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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

PDB‐101: Molecular Explorations through Biology and Medicine

PDB‐101 is an online portal for teachers, students, and the general public to promote exploration of the structural biology of proteins and nucleic acids ( pdb101.rcsb.org ). Learning about the diverse shapes and functions of these biological macromolecules helps to understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease to biological energy. Why PDB‐101? Researchers around the world are studying these molecules at the atomic level. These 3D structures are freely available at the Protein Data Bank (PDB), the central storehouse of biomolecular structures. This website builds introductory materials to help beginners get started in the basics of biomolecular structure and function (“101”, as in an entry level course) as well as resources for extended learning. Since 2011, PDB‐101 has been developed by the RCSB PDB , a global resource for the advancement of research and education in biology and medicine. Along with our Worldwide PDB collaborators, RCSB PDB curates, annotates, and makes publicly available the PDB data deposited by scientists around the globe. The RCSB PDB then provides a window to these data through a rich online resource with powerful searching, reporting, and visualization tools for researchers. This information is then streamlined for students and teachers at PDB‐101. Features include the ongoing Molecule of the Month series, educational materials such as paper models, posters, molecular animations, educational curricula and more. The section “Guide to Understanding PDB Data” is a primer for detailed PDB‐specific information: PDB Data, Visualizing Structures, Reading Coordinate Files, scientific methods for structure determination, and more. PDB‐101 also runs annual Video Challenges for high school students. Participants create short videos that tell molecular stories that connect structural biology and medicine. Previous topics have included HIV/AIDS, diabetes, and antimicrobial resistance. The 2022 challenge will focus on Molecular Mechanisms of Cancer. PDB‐101 activities are evaluated using user surveys, feedback from in‐person activities, and website analytics. In 2020, PDB‐101 hosted >850,000 users and >2.6 million page views.

Zardecki, Christine↗
DOE OSTI2018

Integrating diagnostics and model-based optimization

Energy Management and Information Systems are a family of analytics technologies that include energy information systems, fault detection and diagnostics (FDD), and automated system optimization tools. Such systems have the potential to enable buildings to meet energy management goals of reducing total energy consumption and cost. Most current market offerings use data-driven and rule-based analytics. However, the use of physics-based models in the analytics offers potential improvements by providing an accurate estimation of outputs based on representation of the physical principles governing the building system behaviors. This also permits the use of design stage models to inform commissioning and operation. This paper describes the development and testing of a hybrid data-driven and physics model-based operational tool for energy efficiency in central cooling plants. The tool offers FDD functionality, setpoint optimization, and visualization of key performance parameters. It was demonstrated at a university campus in the mixed-humid ASHRAE Climate Zone 4A. Key performance metrics that were analyzed include plant electricity use reduction, plant model calibration, and system economics. Annual simulations indicate the tool can provide electricity savings of greater than 10% for approximately six months of the year, mainly during the winter season when wet bulb temperatures are low, though only 1.38% savings for the entire year. Additionally, over a 4-day period in April, recommended optimal setpoints were implemented, resulting in 17% savings versus metered baseline consumption. With respect to model calibration, the difference between model-predicted and measured parameters was less than 10% for 90% of data points acquired for three of six chillers, and for each ten cooling towers. Finally, the tool users reported that satisfaction with the capabilities was equal to or better than that with the preexisting BAS system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Towards Interactive, Reproducible Analytics at Scale on HPC Systems

The growth in scientific data volumes has resulted in a need to scale up processing and analysis pipelines using High Performance Computing (HPC) systems. These workflows need interactive, reproducible analytics at scale. The Jupyter platform provides core capabilities for interactivity but was not designed for HPC systems. In this paper, we outline our efforts that bring together core technologies based on the Jupyter Platform to create interactive, reproducible analytics at scale on HPC systems. Our work is grounded in a real world science use case-applying geophysical simulations and inversions for imaging the subsurface. Our core platform addresses three key areas of the scientific analysis workflow-reproducibility, scalability, and interactivity. We describe our implemention of a system, using Binder, Science Capsule, and Dask software. We demonstrate the use of this software to run our use case and interactively visualize real-Time streams of HDF5 data.

containers↗
DOE OSTI2026

GridCoPilot for Thermal Events: An LLM-Based Platform for Power Grid Reliability Analysis

