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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Muon Decay Study at NSRL

A muon is an unstable subatomic particle, classified as a lepton according to the Standard Model. Muons are charged leptons with 1/2 spin. They were discovered by Neddermeyer and Anderson from hadronic cosmic ray showers. Figure 1 provides a visual representation of a cosmic ray shower in Earth’s atmosphere. At a height of 50 000 m in the atmosphere, a primary cosmic ray (mainly protons, helium, a heavy nucleus or a gamma ray) interacts with a gas molecule. The striking of a gas molecule creates a cosmic ray shower, where the energy of the primary particle is distributed among many secondary particles and gamma rays. With each interaction, the cosmic ray particles in the shower lose energy but distribute this energy among a higher number of particles. From the initial interaction, primarily heavy nuclei and pions are generated. Heavy nuclei will interact with gas molecules to produce protons, gamma rays, electrons and pions. The dominant decay mode of neutral pions is to two gamma rays, while charged pions decay to a muon and a neutrino (equation 1): $π^+ → µ^+$ + $\overline ν$ $_µ$; $π → µ$ $^-$ + $\overline v$ $_µ$.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Muon Detector Visualization in Unreal Engine

This presentation will describe recent efforts to visualize muon collider detector geometries and col- lision events with modern 3D game development tools, particularly Unreal Engine 5. The workflow from HEP-specific tools to industry standard formats will be described, and an interactive demo will be available.

Lee, Lawrence↗
DOE OSTI2022

Spatial mapping of plant N-glycosylation cellular heterogeneity inside soybean root nodules provided insights into legume-rhizobia symbiosis

Although ubiquitously present, information on the function of complex N-glycan posttranslational modification in plants is very limited and it is often neglected. In this work, we adopted an enzyme-assisted matrix-assisted laser desorption/ionization mass spectrometry imaging strategy to visualize the distribution and identity of N-glycans in soybean root nodules at a cellular resolution. We additionally performed proteomics analysis to probe the potential correlation to proteome changes during symbiotic rhizobia-legume interactions. Our ion images reveal that intense N-glycosylation occurs in the sclerenchyma layer, and inside the infected cells within the infection zone, while morphological structures such as the cortex, uninfected cells, and cells that form the attachment with the root are less N-glycosylated. Notably, we observed different N-glycan profiles between soybean root nodules infected with wild type rhizobia and those infected with mutant rhizobia incapable of efficiently fixing atmospheric nitrogen. The majority of complex N-glycan structures, particularly those with characteristic Lewis-a epitopes, are overexpressed in the mutant nodules. Our proteomic results revealed that these glycans likely originated from proteins that maintain the redox balance crucial for proper nitrogen fixation, but also from enzymes involved in N-glycan and phenylpropanoid biosynthesis. These findings indicate possible involvement of Lewis-a glycans in these critical pathways during legume-rhizobia symbiosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Iterative ML and Experiments for Emerging VOCs

SAND2026-17074O Iterative ML and Experiments for Emerging VOCs is a tool that analyzes and predicts the behaviors of SARS-CoV-2 variants. It processes experimental data on ACE2 (the receptor for the SARS-CoV-2 virus that allows it to infect the cell) and antibody binding using machine learning models, including neural networks, to forecast ACE2 interactions and variant expression. The tool employs transfer learning and global epistasis modeling, integrating public datasets with proprietary data to enhance prediction accuracy. Additionally, it fits concentration-response curves to determine dissociation constants and generates visualizations to support research findings, thereby aiding in the identification of new antibodies for emerging variants of concern. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sheffield, Thomas [Sandia National Lab. (SNL-NM), ↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Visualizing degradation mechanisms in a gas-fed CO 2 reduction cell via operando X-ray tomography

