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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 sources NASA NTRS DOE OSTI

DOE OSTI2023

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

DancePartner: Python Package to Mine Multiomics Relationship Networks from Literature and Databases

A goal of multi-omics experiments is to understand how mechanistic molecular biology is altered between conditions, typically a control group and experimental groups. Oftentimes this involves studying changes in biomolecule relationships (e.g. interactions, metabolic relationships) of several types of biomolecules (e.g. proteins, lipids, metabolites). Though several databases contain relationships between biomolecules, understudied species may have little to no relationship information in databases and thus must be mined from literature. There are several challenges to literature mining, including automated full-text extraction, duplicate biomolecule term collapsing, and implementing complex machine learning tools. To make relationship extraction more accessible to the community, a python package called DancePartner was developed to allow for the extraction of relationships from literature and databases, with functions to map biomolecule synonyms to standardized identifiers and visualize and characterize the resulting multi-omics network. Here, in this study, an example dataset involving Caenorhabditis elegans is presented, where relationships are mined from 1443 publications using DancePartner. These relationships are combined with relationships from KEGG, WikiPathways, UniProt, and LipidMaps, and visualized.

BERT↗

DOE OSTI2021

Visualization of Fast Ion Phase-Space Flow Driven by Alfvén Instabilities

Fast ion phase-space flow, driven by Alfven eigenmodes (AEs), is measured by an imaging neutral particle analyzer in the DIII-D tokamak. The flow firstly appears near the minimum safety factor at the injection energy of neutral beams, and then moves radially inward and outward by gaining and losing energy, respectively. The flow trajectories in phase space align well with the intersection lines of the constant magnetic moment surfaces and constant E – (ω/n)P ζ surfaces, where E, P ζ are energy and toroidal canonical momentum of ions; ω and n are angular frequencies and toroidal mode numbers of AEs. It is found that the flow is so destructive that the thermalization of fast ions is no longer observed in regions of strong interaction. Here, the measured phase-space flow is consistent with nonlinear hybrid kinetic-magnetohydrodynamics simulation. Calculations of the relatively narrow phase-space islands reveal that fast ions must transition between different flow trajectories to experience large-scale phase-space transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Visualization and quantum control of light-accelerated condensates by terahertz multi-dimensional coherent spectroscopy

Abstract Characterizing and controlling high-order correlation of quantum systems is key for developing quantum devices and switching technologies. Although conventional static and ultrafast spectroscopy gives access to collective excitations characterizing quantum states, more exotic correlations cannot be easily separated from other contributions. Here we develop density matrix simulations to show that seventh-order-wave-mixing peaks with distinct temperature and field dependences in two-dimensional terahertz nonlinear spectra reveal light-induced correlations in non-equilibrium superconducting states. Above critical terahertz driving, these emerging peaks split from conventional peaks along the second axis introduced by pump-probe relative phase in two-dimensional frequency space. They are photo-generated by correlations between two-photon fluctuations and interacting quasi-particle and quasi-particle/Higgs superconductor excitations. By photo-inducing persistent symmetry breaking via light-wave propagation, we also demonstrate seventh-order-wave-mixing sensing of Higgs collective modes. Our theory suggests to use multi-dimensional spectroscopy for quantum sensing of light-driven superconductivity and paves a path for quantum operations by few-cycle-THz-periodic photocurrent modulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Mulayim, Ozan Baris↗

DOE OSTI2022

Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A Guide to Conquer the Biological Network Era Using Graph Theory

Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

In situ nanoscale imaging of moiré superlattices in twisted van der Waals heterostructures

Abstract Direct visualization of nanometer-scale properties of moiré superlattices in van der Waals heterostructure devices is a critically needed diagnostic tool for study of the electronic and optical phenomena induced by the periodic variation of atomic structure in these complex systems. Conventional imaging methods are destructive and insensitive to the buried device geometries, preventing practical inspection. Here we report a versatile scanning probe microscopy employing infrared light for imaging moiré superlattices of twisted bilayers graphene encapsulated by hexagonal boron nitride. We map the pattern using the scattering dynamics of phonon polaritons launched in hexagonal boron nitride capping layers via its interaction with the buried moiré superlattices. We explore the origin of the double-line features imaged and show the mechanism of the underlying effective phase change of the phonon polariton reflectance at domain walls. The nano-imaging tool developed provides a non-destructive analytical approach to elucidate the complex physics of moiré engineered heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Ion complexation waves emerge at the curved interfaces of layered minerals

Abstract Visualizing hydrated interfaces is of widespread interest across the physical sciences and is a particularly acute need for layered minerals, whose properties are governed by the structure of the electric double layer (EDL) where mineral and solution meet. Here, we show that cryo electron microscopy and tomography enable direct imaging of the EDL at montmorillonite interfaces in monovalent electrolytes with ångstrom resolution over micron length scales. A learning-based multiple-scattering reconstruction method for cryo electron tomography reveals ions bound asymmetrically on opposite sides of curved, exfoliated layers. We observe conserved ion-density asymmetry across stacks of interacting layers in cryo electron microscopy that is associated with configurations of inner- and outer-sphere ion-water-mineral complexes that we term complexation waves. Coherent X-ray scattering confirms that complexation waves propagate at room-temperature via a competition between ion dehydration and charge interactions that are coupled across opposing sides of a layer, driving dynamic transitions between stacked and aggregated states via layer exfoliation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Liquid-to-gas transfer of sodium in a liquid cathode glow discharge

