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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 OSTI2024

Integration of Rucio Metadata in Belle II

Rucio is a Data Management software that has become a de-facto standard in the HEP community and beyond. It allows the management of large volumes of data over their full lifecycle. The Belle II experiment located at KEK (Japan) recently moved to Rucio to manage its data over the coming decade (O(10) PB/year). In addition to its Data Management functionalities, Rucio also provides support for storing generic metadata. Rucio metadata already provides accurate accounting of the data stored all over the sites serving Belle II. Annotating files with generic metadata opens up possibilities for finer-grained metadata query support. We will first introduce some of the new developments aimed at providing good performance that were done to cover Belle II use-cases like bulk insert methods, metadata inheritance, etc. We will then describe the various tests performed to validate Rucio generic metadata at Belle II scale (O(100M) files), detailing the import and performance tests that were made.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Customizable Metric to Provide a Comprehensive Picture of the Mobility Potential of a Location

Accessibility in a geo-spatial context refers to the ease of reaching a variety of opportunities from a given location. Accessibility theories (and resulting metrics) have traditionally focused on quantifying access to specific opportunities (such as jobs), or focused on specific modes (such as car, bike, etc.). Such approaches often fall short of providing a comprehensive picture of the true accessibility potential of a location as a combination of multiple modes to multiple types of destinations. Addressing this drawback, a novel metric labeled the ‘Mobility Energy Productivity (MEP) Metric’ was developed at the National Renewable Energy Laboratory to quantify the mobility potential of a location to connect people to goods, services, and employment using a variety of modes, while accounting for time, energy, and affordability. The MEP metric has been integrated with advance travel behavior models to compute the changes in mobility potential for various future scenarios, such as introduction of automated vehicles, and/or electric vehicles—but does so at the aggregate, or average-citizen level. The MEP in its initial iteration is not customized to the particular socio-economic contingents, or even to an individual whose modal availability or pattern of trip making may substantially differ from the average. Addressing this gap, this research effort extends the MEP framework from a static state to a more tailored and dynamic state, one in which an individual, or group can customize the metric for their unique characteristics, such as modes, activity patterns, and time-of-day preferences. The extended MEP metric framework can now be integrated to assess the customized mobility energy productivity of an individual.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Life Cycle Assessment and Life Cycle Cost Analysis of Repurposing Decommissioned Wind Turbine Blades as High-Voltage Transmission Poles

Wind energy is widely deployed and will likely grow in service of reducing the world’s dependency on fossil fuels. The first generation of wind turbines are now coming to the end of their service lives, and there are limited options for the reuse or recycling of the composite materials they are made of. Current literature has verified that there is no existing recycling pathway (i.e., mechanical, chemical, thermal methods of recovery, etc.) for end-of-life materials in wind blades that can meet cost parity with landfilling in the US. However, to the authors’ knowledge there is no study to date that uncovers the cost structures associated with repurposing wind turbine blades in the US. Repurposing could offer a cost-competitive advantage through displacement of higher-value products, rather than materials or chemical constituents alone. This study implements life cycle assessment (LCA) and life cycle cost analysis (LCC) to assess the environmental and financial implications at each stage of repurposing wind turbine blades as the primary load-carrying elements for high-voltage transmission line structures in the United States. This case study contribution to knowledge is based on the successful management of construction waste by analyzing an application for repurposing construction demolition waste. Specifically, this study presents an environmental and financial analysis of repurposing wind turbine blades as transmission line poles. Under this case study, our results show that BladePoles have lower greenhouse gas emissions than steel poles, and we anticipate BladePoles will be less costly than steel poles. Overall emissions are most sensitive to combustion emissions, driven primarily by transportation distance and hours of required crane operations during the installation process. Compared to other evaluated recycling methods, repurposing wind blades as BladePoles has the least overall global warming potential.