We utilize operando X-ray computed tomography, coupled with real-time electrochemical analysis, to reveal the underlying failure mechanisms of membrane electrode assemblies (MEAs) for electrochemical CO 2 reduction (eCO 2 R). Through operando imaging, we can obtain unprecedented insights into the dynamic behavior of the MEA under different operating conditions, revealing critical changes in interface interactions, phase distribution, and structural integrity over time. Our findings identify phenomena giving rise to the transition from CO 2 R to the hydrogen evolution reaction (HER), as evidenced by shifts in cathode potential and CO 2 R selectivity. The formation of inhomogeneous precipitates at the gas diffusion electrode disrupts the CO 2 supply and reduces the active sites for eCO 2 R, resulting in a shift toward H2 production during low current density operation. Additionally, under high current density conditions, rapid water crossover up to the microporous layer/gas diffusion layer promotes the transition from CO 2 R to HER, further shifting cell potential toward anodic direction. Oscillating voltage conditions reveal the dissolution and regrowth of precipitates, providing direct visualization of the competing selectivity of CO 2 R and HER. This work offers new insight into the degradation mechanisms of MEAs, with implications for the design of more durable CO 2 R systems.

Lee, Sol A [California Institute of Technology (Ca↗
DOE OSTI2024

Structures of methane and ammonia monooxygenases in native membranes

Methane- and ammonia-oxidizing bacteria play key roles in the global carbon and nitrogen cycles, respectively. These bacteria use homologous copper membrane monooxygenases to accomplish the defining chemical transformations of their metabolisms: the oxidations of methane to methanol by particulate methane monooxygenase (pMMO) and ammonia to hydroxylamine by ammonia monooxygenase (AMO), enzymes of prime interest for applications in mitigating climate change. However, investigations of these enzymes have been hindered by the need for disruptive detergent solubilization prior to structure determination, confounding studies of pMMO and precluding studies of AMO. Here, we overcome these challenges by using cryoEM to visualize pMMO and AMO directly in their native membrane arrays at 2.4 to 2.8 Å resolution. These structures reveal details of the copper centers, numerous bound lipids, and previously unobserved components, including identifiable and distinct supernumerary helices interacting with pMMO and AMO, suggesting a widespread role for these helices in copper membrane monooxygenases. Comparisons between these structures, their metallocofactors, and their unexpected protein–protein interactions highlight features that may govern activity or the formation of higher-order arrays in native membranes. The ability to obtain molecular insights within the native membrane will enable further understanding of these environmentally important enzymes.

Science & Technology - Other Topics↗
DOE OSTI2024

Direct observation of a magnetic-field-induced Wigner crystal

Wigner predicted that when the Coulomb interactions between electrons become much stronger than their kinetic energy, electrons crystallize into a closely packed lattice. A variety of two-dimensional systems have shown evidence for Wigner crystals (WCs). However, a spontaneously formed classical or quantum WC has never been directly visualized. Neither the identification of the WC symmetry nor direct investigation of its melting has been accomplished. Here we use high-resolution scanning tunnelling microscopy measurements to directly image a magnetic-field-induced electron WC in Bernal-stacked bilayer graphene and examine its structural properties as a function of electron density, magnetic field and temperature. At high fields and the lowest temperature, we observe a triangular lattice electron WC in the lowest Landau level. The WC possesses the expected lattice constant and is robust between filling factor ν ≈ 0.13 and ν ≈ 0.38 except near fillings where it competes with fractional quantum Hall states. Increasing the density or temperature results in the melting of the WC into a liquid phase that is isotropic but has a modulated structure characterized by the Bragg wavevector of the WC. At low magnetic fields, the WC unexpectedly transitions into an anisotropic stripe phase, which has been commonly anticipated to form in higher Landau levels. Furthermore, analysis of individual lattice sites shows signatures that may be related to the quantum zero-point motion of electrons in the WC lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Probing Complex Chemical Processes at the Molecular Level with Vibrational Spectroscopy and X-ray Tools

Understanding the origins of structure and bonding at the molecular level in complex chemical systems spanning magnitudes in length and time is of paramount interest in physical chemistry. Here, we have coupled vibrational spectroscopy and X-ray based techniques with a series of microreactors and aerosol beams to tease out intricate and sometimes subtle interactions, such as hydrogen bonding, proton transfer, and noncovalent interactions. This allows for unraveling the self-assembly of arginine-oleic acid complexes in an aqueous solution and growth processes in a metal–organic framework. Terahertz and infrared spectroscopy provide an intimate view of the hydrogen-bond network and associated phase changes with temperature in neopentyl glycol. The hydrogen-bond network in aqueous glycerol aerosols and levels of protonation of nicotine in aqueous aerosols are visualized. Future directions in probing the hydrogen-bond networks in deep eutectic solvents and organic frameworks are described, and we suggest how X-ray scattering coupled to X-ray spectroscopy can offer insight into the reactivity of organic aerosols.

