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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Simultaneous observation of the quantization and the interference pattern of a plasmonic near-field

Surface plasmon polaritons can confine electromagnetic fields in subwavelength spaces and are of interest for photonics, optical data storage devices and biosensing applications. In analogy to photons, they exhibit wave–particle duality, whose different aspects have recently been observed in separate tailored experiments. Here we demonstrate the ability of ultrafast transmission electron microscopy to simultaneously image both the spatial interference and the quantization of such confined plasmonic fields. Our experiments are accomplished by spatiotemporally overlapping electron and light pulses on a single nanowire suspended on a graphene film. The resulting energy exchange between single electrons and the quanta of the photoinduced near-field is imaged synchronously with its spatial interference pattern. In conclusion, this methodology enables the control and visualization of plasmonic fields at the nanoscale, providing a promising tool for understanding the fundamental properties of confined electromagnetic fields and the development of advanced photonic circuits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Multi-matrix, dual polarity, tandem mass spectrometry imaging strategy applied to a germinated maize seed: toward mass spectrometry imaging of an untargeted metabolome

Mass spectrometry imaging (MSI) provides high spatial resolution information that is unprecedented in traditional metabolomics analyses; however, the molecular coverage is often limited to a handful of compounds and is insufficient to understand overall metabolomic changes of a biological system. Here, we propose an MSI methodology to increase the diversity of chemical compounds that can be imaged and identified, in order to eventually perform untargeted metabolomic analysis using MSI. We use the desorption/ionization bias of various matrixes for different metabolite classes along with dual polarities and a tandem MSI strategy. The use of multiple matrixes and dual polarities allows us to visualize various classes of compounds, while data-dependent MS/MS spectra acquired in the same MSI scans allow us to identify the compounds directly on the tissue. In a proof of concept application to a germinated corn seed, a total of 166 unique ions were determined to have high-quality MS/MS spectra, without counting structural isomers, of which 52 were identified as unique compounds. According to an estimation based on precursor MSI datasets, we expect over five hundred metabolites could be potentially identified and visualized once all experimental conditions are optimized and an MS/MS library is available. Finally, metabolites involved in the glycolysis pathway and tricarboxylic acid cycle were imaged to demonstrate the potential of this technology to better understand metabolic biology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Systematic characterization of protein folding pathways using diffusion maps: Application to Trp-cage miniprotein

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories in a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

58 GEOSCIENCES↗
DOE OSTI2020

eFESTA: Ensemble Feature Exploration with Surface Density Estimates

We propose surface density estimate (SDE) to model the spatial distribution of surface features-isosurfaces, ridge surfaces, and streamsurfaces-in 3D ensemble simulation data. The inputs of SDE computation are surface features represented as polygon meshes, and no field datasets are required (e.g., scalar fields or vector fields). The SDE is defined as the kernel density estimate of the infinite set of points on the input surfaces and is approximated by accumulating the surface densities of triangular patches. We also propose an algorithm to guide the selection of a proper kernel bandwidth for SDE computation. An ensemble Feature Exploration method based on Surface densiTy EstimAtes (eFESTA) is then proposed to extract and visualize the major trends of ensemble surface features. For an ensemble of surface features, each surface is first transformed into a density field based on its contribution to the SDE, and the resulting density fields are organized into a hierarchical representation based on the pairwise distances between them. The hierarchical representation is then used to guide visual exploration of the density fields as well as the underlying surface features. We demonstrate the application of our method using isosurface in ensemble scalar fields, Lagrangian coherent structures in uncertain unsteady flows, and streamsurfaces in ensemble fluid flows.