42 ENGINEERING↗
DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prediction of impact sensitivity, heat of formation and heat of explosion using atomic connectivity

In these proceedings we revisit a large collection of explosives and explosive descriptors with the goal of predicting impact sensitivity using only local atomic environments that can be deciphered from molecular SMILES strings as descriptors without utilizing empirically measured values or computationally expensive electronic structure calculations. From the original database of nearly 500 descriptors, removing empirically measured and electronic structure values decreased the number of descriptors to 135, which we reduced to 18 the most important descriptors using Random Forests. The condensed model predicted impact sensitivity with essentially the same accuracy as the existing, more complex model (R 2 = 0.788 and RSME = 0.312), while remaining applicable to all types of explosives (Peroxides, azides, C-Nitros, Nitroamines, Nitrate Esters, etc.). In addition to impact sensitivity, we proposed similar models to accurately predict values heat of formation (ΔH f ) and heat of explosion (Q), with R 2 = 0.966 and 0.916, respectively. In conclusion, the work in these proceedings allows for prediction of explosive performance and sensitivity with only chemical structure information and an estimate of density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Subsurface spectroscopy of heterogeneous materials using optical wavefront shaping

Plastic-bonded explosives and propellants consist of energetic molecular crystals embedded in a polymer matrix that also includes additives, such as taggants, plasticizers, grit, antioxidants, etc. Furthermore, this heterogeneous composition renders these materials optically opaque, limiting optical characterization techniques (e.g., Raman spectroscopy) to probing chemical reactions at the sur-face. However, many reactions of interest are believed to occur inside the material where current optical techniques can not probe. To address this challenge, we have developed a new optical technique that utilizes feedback assisted wavefront shaping (using spatial light modulators) to focus probe light inside a heterogeneous material, such that we can perform subsurface spectroscopy. Recently, we demonstrated this technique by monitoring subsurface photodegradation and thermal degradation of Eu-doped molecular crystals using both fluorescence and Raman spectroscopy. Based off these successes we are now looking into improvements to this technique to allow for greater time resolution, including replacing our spatial light modulators with fast digital mirror devices, using ns optical phase conjugation, and self-healing optical beams.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Catalytic properties of model supported nanoparticles

Nanoparticles of late transition metals are used as catalysts and electrocatalysts for industrial chemical reactions that produce fuels, convert chemical energy to electricity and clean up pollution associated with the generation and use of these fuels. For such applications, metals are usually bonded onto the surfaces of oxide or carbon support materials. To provide the energy needed for sustained economic development, we must develop new and improved solid catalysts and electrocatalysts for a variety of reactions that take better advantage of traditional and alternate energy sources (solar, wind, biomass, etc.) and avoid serious environmental problems. Additionally, since these metals are often expensive and in limited supply (e.g., Pt), we also need to develop catalysts that do not require precious metals. As a consequence, recent years have seen a dramatic increase in research aimed at providing the basic understanding needed to develop new and improved catalysts and electrocatalysts for a variety of reactions that involve nanoparticles of late transition metals supported on oxide or carbon materials. It is therefore timely to present a special issue that focusses on Catalytic Properties of Model Supported Nanoparticles. The collection highlights some of the most exciting new directions for research in this area, and provides in depth examples of some of the most cutting-edge methods, both experimental and theoretical, for studying this class of catalysts, which provide insights into structure, mechanisms, kinetics and energetics with unprecedented accuracy and detail. Finally, as Guest Editors, we present below a few of the many excellent papers published in the collection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Guided search for desired functional responses via Bayesian optimization of generative model: Hysteresis loop shape engineering in ferroelectrics

Advances in theoretical modeling across multiple disciplines have yielded generative models capable of high veracity in predicting macroscopic functional responses of materials emerging as a result of complex non-local interactions. Correspondingly, of interest is the inverse problem of finding the model parameter that will yield desired macroscopic responses, such as stress–strain curves, ferroelectric hysteresis loops, etc. Here, we suggest and implement Gaussian process based methods that allow to effectively sample the degenerate parameter space of a complex non-local model to output regions of parameter space which yield desired functionalities. In this work, we discuss the specific adaptation of the acquisition function and sampling function to make the process efficient and balance the efficient exploration of parameter space for multiple possible minima and exploitation to densely sample the regions of interest where target behaviors are optimized. Additionally, this approach is illustrated via the hysteresis loop engineering in ferroelectric materials but can be adapted to other functionalities and generative models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Predictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization behaviors in multiferroic Sm-doped BiFeO 3