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

LungMAP Portal Ecosystem: Systems-level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). Finally, as this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

pnnl/hypernetx-widget

Hnx-widget is a Jupyter notebook widget for visualizing hyper graphs that is intended to work in conjunction with the HyperNetX open source package developed by PNNL. It renders hyper graphs using Euler diagrams (a Venn diagram is a special type of Euler diagram). The tool contains simple interactions that allow the user to select nodes and change their appearance. It scales to small to medium sized (100 node) hyper graphs

Arendt, Dustin↗
DOE OSTI2022

Facile Labeling of Sieve Element Phloem-Protein Bodies Using the Reciprocal Oligosaccharide Probe OGA488

Sieve elements of many angiosperms contain structural phloem proteins (P-proteins) that can interact to create large P-protein bodies. P-protein bodies can occlude sieve plates upon injury but the range of functional and physiological roles of P-proteins remains uncertain, in part because of challenges in labeling and visualization methods. Here, we show that a reciprocal oligosaccharide probe, OGA 488 , can be used in rapid and sensitive labeling of P-protein bodies in Arabidopsis, poplar, snap bean and cucumber in histological sections. OGA 488 labeling of knockouts of the two Arabidopsis P-protein-encoding genes, AtSEOR1 and AtSEOR2 , indicated that labeling is specific to AtSEOR2. That protein bodies were labeled and visible in Atseor1 knockouts indicates that heterodimerization of AtSEOR1 and AtSEOR2 may not be necessary for P-protein body formation. Double labeling with a previously characterized stain for P-proteins, sulphorhodamine 101, confirmed P-protein labeling and also higher specificity of OGA 488 for P-proteins. OGA 488 is thus robust and easily used to label P-proteins in histological sections of multiple angiosperm species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Using X-ray Micro-Computed Tomography to Three-Dimensionally Visualize the Foregut of the Glassy-Winged Sharpshooter ( Homalodisca vitripennis )

Dissecting the heads of small insects belonging to the order Hemiptera for detailed anatomical investigation with light or scanning electron microscopy is difficult, time-consuming, and destructive, often resulting in sample preparation artifacts. Nevertheless, the structural details of these insects often hold critical information regarding their interactions with bacterial pathogens. For example, the glassy-winged sharpshooter (GWSS) is an efficient vector of the bacterium Xylella fastidiosa, the causal agent of Pierce’s disease in grape vines, but the foregut of this species is exceptionally difficult to dissect. Here, we describe a simple, non-destructive method to investigate the structure of the anterior gut of GWSS using high-resolution micro-computed X-ray tomography (microCT). The use of microCT eliminates the need for destructive dissection and reveals the morphology of small insects in three dimensions, allowing the user to virtually dissect the sample. The use of microCT imaging is a promising and powerful tool in the entomological sciences for studying the structures of vector insects, especially for difficult-to-dissect regions such as the foregut.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Resolving protein-mineral interfacial interactions during in vitro mineralization by atom probe tomography

Organic macromolecules exert remarkable control over the nucleation and growth of inorganic crystallites during (bio)mineralization, as exemplified during enamel formation where the protein amelogenin regulates the formation of hydroxyapatite (HAP). However, it is poorly understood how fundamental processes at the organic-inorganic interface, such as protein adsorption and/or incorporation into minerals, regulates nucleation and crystal growth due to technical challenges in observing and characterizing mineral-bound organics at high-resolution. Here, atom probe tomography techniques were developed and applied to characterize amelogenin-mineralized HAP particles in vitro, revealing distinct organic-inorganic interfacial structures and processes at the nanoscale. Specifically, visualization of amelogenin across the mineralized particulate demonstrates protein can become entrapped during HAP crystal aggregation and fusion. Identification of protein signatures and structural interpretations were further supported by standards analyses, i.e., defined HAP surfaces with and without amelogenin adsorbed. These findings represent a significant advance in the characterization of interfacial structures and, more so, interpretation of fundamental organic-inorganic processes and mechanisms influencing crystal growth. Ultimately, this approach can be broadly applied to inform how potentially unique and diverse organic-inorganic interactions at different stages regulates the growth and evolution of various biominerals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High precision control and deep learning-based corn stand counting algorithms for agricultural robot