Large Language Models show promise for translating natural language into database queries, but deploying such systems in safety-critical domains requires high reliability. We present an application of GridCoPilot to thermal event analysis (heatwaves and coldwaves) that affect power grid reliability. Our approach uses a LangChain SQL Agent to translate natural language queries into auditable SQL statements, with deterministic visualization routines that parse the structured query results. We introduce structural framing as a design principle, we integrate a NERC-region-level event library with county-level meteorology and decompose the combined data into three relational tables (event metadata, county-level event details, and a county-to-NERC subregion mapping), using prompt-guided joins to direct the model toward correct multi-table queries. For two core analytical patterns (identifying worst events by region and by region-year), the system achieved 100% SQL accuracy across all 16 NERC subregions and both event types (64 queries total). These results validate the approach for target use cases, though performance on diverse natural language formulations requires further investigation. We discuss design trade-offs, failure modes including JSON output truncation, and pathways for extending this approach to other hazard domains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Immersive Digital Twins and Decision Making

This work focuses on developing and implementing immersive digital twins to support decision-making processes in construction automation and energy simulation analysis. The use of digital twins enables users to explore and interact with virtual replicas of physical systems, providing a unique and valuable perspective for problem-solving. In the context of construction automation, we present two case studies that integrate immersive visualization and worker-machine interaction. In the context of energy simulation analysis using digital twins, we describe our digital twin framework that combines interactive visualization with machine learning techniques to approximate computationally expensive simulations, allowing for faster and more efficient analysis of complex energy systems. Through these research endeavors, we demonstrate the potential of immersive digital twins in decision-making across various domains.

digital twins↗
DOE OSTI2020

Laser-Plasma Spatiotemporal Cyanide Spectroscopy and Applications

This article reports new measurements of laser-induced plasma hypersonic expansion measurements of diatomic molecular cyanide (CN). Focused, high-peak-power 1064 nm Q-switched radiation of the order of 1 TW/cm 2 generated optical breakdown plasma in a cell containing a 1:1 molar gas mixture of N 2 and CO 2 at a fixed pressure of 1.1 × 10 5 Pascal and in a 100 mL/min flow of the mixture. Line-of-sight (LOS) analysis of recorded molecular spectra indicated the outgoing shockwave at expansion speeds well in excess of Mach 5. Spectra of atomic carbon confirmed increased electron density near the shockwave, and, equally, molecular CN spectra revealed higher excitation temperature near the shockwave. Results were consistent with corresponding high-speed shadowgraphs obtained by visualization with an effective shutter speed of 5 nanoseconds. In addition, LOS analysis and the application of integral inversion techniques allow inferences about the spatiotemporal plasma distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synchrotron-based double imaging photoelectron/photoion coincidence spectroscopy of radicals produced in a flow tube: OH and OD

We present a microwave discharge flow tube coupled with a double imaging electron/ion coincidence device and vacuum ultraviolet (VUV) synchrotron radiation. The system has been applied to the study of the photoelectron spectroscopy of the well-known radicals OH and OD. The coincidence imaging scheme provides a high selectivity and yields the spectra of the pure radicals, removing the ever-present contributions from excess reactants, background, or secondary products, and therefore obviating the need for a prior knowledge of all possible byproducts. The photoelectron spectra encompassing the X{sup 3}Σ{sup −} ground state of the OH{sup +} and OD{sup +} cations have been extracted and the vibrational constants compared satisfactorily to existing literature values. Future advantages of this approach include measurement of high resolution VUV spectroscopy of radicals, their absolute photoionization cross section, and species/isomer identification in chemical reactions as a function of time.

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

Design and implementation of a data analysis pipeline for paper spray ionization mass spectrometry of UO 2 Cl 2

Ambient mass spectrometry is an emerging characterization method for nuclear materials analysis. SRNL has recently acquired a new JEOL AccuTOF™-DART® LP 4G with a Filter Spray™ front end sample injection system, to develop new methods for ambient mass spectrometry of uranium analytes. Preliminary measurements of uranium-containing samples have demonstrated a need to rapidly evaluate large datasets generated with tailored data analysis scripts. To address this gap a data analysis pipeline written in R within the R Studio environment has been developed. The pipeline comprises a series of processing steps where the data are ingested, analyte peaks of interest are extracted, subsequent ratio and normalization calculations are performed, and results are presented in a series of graphical plots. In detail, the data files containing up to several hundred chronological spectra of a single sample in netCDF format were first extracted into RStudio. Then, initial 3D plots of the data were created in respect to the time, intensity, and mass to charge domains. These graphics serve as an initial easily visualized survey of instrument data. Next, a .csv format file containing the names, masses, and abundances of isotopes of interest were ingested into RStudio and were used to automatically collect intensity values at the mass value. Uranium isotope ratios were plotted against gadolinium isotope ratios (gadolinium was used as an internal standard) and assessed for ion beam stability and intensity. The spectra were filtered by applying a threshold intensity for the 158GdO+ mass channel. A Monte Carlo experiment was performed by creating a theoretical distribution of the data in order to determine the ratio of the uranium isotopes. The results show that the developed data analysis pipeline successfully filters high quality data from overall poor quality runs. Our results also support the idea that paper spray ionization mass spectrometry can be used for both detection and quantification of trace amounts of uranium compounds.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A Bright, Photostable, and Far-Red Dye That Enables Multicolor, Time-Lapse, and Super-Resolution Imaging of Acidic Organelles