The predictability of a certain effect or phenomenon is often equated with the knowledge of relevant physical laws, typically understood as a functional or numerically derived relationship between the observations and known states of the system. Correspondingly, observations inconsistent with prior knowledge can be used to derive new knowledge on the nature of the system or indicate the presence of yet unknown mechanisms. In this work, we explore the applicability of Gaussian processes (GP) to establish predictability and uncertainty of local behaviors from multimodal observations, providing an alternative to this classical paradigm. Using atomic resolution scanning transmission electron microscopy (STEM) of multiferroic Sm-doped BiFeO 3 across a broad composition range, we directly visualize the atomic structure and structural, physical, and chemical order parameter fields for the material. GP regression is used to establish the predictability of the local polarization field from different groups of parameters, including the adjacent polarization values and several combinations of physical and chemical descriptors, including lattice parameters, column intensities, etc. We observe that certain elements of microstructure, including charged and uncharged domain walls and interfaces with the substrate, are best predicted with specific combinations of descriptors, and this predictability and associated uncertainties are consistent across the composition series. The associated generative physical mechanisms are discussed. It is also found that certain parameter combinations tend to predict the orthorhombic phase in the cases where rhombohedral phase is observed, suggesting a potential role of clamping and confinement phenomena in phase equilibrium in Sm-BiFeO 3 system close to morphotropic phase boundary. We argue that predictability and uncertainty in observational data offer a new pathway to probe the physics of condensed matter systems from multimodal local observations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Servo-aero-gravo-elastic (SAGE) scaling and its application to a 13-MW downwind turbine

Reduced scale wind turbines can be extremely cost-effective to test new rotor concepts since prototype costs are heavily dependent on the rotor diameter. Ideally, the scaled model would have the same non-dimensional deflections, dynamics, and control behavior as the full-scale model. This would provide a high-fidelity demonstration of the full-scale performance, which is ideal if the full-scale turbine has significant aeroelastic interactions. To this end, servo-aero-gravo-elastic (SAGE) scaling is developed and applied to a 13-MW turbine that is scaled to a 20% scale model. The scaling preserves the tip-speed ratio, the rotor speed normalized by the flapping frequency, and the tip deflections normalized by the blade length. In addition, the controller employs the same control structure (gain-scheduled pitch control and variable speed torque control) and is scaled dynamically (e.g., matching non-dimensional time constant of the pitch angle, etc.). Furthermore, the thrust, gravity, and centrifugal moments are scaled such that the load angles are preserved as a function of a non-dimensional wind speed. However, the environmental scaling must consider differences in Reynolds number (since this parameter cannot be held constant) and subsequent changes in the axial induction factor. While the presented results showcase these differences during operational conditions, the non-dimensional tip deflections remain comparable through all wind speed ranges, indicating the viability of the SAGE scaling method in matching full-scale aeroelastic responses.

Kaminski, Meghan (ORCID:0000000322334784)↗
DOE OSTI2020

Binding and excitations in Si x H y molecular systems using quantum Monte Carlo

In this work, we present high-accuracy correlated calculations of small SixHy molecular systems in both the ground and excited states. We employ quantum Monte Carlo (QMC) together with a variety of many-body wave function approaches based on basis set expansions. The calculations are carried out in a valence-only framework using recently derived correlation consistent effective core potentials. Our primary goal is to understand the fixed-node diffusion QMC errors in both the ground and excited states with single-reference trial wave functions. Using a combination of methods, we demonstrate the very high accuracy of the QMC atomization energies being within ≈0.07 eV or better when compared with essentially exact results. By employing proper choices for trial wave functions, we have found that the fixed-node QMC biases for total energies are remarkably uniform ranging between 1% and 3.5% with absolute values at most ≈0.2 eV across the systems and several types of excitations such as singlets and triplets as well as low-lying and Rydberg-like states. Our results further corroborate that Si systems, and presumably also related main group IV and V elements of the periodic table (Ge, Sn, etc), exhibit some of the lowest fixed-node biases found in valence-only electronic structure QMC calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A new era in ferroelectrics