This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, such as emergence rate, biomass, vigor, and stand counting, are measured manually. This is highly labor-intensive and prone to errors. The robot, termed TerraSentia, is designed to automate the measurement of plant traits for efficient phenotyping as an alternative to manual measurements. In this paper, we formulate a Nonlinear Moving Horizon Estimator that identifies key terrain parameters using onboard robot sensors and a learning-based Nonlinear Model Predictive Control that ensures high precision path tracking in the presence of unknown wheel-terrain interaction. Moreover, we develop a machine vision algorithm designed to enable an ultra-compact ground robot to count corn stands by driving through the fields autonomously. The algorithm leverages a deep network to detect corn plants in images, and a visual tracking model to re-identify detected objects at different time steps. We collected data from 53 corn plots in various fields for corn plants around 14 days after emergence (stage V3 - V4). The robot predictions have agreed well with the ground truth with C robot =1.02×C human -0.86 and a correlation coefficient R=0.96. The mean relative error given by the algorithm is -3.78%, and the standard deviation is 6.76%. These results indicate a first and significant step towards autonomous robot-based real-time phenotyping using low-cost, ultra-compact ground robots for corn and potentially other crops.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems

Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting the building’s overall energy inefficiency and occupant comfort. A model predictive control (MPC) system that features a multi-objective MPC scheme to enable coordinated control of multiple building services for overall optimized energy efficiency, indoor thermal and visual comfort, as well as a hybrid model for predicting indoor visual comfort and lighting power is proposed. The MPC system was implemented in a test facility having two identical, side-by-side experimental cells to facilitate comparison with a building management system (BMS) employing conventional reactive feedback control. The MPC system coordinated the control of the ACMV, dynamic façade and automated dimmable lighting systems in one cell while the BMS controlled the building services in the other cell in a conventional manner. The MPC side achieved 15.1–20.7% electricity consumption reduction, as compared to the BMS side. Simultaneously, the MPC system improved indoor thermal comfort by maintaining the room within the comfortable range (-0.5 < predicted mean vote < 0.5) for 98.3% of the time, up from 91.8% of the time on the BMS side. Visual comfort, measured by indoor daylight glare probability (DGP) and horizontal illuminance level at work plane height, was maintained for the entire test period on the MPC side, improving from having visual comfort for 94.5% and 85.7% of the time, respectively, on the BMS side.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Phase-contrast 3D tomography of HeLa cells grown in PLLA polymer electrospun scaffolds using synchrotron X-rays

Advanced imaging is useful for understanding the three-dimensional (3D) growth of cells. X-ray tomography serves as a powerful noninvasive, nondestructive technique that can fulfill these purposes by providing information about cell growth within 3D platforms. There are a limited number of studies taking advantage of synchrotron X-rays, which provides a large field of view and suitable resolution to image cells within specific biomaterials. In this study, X-ray synchrotron radiation microtomography at Diamond Light Source and advanced image processing were used to investigate cellular infiltration of HeLa cells within poly L-lactide (PLLA) scaffolds. This study demonstrates that synchrotron X-rays using phase contrast is a useful method to understand the 3D growth of cells in PLLA electrospun scaffolds. Two different fiber diameter (2 and 4 µm) scaffolds with different pore sizes, grown over 2, 5 and 8 days in vitro , were examined for infiltration and cell connectivity. After performing visualization by segmentation of the cells from the fibers, the results clearly show deeper cell growth and higher cellular interconnectivity in the 4 µm fiber diameter scaffold. Finally, this indicates the potential for using such 3D technology to study cell–scaffold interactions for future medical use.

3D culture↗