Computational modeling↗
DOE OSTI2015

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

MFA-DVR: direct volume rendering of MFA models

3D volume rendering is widely used to reveal insightful intrinsic patterns of volumetric datasets across many domains. However, the complex structures and varying scales of volumetric data can make efficiently generating high-quality volume rendering results a challenging task. Multivariate functional approximation (MFA) is a new data model that addresses some of the critical challenges: high-order evaluation of both value and derivative anywhere in the spatial domain, compact representation for large-scale volumetric data, and uniform representation of both structured and unstructured data. Here, in this paper, we present MFA-DVR, the first direct volume rendering pipeline utilizing the MFA model, for both structured and unstructured volumetric datasets. We demonstrate improved rendering quality using MFA-DVR on both synthetic and real datasets through a comparative study. We show that MFA-DVR not only generates more faithful volume rendering than using local filters but also performs faster on high-order interpolations on structured and unstructured datasets. MFA-DVR is implemented in the existing volume rendering pipeline of the Visualization Toolkit (VTK) to be accessible by the scientific visualization community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Intergalactic medium emission observations with the cosmic web imager. II. Discovery of extended, kinematically linked emission around SSA22 Lyα BLOB 2

The intergalactic medium (IGM) is the dominant reservoir of baryons, delineates the large-scale structure of the universe at low to moderate overdensities, and provides gas from which galaxies form and evolve. Simulations of a cold-dark-matter- (CDM-) dominated universe predict that the IGM is distributed in a cosmic web of filaments and that galaxies should form along and at the intersections of these filaments. While observations of QSO absorption lines and the large-scale distribution of galaxies have confirmed the CDM paradigm, the cosmic web of IGM has never been confirmed by direct imaging. Here we report our observation of the Lyα blob 2 (LAB2) in SSA22 with the Cosmic Web Imager (CWI). This is an integral field spectrograph optimized for low surface brightness, extended emission. With 22 hr of total on- and off-source exposure, CWI has revealed that LAB2 has extended Lyα emission that is organized into azimuthal zones consistent with filaments. We perform numerous tests with simulations and the data to secure the robustness of this result, which relies on data with modest signal-to-noise ratios. We have developed a smoothing algorithm that permits visualization of data cube slices along image or spectral image planes. With both raw and smoothed data cubes we demonstrate that the filaments are kinematically associated with LAB2 and display double-peaked profiles characteristic of optically thick Lyα emission. The flux is 10-20 times brighter than expected for the average emission from the IGM but is consistent with boosted fluorescence from a buried QSO or gravitation cooling radiation. Using simple emission models, we infer a baryon mass in the filaments of at least 1-4 × 10{sup 11} M {sub ☉}, and the dark halo mass is at least 2 × 10{sup 12} M {sub ☉}. The spatial-kinematic morphology is more consistent with inflow from the cosmic web than outflow from LAB2, although an outflow feature maybe present at one azimuth. LAB2 and the surrounding gas have significant and coaligned angular momentum, strengthening the case for their association.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Characterizing vortex tangle properties in steady-state He II counterflow using particle tracking velocimetry

Historically, there has been little faith in particle tracking velocimetry (PTV) as a tool to make quantitative measurements of thermal counterflow in He II, since tracer particle motion is complicated by influences from the normal fluid, superfluid, and quantized vortex lines, or a combination thereof. Recently, we introduced a scheme for differentiating particles trapped on vortices (G1) from particles entrained by the normal fluid (G2). In this paper, we apply this scheme to demonstrate the utility of PTV for quantitative measurements of vortex dynamics in He II counterflow.We estimate Ι, the mean vortex line spacing, using G2 velocity data, and c 2 , a parameter related to the mean curvature radius of vortices and energy dissipation in quantum turbulence, using G1 velocity data. We find that both estimations show good agreement with existing measurements that were obtained using traditional experimental methods. This is of particular consequence since these parameters likely vary in space, and PTV offers the advantage of spatial resolution. Furthermore, we also show a direct link between power-law tails in transverse particle velocity probability density functions (PDFs) and reconnection of vortex lines on which G1 particles are trapped.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Identification of a nematic pair density wave state in Bi 2 Sr 2 CaCu 2 O 8+x