Lysosomes have long been known for their acidic lumens and efficient degradation of cellular byproducts. In recent years, it has become clear that their function is far more sophisticated, involving multiple cell signaling pathways and interactions with other organelles. Unfortunately, their acidic interior, fast dynamics, and small size make lysosomes difficult to image with fluorescence microscopy. Here we report a far-red small molecule, HMSiR 680 -Me, that fluoresces only under acidic conditions, causing selective labeling of acidic organelles in live cells. HMSiR 680 -Me can be used alongside other far-red dyes in multicolor imaging experiments and is superior to existing lysosome probes in terms of photostability and maintaining cell health and lysosome motility. We demonstrate that HMSiR 680 -Me is compatible with overnight time-lapse experiments as well as time-lapse super-resolution microscopy with a frame rate of 1.5 fps for at least 1000 frames. HMSiR 680 -Me can also be used alongside silicon rhodamine dyes in a multiplexed super-resolution microscopy experiment to visualize interactions between mitochondria and lysosomes with only a single excitation laser and simultaneous depletion. We envision this dye permitting a more detailed study of the role of lysosomes in dynamic cellular processes and disease.

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

Quantitative Comparison of Dye and Ultrasmall Fluorescent Silica Core–Shell Nanoparticle Probes for Optical Super-Resolution Imaging of Model Block Copolymer Thin Film Surfaces

In recent years, high-resolution optical imaging in the far field has provided opportunities for alternative approaches to nanocharacterization traditionally dominated by electron and scanning probe microscopies. Here in this paper, we report the optical super-resolution imaging of model block copolymer (BCP) thin film surface nanostructures through stochastic optical reconstruction microscopy (STORM). We compare a set of surface-functionalized fluorescent core–shell silica nanoparticles encapsulating two different organic dyes, Cy3 and Cy5, with the corresponding free dyes in STORM. Using various click-type chemistries, these probes are covalently attached to the surface of specific blocks of BCP thin films, enabling selective block labeling and optical visualization. We demonstrate that the enhanced brightness of these particle probes offers distinct advantages over conventional dye labeling, outperforming one of the best STORM dyes available (Cy5).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Biogenic manganese oxide nanoparticle formation by a multimeric multicopper oxidase Mnx

Bacteria that produce Mn oxides are extraordinarily skilled engineers of nanomaterials that contribute significantly to global biogeochemical cycles. Their enzyme-based reaction mechanisms may be genetically tailored for environmental remediation applications or bioenergy production. However, significant challenges exist for structural characterization of the enzymes responsible for biomineralization. The active Mn oxidase, Mnx, in Bacillus sp. PL-12 is a complex composed of a multicopper oxidase (MCO), MnxG, and two accessory proteins MnxE and MnxF. MnxG shares sequence similarity with other, structurally characterized MCOs. However, MnxE and MnxF have no similarity to any characterized proteins. The ~200 kDa complex has been recalcitrant to crystallization, so its structure is unknown. In this study, native mass spectrometry defines the subunit topology and copper binding of the Mnx complex, while high resolution electron microscopy visualizes the protein and nascent Mn oxide minerals. Furthermore, these data provide critical structural information for conceptualizing how Mnx produces nanoparticulate Mn oxides.

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

Quantitative imaging of anion exchange kinetics in halide perovskites

Significance Fundamental understanding of chemical transformation mechanism in solid-state semiconductors can offer guidelines for engineering these materials with various functionalities. Microscopically resolving such transformation process on the single-particle level can provide a direct picture of the dynamics, but has always been challenging due to the deficiencies of characterization techniques and material dimensions. This work presents a unique design on realizing the quantitative imaging of anion exchange reaction kinetics in halide perovskites by taking advantage of their high and tunable photoluminescence and characteristic lattice dynamics, coupled with controllable chemical treatments and optical microscopic techniques. Our study on kinetically visualizing ion exchange behavior in solid-state materials could also inspire mechanistic insights into other phenomena in a broad context of physical science.

