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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Topological Magnets: Functions Based on Berry Phase and Multipoles

Macroscopic responses of magnets are often governed by magnetization and, thus, have been restricted to ferromagnets. However, such responses are strikingly large in the newly developed topological magnets, breaking the conventional scaling with magnetization. Taking the recently discovered antiferromagnetic (AF) Weyl semimetals as a prime example, we highlight the two central ingredients driving the significant macroscopic responses: the Berry curvature enhanced because of nontrivial band topology in momentum space, and the cluster magnetic multipoles in real space. The combination of large Berry curvature and multipoles enables large macroscopic responses such as the anomalous Hall and Nernst effects, the magneto-optical effect, and the novel magnetic spin Hall effect in antiferromagnets with negligible net magnetization, but also allows us to manipulate these effects by electrical means. Furthermore, nodal-point and nodal-line semimetallic states in ferromagnets may provide the strongly enhanced Berry curvature near the Fermi energy, leading to large responses beyond the conventional magnetization scaling. These significant properties and functions of the topological magnets lay the foundation for future technological development such as spintronics and thermoelectric technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Stabilized Nanocrystalline Alloys: The Intersection of Grain Boundary Segregation with Processing Science

Processing science for nanocrystalline metals has largely focused on far-from-equilibrium methods that can generate many grain boundaries with excess defect energy. Conversely, the science of stabilizing nanocrystalline alloys has largely focused on the lowering of that excess defect energy through grain boundary segregation, bringing nanocrystalline structures closer to equilibrium. With increasing technological adoption of stabilized nanocrystalline alloys, there is a substantial need for research at the intersection of these two fields. This review lays out the basic thermodynamic issues of the two subfields and surveys the literature on the most common processing methods, including severe plastic deformation, ball milling, physical vapor deposition, and electrodeposition. We provide an overview of studies that have examined grain boundary segregation through each of these methods and identify general themes. We conclude that there is substantial scope for more systematic work at the intersection of these fields to understand how nonequilibrium processing affects grain boundary segregation.

Materials Science↗
DOE OSTI2026

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗
DOE OSTI2022

IViz-OT (Intrusion Detection Visualizer for Operational Technology Network) [SWR-22-63]

The Visualizer dashboard provides grid operator highly-trusted alarming environment for an ongoing or potential cyber-attack based on system anomalies and network-based verification. Once anomalies are detected by the IDS tool (HIDES, NREL SWR-19-65), this platform stores the signatures or alert logs that are generated by the intrusion detector, lays out the detailed summary of the possible alerts, and maps these attacks with high-level scenarios. These scenarios are later combined to define a final event using a decision tree approach and a final report is generated out of this tool for further forensic analysis. It also supports authentication and authorization to support roles-based access control (RBAC) for users and a group of people.

Singh, Vivek Kumar↗
DOE OSTI2023

tih_vqe [SWR-23-32]

This software supports the paper, "Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules," published in the International Journal of Quantum Chemistry, whose abstract is as follows: Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods but are hypothesized to be the ideal use case for quantum computing. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately-sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near-term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near-term feasibility of modeling a molecule with d-orbitals on real quantum hardware. We demonstrate that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE+UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

Graf, Peter↗
DOE OSTI2022

Vessel Routing And Suitability Tool

The purpose of this tool is to assist harbor traffic controllers in routing vessel traffic into appropriate ports and piers in an emergency in the Hawaiian Islands. The user inputs information about a vessel coming to port, and the tool returns a list of appropriate options for the vessel to berth within the Hawaiian Islands. Additionally, the application can be used to store cargo data for tracking what locations can be used to lay down cargo in an emergency situation.

Reichenberger, RachelL.↗
DOE OSTI2026

Fortran mimetic abstraction language (Formal) v0.1.