Electron-pair density wave (PDW) states are now an intense focus of research in the field of cuprate correlated superconductivity. PDWs exhibit periodically modulating superconductive electron pairing that can be visualized directly using scanned Josephson tunneling microscopy (SJTM). Although from theory, intertwining the d-wave superconducting (DSC) and PDW order parameters allows a plethora of global electron-pair orders to appear, which one actually occurs in the various cuprates is unknown. In this work, we use SJTM to visualize the interplay of PDW and DSC states in Bi 2 Sr 2 CaCu 2 O 8+x at a carrier density where the charge density wave modulations are virtually nonexistent. Simultaneous visualization of their amplitudes reveals that the intertwined PDW and DSC are mutually attractive states. Then, by separately imaging the electron-pair density modulations of the two orthogonal PDWs, we discover a robust nematic PDW state. Its spatial arrangement entails Ising domains of opposite nematicity, each consisting primarily of unidirectional and lattice commensurate electron-pair density modulations. Further, we demonstrate by direct imaging that the scattering resonances identifying Zn impurity atom sites occur predominantly within boundaries between these domains. This implies that the nematic PDW state is pinned by Zn atoms, as was recently proposed [Lozano et al., Phys. Rev. B 103, L020502 (2021)]. Taken in combination, these data indicate that the PDW in Bi 2 Sr 2 CaCu 2 O 8+x is a vestigial nematic pair density wave state [Agterberg et al. Phys. Rev. B 91, 054502 (2015); Wardh and Granath arXiv:2203.08250].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles?

Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles. However, little is known as to whether antipredator behavior models are appropriate to apply to an approaching high-speed vehicle scenario. We addressed this gap by (a) providing an overview of the main hypotheses and predictions of different antipredator behavior models via a literature review, (b) exploring whether these models can generate quantitative predictions on escape distance when parameterized with empirical data from the literature, and (c) evaluating their sensitivity to vehicle approach speed using a simulation approach wherein we assessed model performance based on changes in effect size with variations in the slope of the flight initiation distance (FID) vs. approach speed relationship. The slope of the FID vs. approach speed relationship was then related back to three different behavioral rules animals may rely on to avoid approaching threats: the spatial, temporal, or delayed margin of safety. We used literature on birds for goals (b) and (c). Our review considered the following eight models: the economic escape model, Blumstein’s economic escape model, the optimal escape model, the perceptual limit hypothesis, the visual cue model, the flush early and avoid the rush (FEAR) hypothesis, the looming stimulus hypothesis, and the Bayesian model of escape behavior. We were able to generate quantitative predictions about escape distance with the last five models. However, we were only able to assess sensitivity to vehicle approach speed for the last three models. The FEAR hypothesis is most sensitive to high-speed vehicles when the species follows the spatial (FID remains constant as speed increases) and the temporal margin of safety (FID increases with an increase in speed) rules of escape. The looming stimulus effect hypothesis reached small to intermediate levels of sensitivity to high-speed vehicles when a species follows the delayed margin of safety (FID decreases with an increase in speed). The Bayesian optimal escape model reached intermediate levels of sensitivity to approach speed across all escape rules (spatial, temporal, delayed margins of safety) but only for larger (> 1 kg) species, but was not sensitive to speed for smaller species. Overall, no single antipredator behavior model could characterize all different types of escape responses relative to vehicle approach speed but some models showed some levels of sensitivity for certain rules of escape behavior. We derive some applied applications of our findings by suggesting the estimation of critical vehicle approach speeds for managing populations that are especially susceptible to road mortality. Overall, we recommend that new escape behavior models specifically tailored to high-speeds vehicles should be developed to better predict quantitatively the responses of animals to an increase in the frequency of cars, airplanes, drones, etc. they will face in the next decade.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗
DOE OSTI2023

Patterns and rates of soil movement and shallow failures across several small watersheds on the Seward Peninsula, Alaska