Abstract Plasma-liquid interactions have been extensively studied with a focus on the transport of reactive species from the plasma to the liquid phase and their induced liquid phase chemistry and resulting applications. While solute transfer from the liquid to the gas phase in plasmas has been widely used in analytical chemistry, the underlying processes remain relatively unexplored. We report spatially and temporally resolved absolute density measurements of sodium in a plasma with a NaCl solution cathode using two-photon absorption laser induced fluorescence (TaLIF). The observed non-linear increase in sodium density with solution conductivity is shown to correlate with droplet generation as visualized by Mie scattering. The findings are explained by droplet generation by electrospray induced by Taylor cone formation as underpinning mechanism for the introduction of sodium in the plasma. An analytical sheath model combined with a scaling law shows an increase in electric field force with solution conductivity that is consistent with the observed non-linear increase in sodium density in the plasma with solution conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Delamination-Assisted Ultrafast Wrinkle Formation in a Freestanding Film

Freestanding films provide a versatile platform for materials engineering thanks to additional structural motifs not found in films with a substrate. A ubiquitous example is wrinkles, yet little is known about how they can develop over as fast as a few picoseconds due to a lack of experimental probes to visualize their dynamics in real time on the nanoscopic scale. Here, we use time-resolved electron diffraction to directly observe light-activated wrinkling formation in freestanding La 2/3 Ca 1/3 MnO 3 films. Via a “lock-in” analysis of oscillations in the diffraction peak position, intensity, and width, we quantitatively reconstructed how wrinkles develop on the time scale of lattice vibration. Contrary to the common assumption of fixed boundary conditions, we found that wrinkle development is associated with ultrafast delamination at the film boundaries. Finally, our work provides a generic protocol to quantify wrinkling dynamics in freestanding films and highlights the importance of the film–substrate interaction in determining the properties of freestanding structures.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

DOE OSTI2020

Differences in fine particle chemical composition on clear and cloudy days

Clouds are prevalent and alter fine particulate matter (PM 2.5 ) mass and chemical composition. Cloud-affected satellite retrievals are subject to higher uncertainty and are often removed from data products, hindering quantitative estimates of tropospheric chemical composition during cloudy times. We examine surface PM 2.5 chemical constituent concentrations in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network in the United States during cloudy and clear-sky times defined using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud flags from 2010 to 2014 with a focus on differences in particle species that affect hygroscopicity and aerosol liquid water (ALW). Cloudy and clear-sky periods exhibit significant differences in PM 2.5 mass and chemical composition that vary regionally and seasonally. In the eastern US, relative humidity alone cannot explain differences in ALW, suggesting that emissions and in situ chemistry related to anthropogenic sources exert determining impacts. An implicit clear-sky bias may hinder efforts to quantitatively understand and improve representation of aerosol–cloud interactions, which remain dominant uncertainties in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Visualizing subcellular rearrangements in intact β cells using soft x-ray tomography

Characterizing relationships between cell structures and functions requires mesoscale mapping of intact cells showing subcellular rearrangements following stimulation; however, current approaches are limited in this regard. Here, we report a unique application of soft x-ray tomography to generate three-dimensional reconstructions of whole pancreatic β cells at different time points following glucose-stimulated insulin secretion. Reconstructions following stimulation showed distinct insulin vesicle distribution patterns reflective of altered vesicle pool sizes as they travel through the secretory pathway. Our results show that glucose stimulation caused rapid changes in biochemical composition and/or density of insulin packing, increased mitochondrial volume, and closer proximity of insulin vesicles to mitochondria. Costimulation with exendin-4 (a glucagon-like peptide-1 receptor agonist) prolonged these effects and increased insulin packaging efficiency and vesicle maturation. This study provides unique perspectives on the coordinated structural reorganization and interactions of organelles that dictate cell responses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Spin–Orbit Natural Transition Orbitals and Spin-Forbidden Transitions

Natural transition orbitals (NTOs) are in widespread use for visualizing and analyzing electronic transitions. Here, the present work introduces the analysis of formally spin-forbidden transitions with the help of complex-valued spin-orbit (SO) NTOs. The analysis specifically focuses on the components in such transitions that cause their intensity to be non-zero because of SO coupling. Transition properties such as transition dipole moments are partitioned into SO-NTO hole-particle pairs, such that contributions to the intensity from specific occupied and unoccupied orbitals are obtained. The method has been implemented within the restricted active space (RAS) self-consistent field wave function theory framework, with SO coupling treated by RAS state interaction. SO-NTOs have a broad range of potential applications, which is illustrated by the T 2 -S 1 state mixing in pyrazine, spin-forbidden vs. spin-allowed 4f–5d transitions in the Tb 3+ ion, and the phosphorescence of tris(2-phenylpyridine) iridium [Ir(ppy) 3 ].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