2D heterostructures↗
DOE OSTI2019

Topology Inference of Unknown Networks Based on Robust Virtual Coordinate Systems

Learning and exploring the connectivity of unknown networks represent an important problem in practical applications of communication networks and social-media networks. Modeling large-scale networks as connected graphs is highly desirable to extract their connectivity information among nodes to visualize network topology, disseminate data, and improve routing efficiency. This paper investigates a simple measurement model in which a small subset of source nodes collect hop distance information from networked nodes in order to generate a virtual coordinate system (VCS) for networks of unknown topology. We establish the VCS to define logical distance among nodes based on principal component analysis and to determine connectivity relationship and effective routing methods. More importantly, we present a robust analytical algorithm to derive the VCS against practical issues of missing and corrupted measurements. We also develop a connectivity inference method which classifies nodes into layers based on the hop distances and derives partial information on network connectivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Status of FUDGE [Slides]

This presentation discusses the nuclear data management code FUDGE (For Updating Data and Generating Evaluations). While FUDGE is designed to support GNDS, the presentation also states that ENDF-6 and ENDL data files are also supported but must first be translated into GNDS; translators are included with FUDGE. It also states that FUDGE supports plotting, manipulating, checking for physical content, resonance reconstruction, Doppler broadening, etc. FUDGE also supports processing for Monte Carlo and deterministic transport. FUDGE is open source, and the latest public release was FUDGE-4.2.3 with support for GNDS-1.9. In summation, FUDGE capabilities include translating older formats into GNDS, translating GNDS back to ENDF-6, and visualizing, modifying, checking, and processing GNDS data. It also states that a new version of FUDGE is coming soon. The plan is to support GNDS-2.0 specification, but it may be released sooner if v2.0 is delayed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Analysis of conical slump shape reconstructed from stereovision images for yield stress prediction

Highlights: • Conical slump model tends to underpredict yield stress of material by slump height. • Profiles of slumped materials were reconstructed from stereovision images. • Actual profiles were compared to those predicted by cone and cylinder model. • The cause of deviation lies in the cylinder-like behaviour of conical slumping. • The model of equivalent cylinder could give an accurate yield stress value. Slump cones are widely utilised to evaluate the workability of cement materials owing to their simplicity. Analytical models have been established to relate this empirical value to the yield stress. However, they tend to be less effective for the cone and more valid for cylinder slumps. The cause of this deviation is yet to be fully understood. In this work, more details were sought from slump profiles using stereovision technology. A direct comparison of the predicted shapes based on conical model as well as cylindrical model to actual shapes was undertaken. The visual illustration clearly indicated that conical slumping shows a cylinder-like behaviour, and the slumped shapes in cone tests agree well with those predicted by an equivalent cylinder. By converting to cylindrical dimensionless units, the conical slump height can provide an accurate yield stress. The results suggest that the theory is valid if the slumping behaviour is effectively assumed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

An Organic Semiconductor Organized into 3D DNA Arrays by “Bottom-up” Rational Design

Here, a 3D array of organic semiconductors was assembled using a DNA scaffold. An octameric aniline molecule (“octaniline”) was incorporated into a DNA building block based on a dimeric tensegrity triangle. The construct self-assembled to form a 3D crystal. Reversible redox conversion between the pernigraniline and leucoemeraldine states of the octaniline is retained in the crystal. Protonic doping gave emeraldine salt at pH 5, corresponding to the conductive form of polyaniline. Redox cycling within the crystal was visualized by color changes and Raman microscopy. The ease of conversion between the octaniline states suggests that it is a viable electronic switch within a unique 3D structure.

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

Molecular-Weight-Dependent Infiltration and Adsorption of Polymers into Nanochannels

The mesoporous silica shell coating hydrogenolysis nano-catalysts alters the molecular weight distributions of cleaved polymer chains compared to catalysts without a shell. The shell, composed of radially aligned narrow cylindrical nanopores, reduces the formation of low-valued gaseous products and increases the median molecular weight of the product, thus enhancing the value of the products for polymer upcycling. Here, to understand the role of the mesoporous shell, we have studied the spatial distribution of polystyrene chains, used as a model polymer, in the nanochannels in both the melt phase and solution phase. In the melt, we observed from small-angle X-ray scattering experiments that the infiltration rate of the polymer into the nanochannels is inversely proportional to the molecular weight, which is consistent with theory. In theta solution experiments using UV–vis spectroscopy, we found that the shell significantly enhances polymer adsorption compared to nanoparticles without pores. In addition, the degree of polymer adsorption is not a monotonic function of molecular weight but initially increases with the molecular weight before eventually decreasing. The molecular weight for the peak adsorption increases with the pore diameter. This adsorption behavior is rationalized as resulting from a balance between the mixing entropy gain by surface adsorption and the conformational entropy penalty incurred by chains confined in the nanochannels. The spatial distribution of polymer chains in the nanochannels is visualized by energy-dispersive X-ray spectroscopy (EDX), and inverse Abel-transformed data reveals a less uniform polymer distribution along the primary pore axis for longer chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