Abstract. Thawing permafrost can alter topography, ecosystems, and sediment and carbon fluxes, but predicting landscape evolution of permafrost-influenced watersheds in response to warming and/or hydrological changes remains an unsolved challenge. Sediment flux and slope instability in sloping saturated soils have been commonly predicted from topographic metrics (e.g., slope, drainage area). In addition to topographic factors, cohesion imparted by soil and vegetation and melting ground ice may also control spatial trends in slope stability, but the distribution of ground ice is poorly constrained and hard to predict. To address whether slope stability and surface displacements follow topographic-based predictions, we document recent drivers of permafrost sediment flux present on a landscape in western Alaska that include creep, solifluction, gullying, and catastrophic hillslope failures ranging in size from a few meters to tens of meters, and we find evidence of rapid and substantial landscape change on an annual timescale. We quantify the timing and rate of surface movements using a multi-pronged, multi-scalar dataset including aerial surveys, interannual GPS surveys, synthetic aperture radar interferometry (InSAR), and climate data. Despite clear visual evidence of downslope soil transport of solifluction lobes, we find that the interannual downslope surface displacement of these features does not outpace downslope displacement of soil in locations where lobes are absent (downslope movement means: 7 cm yr−1 for lobes over 2 years vs. 10 cm yr−1 in landscape positions without lobes over 1 year). Annual displacements do not appear related to slope, drainage area, or modeled total solar radiation but are likely related to soil thickness, and volumetric sediment fluxes are high compared to temperate landscapes of comparable bedrock lithology. Time series of InSAR displacements show accelerated movement in late summer, associated with intense rainfall and/or deep thaw. While mapped slope failures do cluster at slope–area thresholds, a simple slope stability model driven with hydraulic conductivities representative of throughflow in mineral and organic soil drastically overpredicts the occurrence of slope failures. This mismatch implies permafrost hillslopes have unaccounted-for cohesion and/or throughflow pathways, perhaps modulated by vegetation, which stabilize slopes against high rainfall. Our results highlight the breadth and complexity of soil transport processes in Arctic landscapes and demonstrate the utility of using a range of synergistic data collection methods to observe multiple scales of landscape change, which can aid in predicting periglacial landscape evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Anatomic Distribution of Fluorodeoxyglucose-Avid Para-aortic Lymph Nodes in Patients With Cervical Cancer

Purpose: Conformal treatment of para-aortic lymph nodes (PAN) in cervical cancer allows dose escalation and reduces normal tissue toxicity. Currently, data documenting the precise location of involved PAN are lacking. We define the spatial distribution of this high-risk nodal volume by analyzing fluorodeoxyglucose (FDG)-avid lymph nodes (LNs) on positron emission tomography/computed tomography (PET/CT) scans in patients with cervical cancer. Methods and Materials: We identified 72 PANs on pretreatment PET/CT of 30 patients with newly diagnosed stage IB-IVA cervical cancer treated with definitive chemoradiation. LNs were classified as left-lateral para-aortic (LPA), aortocaval (AC), or right paracaval (RPC). Distances from the LN center to the closest vessel and adjacent vertebral body were calculated. Using deformable image registration, nodes were mapped to a template computed tomogram to provide a visual impression of nodal frequencies and anatomic distribution. Results: We identified 72 PET-positive para-aortic lymph nodes (37 LPA, 32 AC, 3 RPC). All RPC lymph nodes were in the inferior third of the para-aortic region. The mean distance from aorta for all lymph nodes was 8.3 mm (range, 3-17 mm), and from the inferior vena cava was 5.6 mm (range, 2-10 mm). Of the 72 lymph nodes, 60% were in the inferior third, 36% were in the middle third, and 4% were in the upper third of the para-aortic region. In all, 29 of 30 patients also had FDG-avid pelvic lymph nodes. Conclusions: A total of 96% of PET positive nodes were adjacent to the aorta; PET positive nodes to the right of the IVC were rare and were all located distally, within 3 cm of the aortic bifurcation. Our findings suggest that circumferential margins around the vessels do not accurately define the nodal region at risk. Instead, the anatomical extent of the nodal basin should be contoured on each axial image to provide optimal coverage of the para-aortic nodal compartment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