The Fortran mimetic abstraction language ("Formal") is a domain-specific language (DSL) embedded in Fortran 202Y [1]. Formal provides novel software abstractions for simulating phenomena governed by the partial differential equations (PDEs) of vector and tensor calculus. Such equations model an extremely broad set of physical phenomena, ranging from atmospheric winds to light propagation. Formal's data structures and algorithms mimic in form and behavior continuous functions and operators. Formal supports these mathematical constructs using mimetic discretizations that define a discrete calculus satisfying various tensor calculus theorems, thereby ensuring high-fidelity representations of the physics being modeled. [2] Formal 0.1.0 also lays a foundation for the future use of Fortran 202Y type-safe templates to facilitate the formal verification of tensor contractions in computational physics and artificial intelligence [3]. [1] "Fortran 202Y" is Fortran standard committee's informal designation for the next Fortran revision, which will likely be "Fortran 2028". [2] Corbino, J. and Castillo, J. (2020) Journal of Computational and Applied Mathematics, https://doi.org/10.1016/j.cam.2019.06.042. [3] Haveraaen, M., Järvi, J., & Rouson, D. (2019). Reflecting on Generics for Fortran. https://j3-fortran.org/doc/year/19/19-188.pdf.

Rouson, Damian [Lawrence Berkeley National Laborat↗
DOE OSTI2023

Supporting Advancement in Weather and Water Prediction in the Upper Colorado River Basin: The SPLASH Campaign

Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Vibrational Spectroscopic Monitoring of the Gelation Transition in Nafion Ionomer Dispersions

Infrared and Raman spectroscopy techniques were applied to investigate the drying and aggregation behavior of Nafion ionomer particles dispersed in aqueous solution. Gravimetric measurements aided the identification of gel-phase development within a series of time-resolved spectra that tracked transformations of a dispersion sample during solvent evaporation. A spectral band characteristic of ionomer sidechain end group vibration provided a quantitative probe of the dispersion-to-gel change. For sets of attenuated total reflection Fourier transform infrared (ATR FT-IR) spectra, adherence to Beer's law was attributed to the relatively constant refractive index in the frequency region of hydrated –SO$^{–}_{3}$ group vibrations as fluorocarbon-rich ionomer regions aggregate in forming the structural framework of membranes and thin films. Although vibrational bands associated with ionomer backbone CF 2 stretching vibrations were affected by distortion characteristic of wavelength-dependent refractive index change within a sample, the onset of band distortion signaled gel formation and coincided with ionomer mass % values just below the critical gelation point for Nafion aqueous dispersions. Similar temporal behavior was observed in confocal Raman microscopy experiments that monitored the formation of a thin ionomer film from an individual dispersion droplet. For the ATR FT-IR spectroscopy and confocal Raman microscopy techniques, intensity in the water H–O–H bending vibrational band dropped sharply at the ionomer critical gelation point and displayed a time dependence consistent with changes in water content derived from gravimetric measurements. The reported studies lay groundwork for examining the impact of dispersing solvents and above-ambient temperatures on fluorinated ionomer transformations that influence structural properties of dispersion-cast membranes and thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coupling of the Liquid Sampling–Atmospheric Pressure Glow Discharge to Orbitrap Mass Analyzers for Uranium Isotope Ratio Analysis: Evolution of the Methodology and Implications to the Field

Just over a decade ago, a truly outside-of-the-box approach to isotope ratio mass spectrometry (IRMS) was undertaken between research groups at Clemson University and the Pacific Northwest National Laboratory. The original motivation dealt with projections as to whether or not microplasmas could be developed into practical elemental ionization sources, perhaps for transportable analysis applications. In particular, the use of the liquid sampling–atmospheric pressure glow discharge (LS-APGD) was pursued. Its interfacing to an ultra-high resolution Orbitrap platform, proved not only facile, but opened up a wealth of potential applications. Here, we lay out a historical, tutorial description of the interfacing and the evolution of the methodology regarding IRMS of uranium. Practical challenges and opportunities are described, which hopefully provide guidance to further applications in high resolution IRMS. It is hoped that, while detailed and lengthy, the didactic nature of the presentation provides experimental insights and tips, and also serves as an homage to our very good friend, Professor Gary M. Hieftje, whose scientific inspiration and comradery have been immeasurably important in our own careers.

