Field–Controlled Multistep Proton Evolution in H x SrCoO 2.5 with Formation of H–H Dimer

Ionic evolution–induced phase transformation can lead to wide ranges of novel material functionalities with promising applications. Here, using the gating voltage during ionic liquid gating as a tuning knob, the brownmillerite SrCoO2.5 is transformed into a series of protonated HxSrCoO2.5 phases with distinct hydrogen contents. The unexpected electron to charge-neutral doping crossover along with the increase of proton concentration from x = 1 to 2 suggests the formation of exotic charge neutral H–H dimers for higher proton concentration, which is directly visualized at the vacant tetrahedron by scanning transmission electron microscopy and then further supported by first principles calculations. Although the H–H dimers cause no change of the valency of Co2+ ions, they result in clear enhancement of electronic bandgap and suppression of magnetization through lattice expansion. These results not only reveal a hydrogen chemical state beyond anion and cation within the complex oxides, but also suggest an effective pathway to design functional materials through tunable ionic evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Representations of Shavitt Graphs Within the Graphical Unitary Group Approach

The Shavitt graph is a visual representation of a distinct row table (DRT) within the graphical unitary group approach. The DRT is a compact representation of the entire configuration state function expansion space within a molecular electronic structure calculation. Each node of the graph is associated with an integer triple (a k , b k , c k ). These integers may be mapped to other quantum numbers, including the number of orbitals, number of electrons, and spin quantum number, and used to display Shavitt graphs in various ways that emphasize different aspects of the expansion space or that reveal different aspects of computed wave functions. In conclusion, the features of several graph density plots are discussed, including electron-hole symmetries and the bonding-antibonding wave function character.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nanophotonics for Chemical Imaging and Spectroscopy

The manipulation of light and light-matter interactions on the nanoscale is enabled by the unique optical properties of plasmonic metal nanostructures and nanoparticles. Indeed, engineered hybrid molecular-plasmonic nanostructures have enabled single molecule detection and identification via surface-enhanced Raman scattering (SERS). Further, the same effect is at the core of visualizing single molecules with sub-nanometer spatial resolution via tip-enhanced Raman scattering (TERS). More generally, modern applications of plasmon-enhanced spectroscopy and microscopy fueled advances in fields as diverse as quantum and semiconductor materials, heterogeneous catalysis, and the health sciences, to name a few. All these exciting developments and many more are touched in this virtual special issue (VSI) on nanophotonics. From ultra-precise chemical imaging measurements performed in a scanning tunneling microscope chamber to single molecule spectroscopic measurements performed at solid-air and solid-liquid interfaces, this VSI includes contributions from active practitioners that are all striving to better-understand increasingly complex interfaces encountered in the biological, materials, and chemical sciences.

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

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

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

Direct visualization of radiation-induced transformations at alkali halide–air interfaces

Radiation driven reactions at mineral/air interfaces are important to the chemistry of the atmosphere, but experimental constraints (e.g. simultaneous irradiation, in situ observation, and environmental control) leave process understanding incomplete. Using a custom atomic force microscope equipped with an integrated X-ray source, transformation of potassium bromide surfaces to potassium nitrate by air radiolysis species was followed directly in situ at the nanoscale. Radiolysis initiates dynamic step edge dissolution, surface composition evolution, and ultimately nucleation and heteroepitaxial growth of potassium nitrate crystallites mediated by surface diffusion at rates controlled by adsorbed water. Finally, in contrast to in situ electron microscopy and synchrotron-based imaging techniques where high radiation doses are intrinsic, our approach illustrates the value of decoupling irradiation and the basis of observation.