KS4A-Omics1.0_FspDS682

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils, because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hotspots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood. Here, we addressed this knowledge gap by directly visualizing nutrient acquisition and transport through fungal hyphae in a mineral doped soil micromodel using a multimodal imaging approach. Here, we observed how a representative of common saprotrophic soil fungi, Fusarium sp. DS 682, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals.This study establishes the significance of fungal biology and nutrient translocation mechanisms in maintaining fungal growth under water and nutrient limitations in a soil-like microenvironment, using a high-throughput multi-omic analysis approach. Data package KS4A-Omics.1.0_FspDS682 (Publication: Fungal Mineral Weathering Mechanisms Revealed Through Direct Molecular Visualization) contents reported here are the first version (1.0) and contain pre- and post-processed data using high throughput data capture technologies for multi-omic analysis and integration, this data package contains raw and post-processed experimental data for X-Ray Absorption Near Edge Structure Spectroscopy (XANES/XRF), Optical Microscopy, Proteomics, Scanning Electron Microscope (SEM), Time-of-Flight Secondary Ion Mass Spectroscopy (ToF-SIMS), X-Ray Diffraction Spectroscopy (XRD) files, and X- Ray Photoelectron Spectroscopy (XPS) using EMSL capabilities. This data package DOI contains a comprehensive collection of high-throughput multi-omics data and process metadata catalog. Support files include additional data download contents “Read Me” with dataset descriptor information and data source method application ontologies (see data dictionary section). Reported data download content is structured for compliance with reported guidelines provided by community standard initiatives and publisher stakeholder policies supporting FAIR data principles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Quantitative Effects of Disorder on Chemically Modified Amorphous Carbon Electrodes

Real materials are disordered. This disorder influences the properties of these materials and the chemical processes that occur at their interfaces. Gaining a molecular-level understanding of the underlying physical manifestations caused by disordered materials is crucial to unraveling and ultimately controlling the efficiency and performance of these materials in a range of energy-related devices. This understanding necessitates measurement techniques through which disorder can be detected, quantified, and monitored. However, such quantitative measurements are notoriously difficult, as effects often average out in ensemble measurements. In this work, we describe how a combination of electrochemical and spatially resolved surface spectroscopy measurements illuminate a molecular-level picture of disorder in materials. Using amorphous carbon as an intrinsically disordered material, we covalently attached a monolayer of ferrocene. Interfacial electron transfer across the amorphous carbon–ferrocene interface is highly sensitive to disruptions of order. Here, by systematically varying linker properties and surface loadings, the influence of lateral interactions between nonuniformly distributed ferrocene headgroups on ensemble electrochemical measurements is demonstrated. Electrochemical and imaging data collectively indicate that conformational flexibility of the ferrocene moieties provides a mechanism to elude repulsive and unbalanced lateral interactions, while rigid linkages provide direct information about the underlying disorder of the material. This study is the first of its kind to quantify and visualize molecular disorder and heterogeneity with an experimental model accessed through ensemble measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗
DOE OSTI2017

3D MALDI Mass Spectrometry Imaging of a Single Cell: Spatial Mapping of Lipids in the Embryonic Development of Zebrafish

The zebrafish ( Danio rerio ) has been widely used as a model vertebrate system to study lipid metabolism, the roles of lipids in diseases, and lipid dynamics in embryonic development. Here, we applied high-spatial resolution matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) to map and visualize the three-dimensional spatial distribution of phospholipid classes, phosphatidylcholine (PC), phosphatidylethanolamines (PE), and phosphatidylinositol (PI), in newly fertilized individual zebrafish embryos. This is the first time MALDI-MSI has been applied for three dimensional chemical imaging of a single cell. PC molecular species are present inside the yolk in addition to the blastodisc, while PE and PI species are mostly absent in the yolk. Two-dimensional MSI was also studied for embryos at different cell stages (1-, 2-, 4-, 8-, and 16-cell stage) to investigate the localization changes of some lipids at various cell developmental stages. Lastly, four different normalization approaches were compared to find reliable relative quantification in 2D- and 3D- MALDI MSI data sets.

59 BASIC BIOLOGICAL SCIENCES↗