Koppenaal, David W.↗
DOE OSTI2020

Linking crop traits to transcriptome differences in a progeny population of tetraploid potato

Background: Potato is the third most consumed crop in the world. Breeding for traits such as yield, product quality and pathogen resistance are main priorities. Identifying molecular signatures of these and other important traits is important in future breeding efforts. In this study, a progeny population from a cross between a breeding line, SW93–1015, and a cultivar, Désirée, was studied by trait analysis and RNA-seq in order to develop understanding of segregating traits at the molecular level and identify transcripts with expressional correlation to these traits. Transcript markers with predictive value for field performance applicable under controlled environments would be of great value for plant breeding.Results: A total of 34 progeny lines from SW93–1015 and Désirée were phenotyped for 17 different traits in a field in Nordic climate conditions and controlled climate settings. A master transcriptome was constructed with all 34 progeny lines and the parents through a de novo assembly of RNA-seq reads. Gene expression data obtained in a controlled environment from the 34 lines was correlated to traits by different similarity indices, including Pearson and Spearman, as well as DUO, which calculates the co-occurrence between high and low values for gene expression and trait. Our study linked transcripts to traits such as yield, growth rate, high laying tubers, late and tuber blight, tuber greening and early flowering. We found several transcripts associated to late blight resistance and transcripts encoding receptors were associated to Dickeya solani susceptibility. Transcript levels of a UBX-domain protein was negatively associated to yield and a GLABRA2 expression modulator was negatively associated to growth rate.Conclusion: In our study, we identify 100’s of transcripts, putatively linked based on expression with 17 traits of potato, representing both well-known and novel associations. This approach can be used to link the transcriptome to traits. We explore the possibility of associating the level of transcript expression from controlled, optimal environments to traits in a progeny population with different methods introducing the application of DUO for the first time on transcriptome data. We verify the expression pattern for five of the putative transcript markers in another progeny population.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ethanol tolerance in engineered strains of Clostridium thermocellum

Abstract Clostridium thermocellum is a natively cellulolytic bacterium that is promising candidate for cellulosic biofuel production, and can produce ethanol at high yields (75–80% of theoretical) but the ethanol titers produced thus far are too low for commercial application. In several strains of C. thermocellum engineered for increased ethanol yield, ethanol titer seems to be limited by ethanol tolerance. Previous work to improve ethanol tolerance has focused on the WT organism. In this work, we focused on understanding ethanol tolerance in several engineered strains of C. thermocellum . We observed a tradeoff between ethanol tolerance and production. Adaptation for increased ethanol tolerance decreases ethanol production. Second, we observed a consistent genetic response to ethanol stress involving mutations at the AdhE locus. These mutations typically reduced NADH-linked ADH activity. About half of the ethanol tolerance phenotype could be attributed to the elimination of NADH-linked activity based on a targeted deletion of adhE . Finally, we observed that rich growth medium increases ethanol tolerance, but this effect is eliminated in an adhE deletion strain. Together, these suggest that ethanol inhibits growth and metabolism via a redox-imbalance mechanism. The improved understanding of mechanisms of ethanol tolerance described here lays a foundation for developing strains of C. thermocellum with improved ethanol production.

09 BIOMASS FUELS↗
DOE OSTI2023

Highly diverse and unknown viruses may enhance Antarctic endoliths’ adaptability

Abstract Background Rock-dwelling microorganisms are key players in ecosystem functioning of Antarctic ice free-areas. Yet, little is known about their diversity and ecology, and further still, viruses in these communities have been largely unexplored despite important roles related to host metabolism and nutrient cycling. To begin to address this, we present a large-scale viral catalog from Antarctic rock microbial communities. Results We performed metagenomic analyses on rocks from across Antarctica representing a broad range of environmental and spatial conditions, and which resulted in a predicted viral catalog comprising > 75,000 viral operational taxonomic units (vOTUS). We found largely undescribed, highly diverse and spatially structured virus communities which had predicted auxiliary metabolic genes (AMGs) with functions indicating that they may be potentially influencing bacterial adaptation and biogeochemistry. Conclusion This catalog lays the foundation for expanding knowledge of virosphere diversity, function, spatial ecology, and dynamics in extreme environments. This work serves as a step towards exploring adaptability of microbial communities in the face of a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving inverse Compton sources by avoiding non-linearities