Topological structures in ferroic materials have drawn great interest in recent years due to the richness of the underlying physics and the potential for applications in next generation electronics. Recent advances in atomically precise thin-film materials synthesis and characterization of structural/physical phenomena at unprecedented length/energy/time scales have enabled us to study exotic phases and their associated physics [Rößler et al., Nature 442, 797 (2006); S. Das, Nature 568, 368 (2019); Yadav et al., Nature 530, 198 (2016); and Stoica et al., Nat. Mater. 18, 377 (2019)]. It is appropriate that, in the second century of ferroelectrics, some dramatic discoveries are propelling the field into directions heretofore unimaginable. In this review, we explore the recent progress in ferroelectric-oxide superlattices in which researchers can control structure and physical properties through the application of epitaxial strain, layer thickness, temperature, electric field, etc. We provide a discussion of exotic topological structures (e.g., closure domains, vortices, polar skyrmions, and other exotic phases) and associated functionalities in ferroelectric/paraelectric superlattices. We conclude with a brief overview of and prospects for how the field may evolve in the coming years.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New, improved analysis of correlation ECE data to accurately determine turbulent electron temperature spectra and magnitudes (invited)

Turbulent electron temperature fluctuation measurement using a correlation electron cyclotron emission (CECE) radiometer has become an important diagnostic for studying energy transport in fusion plasmas, and its use is widespread in tokamaks (DIII-D, ASDEX Upgrade, Alcator C-Mod, Tore Supra, EAST, TCV, HL-2A, etc.). The CECE diagnostic typically performs correlation analysis between two closely spaced (within the turbulent correlation length) ECE channels that are dominated by uncorrelated thermal noise emission. This allows electron temperature fluctuations embedded in the thermal noise to be revealed and fluctuation level and spectra determined. We have demonstrated a new, improved CECE coherency-based analysis for calculating the temperature fluctuation frequency spectrum and level, which has been verified both numerically through the simulation of synthetic ECE radiometer data and through analysis of experimental data from the CECE system on DIII-D. The new formulation places coherency-based analysis on a firm foundational footing and corrects some currently published methodologies. This new method accurately accounts for bias error in the coherence function and correctly calculates noise levels for a fixed data record length. It provides excellent accuracy in determining temperature fluctuation level (e.g., <10% error) even for a small realization number in the ensemble average. The method also has a smaller uncertainty (i.e., error bar) in the power spectrum when compared to the more standard cross-power method when evaluated at low coherency. Direct calculation of system noise level using correlation between randomized intermediate frequency signals is recommended.

Wang, G. (ORCID:0000000225739827)↗
DOE OSTI2022

High-throughput, in situ imaging of multi-layer powder-blown directed energy deposition with angled nozzle

Laser metal additive manufacturing (AM) has become an increasingly popular technology due to its flexibility in geometry and materials. As one of the commercialized additive processes, powder-blown directed energy deposition (DED) has been used in multiple industries such as aerospace, automotive, medical device, etc. However, a lack of fundamental understanding remains for this process, and many opportunities for alloy development and implementation can be identified. A high-throughput, in situ DED system capable of multi-layer builds that can address these issues is presented here. In this work, implications of layer heights and energy density are investigated through an extensive process parameter sweep, showcasing the power of a high-throughput setup while also discussing multi-layer interactions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Digging deeper: Buried layers and interfaces studied by modified total electron yield and soft x-ray absorption spectroscopy

We report on the soft x-ray absorption spectroscopy investigation of thin film capacitors using a modified total electron yield detection mode. This mode utilizes two ammeters instead of one as commonly employed in the classical total electron yield scheme to measure photocurrents of devices under soft x-ray irradiation. The advantage of this configuration over the surface sensitive classical total electron yield mode is that it can provide information from buried layers and interfaces up to a thickness equal to the penetration depth of soft x-rays. The method can be easily adapted to existing synchrotron end stations. We investigate dielectric capacitors with dissimilar electrodes to assess the feasibility of the modified total electron yield method. Furthermore, in operando soft x-ray absorption spectroscopy measurements are performed on ferroelectric capacitors under bias and using two ammeters. The experimental results are discussed in terms of the external and internal photoemission processes and their distribution in thin film capacitors under an external bias condition. The proposed detection method opens the way to perform electronic and chemical state analyses of the buried interfaces and layers in various devices like multiferroic tunnel junctions, memristive devices, etc., during operation under an applied bias.