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

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2023

Longitudinal Single‐Cell Imaging of Engineered Strains with Stimulated Raman Scattering to Characterize Heterogeneity in Fatty Acid Production

Abstract Understanding metabolic heterogeneity is critical for optimizing microbial production of valuable chemicals, but requires tools that can quantify metabolites at the single‐cell level over time. Here, longitudinal hyperspectral stimulated Raman scattering (SRS) chemical imaging is developed to directly visualize free fatty acids in engineered Escherichia coli over many cell cycles. Compositional analysis is also developed to estimate the chain length and unsaturation of the fatty acids in living cells. This method reveals substantial heterogeneity in fatty acid production among and within colonies that emerges over the course of many generations. Interestingly, the strains display distinct types of production heterogeneity in an enzyme‐dependent manner. By pairing time‐lapse and SRS imaging, the relationship between growth and production at the single‐cell level are examined. The results demonstrate that cell‐to‐cell production heterogeneity is pervasive and provides a means to link single‐cell and population‐level production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mending cracks atom-by-atom in rutile TiO2 with electron beam radiolysis

Abstract Rich electron-matter interactions fundamentally enable electron probe studies of materials such as scanning transmission electron microscopy (STEM). Inelastic interactions often result in structural modifications of the material, ultimately limiting the quality of electron probe measurements. However, atomistic mechanisms of inelastic-scattering-driven transformations are difficult to characterize. Here, we report direct visualization of radiolysis-driven restructuring of rutile TiO 2 under electron beam irradiation. Using annular dark field imaging and electron energy-loss spectroscopy signals, STEM probes revealed the progressive filling of atomically sharp nanometer-wide cracks with striking atomic resolution detail. STEM probes of varying beam energy and precisely controlled electron dose were found to constructively restructure rutile TiO 2 according to a quantified radiolytic mechanism. Based on direct experimental observation, a “two-step rolling” model of mobile octahedral building blocks enabling radiolysis-driven atomic migration is introduced. Such controlled electron beam-induced radiolytic restructuring can be used to engineer novel nanostructures atom-by-atom.

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

Effects of α-tubulin acetylation on microtubule structure and stability

Acetylation of K40 in α-tubulin is the sole posttranslational modification to mark the luminal surface of microtubules. It is still controversial whether its relationship with microtubule stabilization is correlative or causative. We have obtained high-resolution cryo-electron microscopy (cryo-EM) reconstructions of pure samples of αTAT1-acetylated and SIRT2-deacetylated microtubules to visualize the structural consequences of this modification and reveal its potential for influencing the larger assembly properties of microtubules. We modeled the conformational ensembles of the unmodified and acetylated states by using the experimental cryo-EM density as a structural restraint in molecular dynamics simulations. We found that acetylation alters the conformational landscape of the flexible loop that contains αK40. Modification of αK40 reduces the disorder of the loop and restricts the states that it samples. We propose that the change in conformational sampling that we describe, at a location very close to the lateral contacts site, is likely to affect microtubule stability and function.

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

An experimental and computational view of the photoionization of diol–water clusters

In the interstellar medium, diols and other prebiotic molecules adsorb onto icy mantles surrounding dust grains. Water in the ice may affect the reactivity and photoionization of these diols. Ethylene glycol (EG), 1,2-propylene glycol, and 1,3-propylene glycol clusters with water clusters were used as a proxy to study these interactions. The diol–water clusters were generated in a continuous supersonic molecular beam, photoionized by synchrotron-based vacuum ultraviolet light from the Advanced Light Source, and subsequently detected by reflectron time-of-flight mass spectrometry. The appearance energies for the detected clusters were determined from the mass spectra, collected at increasing photon energy. Clusters of both diol fragments and unfragmented diols with water were detected. The lowest energy geometry optimized conformers for the observed EG–water clusters and EG fragment–water clusters have been visualized using density functional theory (DFT), providing insight into hydrogen bonding networks and how these affect fragmentation and appearance energy. As the number of water molecules clustered around EG fragments (m/z 31 and 32) increased, the appearance energy for the cluster decreased, indicating a stabilization by water. This trend was supported by DFT calculations. Fragment clusters from 1,2-propylene glycol exhibited a similar trend, but with a smaller energy decrease, and no trend was observed from 1,3-propylene glycol. In conclusion, we discuss and suggest that the reactivity and photoionization of diols in the presence of water depend on the size of the diol, the location of the hydroxyl group, and the number of waters clustered around the diol.

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

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