We present a new, more nuanced understanding of non-linear effects in inverse Compton sources. Deleterious non-linear effects can arise even at low laser intensities, a regime previously viewed as linear. After laying out a survey of non-linear phenomena which degrade the effectiveness of inverse Compton sources, we discuss two powerful techniques designed to avoid these non-linearities. Starting with the known technique of non-linear longitudinal chirping of the laser pulse in the high laser field regime, we show that the simple stretching of the laser pulse, while keeping the energy constant, can significantly increase the spectral density of the scattered radiation in many operating regimes. Our numerical simulations show that combining these two techniques avoids detrimental non-linearities and improves the performance of inverse Compton sources over an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantum search on noisy intermediate-scale quantum devices

Abstract Quantum search algorithm (also known as Grover's algorithm) lays the foundation for many other quantum algorithms. Although it is very simple, its implementation is limited on noisy intermediate-scale quantum (NISQ) processors. Grover's algorithm was designed without considering the physical resources, such as depth, in the real implementations. Therefore, Grover's algorithm can be improved for NISQ devices. In this paper, we demonstrate how to implement quantum search algorithms better on NISQ devices. We present detailed benchmarks of the five-qubit quantum search algorithm on different quantum processors, including IBMQ, IonQ, and Honeywell quantum devices. We report the highest success probability of the five-qubit search algorithm compared to previous works. Our results show that designing the error-aware quantum search algorithms is possible, which can maximally harness the power of NISQ computers.

Physics↗
DOE OSTI2023

Data for Application of Time-Domain 1H NMR for Investigating Dynamics of Vegetative Lipids in Bioenergy Crops at Different Developmental Stages

Sweet sorghum is typically cultivated for the food and fodder market. Recently, sweet sorghum varieties are being metabolically transitioned to enhance energy density by accumulating oil droplets in their vegetative tissues for bioenergy applications. Owing to the high biomass yield of sorghum, the transgenic lines can compete with oil-seed crops for biodiesel yield per unit area. In the initial phase of transgenic development, a high-throughput phenotyping method can bridge the gap between the production pipeline and analysis to improve the efficiency of the process. To meet the requirement, the present study extends the application of time-domain 1H-NMR spectroscopy for rapid quantification and characterization of the total in-situ lipids of sweet sorghum ‘ramada’ to lay the groundwork for analyzing the upcoming large quantity of transgenic samples. NMR technology has been successfully established for analyzing lipid contents of vegetative tissues of non-transgenic variety. The multiexponential analysis of spin-lattice (T1) relaxation spectra obtained from TD-NMR aided the investigation of the dynamics of the free and bound lipid fraction with plant development. The total lipid concentration of bagasse and leaves of non-transgenic sweet sorghum remained unchanged throughout the plant development. Leaves displayed a higher percentage of bound lipids as compared to bagasse. A significant variation in the lipid concentration of juice was observed at the different growth stages with a maximum lipid accumulation of 1.21 ± 0.04% w/w at the boot stage that decreased with further maturity of the plant.

Biomass Analytics↗
DOE OSTI2023

Anomaly Detection and Identification Using a Leave-One-Variable-Out Method

At nuclear power plants (NPPs), anomaly detection and identification (i.e., determining the causes of anomalies) are important tasks for ensuring the safe and efficient operation of NPPs. These tasks are currently labor-intensive and costly, and are made more difficult by the size and complexity of NPP systems. An alternative approach to conducting these tasks is to automate them, such as via the reconstruction-based contribution method, which is a well-researched unsupervised machine learning method that uses a data-driven model of anomaly-free behavior to detect events and then identify each variable’s contributions to those events. The present effort developed a novel contribution approach that utilized a leave-one-variable-out (LOVO) model, with which each variable is predicted using all the other variables. The novelty lay in transforming this model into a reconstruction model and modifying the identification algorithm to work with the new reconstruction model. To evaluate this method in a controlled environment, a synthetic dataset based on spring-mass-damper (SMD) systems (commonly found in mechanical engineering references) was used, with known anomalies introduced into the system. The proposed method successfully detected the anomalies and afforded insights into their causes, thus enabling the appropriate identifications to be made.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