Kröger, E.↗
DOE OSTI2022

Evaluation of thermodynamic closure models for partially reacted two-phase mixture of condensed phase explosives

One of the key fundamental issues that is crucial in the continuum modeling of reactive flow phenomena is the thermodynamically consistent description of reaction mixture properties. To define the mixture properties, thermodynamic closure rules that relate the properties of the individual reaction components to the mixture properties are required. In the context of reactive two-phase modeling approaches, various strategies to define the thermodynamic closures have been adopted such as pressure temperature (PT) equilibrium between the individual reaction components, pressure (specific) volume (PV) equilibrium, etc. The choice of closure rules determines the relative distribution of specific volume and energy across the reaction components that comprise the mixture. Therefore, depending on the choice of the closure, the mixture thermodynamic behavior can vary. The present work examines the effect of different closure approaches on the thermodynamic properties of the reaction mixture. The analysis is performed for a condensed phase HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) based plastic bonded explosive (PBX) 9501 explosive using four different thermodynamic closures, viz., PT equilibrium, PV equilibrium, volume temperature (VT) equilibrium, and pressure (P) equilibrium with reactants on an isentrope. Furthermore, the relative variations in the thermodynamic properties of the mixture are analyzed and compared under both compression and expansion loading regimes. It is shown that out of the four closure models, only PT equilibrium and P equilibrium closures lead to a thermodynamically accurate description of the mixture under both compression and expansion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Breaking covalent bonds in the context of the many-body expansion (MBE). I. The purported “first row anomaly” in XH n (X = C, Si, Ge, Sn; n = 1–4)

We present a new, novel implementation of the Many-Body Expansion (MBE) to account for the breaking of covalent bonds, thus extending the range of applications from its previous popular usage in the breaking of hydrogen bonds in clusters to molecules. A central concept of the new implementation is the in situ atomic electronic state of an atom in a molecule that casts the one-body term as the energy required to promote it to that state from its ground state. The rest of the terms correspond to the individual diatomic, triatomic, etc., fragments. Its application to the atomization energies of the XH n series, X = C, Si, Ge, Sn and n = 1–4, suggests that the (negative, stabilizing) 2-B is by far the largest term in the MBE with the higher order terms oscillating between positive and negative values and decreasing dramatically in size with increasing rank of the expansion. The analysis offers an alternative explanation for the purported “first row anomaly” in the incremental H n–1 X–H bond energies seen when these energies are evaluated with respect to the lowest energy among the states of the XH n molecules. Due to the “flipping” of the ground/first excited state between CH 2 ( 3 B 1 ground state, 1 A 1 first excited state) and XH 2 , X = Si, Ge, Sn ( 1 A 1 ground state, 3 B 1 first excited state), the overall picture does not exhibit a “first row anomaly” when the incremental bond energies are evaluated with respect to the molecular states having the same in situ atomic states.

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

All-dielectric magneto-photonic metasurfaces

All-dielectric metasurfaces have been attracting much attention. Low optical losses and a huge variety of optical modes provide unique possibilities for light manipulation at the nanoscale. Recent studies showed that the magneto-optical effects in such metasurfaces are enormously enhanced. Moreover, it is possible to observe novel magneto-optical effects that are absent in smooth films. Excitation of particular photonic resonances makes it possible to design the magneto-optical interaction by the metasurface design. This opens up broad opportunities for magneto-photonic metasurface applications, including optomagnetism, light modulation, sensing, magnetometry, etc.

Ignatyeva, Daria O.↗