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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 1,117 records · Page 62

Reversible Disorder-to-Order Transition Induced by Aqueous Lithiation in Vanadate Electrode Materials

Vanadium-based oxides are intriguing electrode materials in aqueous electrochemical systems owing to their low cost and high theoretical capacity for alkali storage, especially lithium (Li) ions. However, a sequence of phase transformations and irreversible structure distortion upon Li-ion intercalation causes structural instability and has been a lingering problem for vanadium oxide electrodes. Here, in this work, we investigate lithium vanadate (Li–V 3 O 8 ) for aqueous Li-ion intercalation and deintercalation processes. Unlike its crystalline V 2 O 5 polymorph, Li–V 3 O 8 retains monophasic lithiation, which is attributed to its disordered crystalline nature and large interplanar distance. Importantly, we show a unique and reversible sequence of disorder-to-order structural transition induced by the extent of lithiation, which indicates sequential interlayer and intralayer lithiation process, and vice versa in delithiation process, supported by electrokinetic analysis, in situ X-ray diffraction (XRD), and Debye scattering simulations. The absence of distortive phase transitions and multilithiation pathways facilitates Li-ion diffusion across the vanadate electrode materials to improve storage capacity. This work opens a new dimension for vanadium-based disordered oxides, accelerating the development of low-cost, aqueous electrochemical systems.

36 MATERIALS SCIENCE↗

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

1 / ω electric-field noise in surface ion traps from correlated adsorbate dynamics

Ion traps are promising architectures for implementing quantum computers, but they suffer from excessive “anomalous” ion motional heating that limit their overall coherence and practicality for scalable quantum computing. The exact microscopic origins of anomalous heating remain an open question, but experiments point to adsorbates on trap electrodes as one likely source. Many different models of anomalous heating have been proposed, but these models have yet to pinpoint the atomistic origin of the experimentally observed 1/ω electric-field noise scaling seen in ion traps at frequencies between 0.1–10 MHz. In this work, we show that a model based on previously proposed surface-induced dipole fluctuations on adsorbates, but which also incorporates interparticle interaction dynamics through molecular dynamics simulations of up to multiple monolayers of adsorbates, gives rise to 1/ω frequency scaling at the MHz frequencies typically employed in ion traps. Overall, these results demonstrate that moderate-to-high densities of adsorbates can give rise to a set of activated motions that produce the 1/ω noise observed in ion traps and that collective adsorbate motions produce the observed noise spectra that a noninteracting model does not capture.

36 MATERIALS SCIENCE↗

Modeling a ring magnet in ALEGRA

We show here that Sandia's ALEGRA software can be used to model a permanent magnet in 2D and 3D, with accuracy matching that of the open-source commercial software FEMM. This is done by conducting simulations and experimental measurements for a commercial-grade N42 neodymium alloy ring magnet with a measured magnetic field strength of approximately 0.4 T in its immediate vicinity. Transient simulations using ALEGRA and static simulations using FEMM are conducted. Comparisons are made between simulations and measurements, and amongst the simulations, for sample locations in the steady-state magnetic field. The comparisons show that all models capture the data to within 7%. The FEMM and ALEGRA results agree to within approximately 2%. The most accurate solutions in ALEGRA are obtained using quadrilateral or hexahedral elements. In the case where iron shielding disks are included in the magnetized space, ALEGRA simulations are considerably more expensive because of the increased magnetic diffusion time, but FEMM and ALEGRA results are still in agreement. The magnetic field data are portable to other software interfaces using the Exodus file format.

36 MATERIALS SCIENCE↗

Considerations about future hard x-ray area detectors

X-ray sources continue to advance in both intensity and temporal domains, thereby opening new ways to analyze the structure and properties of matter, provided that the resultant x-ray images can be efficiently and quantitatively recorded. In this perspective we focus on specific limitations of pixel area x-ray detectors. Although pixel area x-ray detectors have also advanced in recent years, many experiments are still detector limited. Specifically, there is need for detectors that can acquire successive images at GHz rates; detectors that can accurately measure both single photon and millions of photons per pixel in the same image at frame rates of hundreds of kHz; and detectors that efficiently capture images of very hard x-rays (20 keV to several hundred keV). The data volumes and data rates of state-of-the-art detection exceeds most practical data storage options and readout bandwidths, thereby necessitating on-line processing of data prior to, or in lieu of full frame readouts.

36 MATERIALS SCIENCE↗

Corrosion Inhibition of Cold-rolled Low Carbon Steel with Pulse Fiber Laser Ablation in Water

This study aims at the use of a fiber laser for modifying the surface properties of cold-rolled low carbon steel via a pulse laser ablation technique in water. The effect on the corrosion behavior of the fiber laser-treated metal surface was investigated in NaCl and HCl environments. Electrochemical tests showed significant improvement in the corrosion resistance of the laser-treated sample in NaCl, with an increase in open-circuit potential (OCP) from − 0.65 to − 0.60 V and an inhibition efficiency of 89.22% as obtained from the impedance study. Such improvement was less significant in an acidic environment. Lower corrosion rates of 20.9 mpy and 5.819 × 10{sup 3} mpy were obtained for the laser-treated samples in neutral and acidic electrolytes, respectively, than the corrosion rates obtained for the as-received samples (33.2 mpy and 11.98 × 10{sup 3} mpy). Morphological analysis indicated a passive film built by spherical grains of regular size on the metal surface after laser treatment. The corrosion inhibition effects in NaCl were evident by the nonexistence of the common corrosion products of lepidocrocite and crystalline structures that were seen on as-received samples; only polyhedral crystals with micrograins grown on them were seen covering the laser-treated surface. Therefore, the laser treatment using a fiber laser source improved the corrosion resistance of cold-rolled low carbon steel.

36 MATERIALS SCIENCE↗

pyGWBSE: a high throughput workflow package for GW-BSE calculations

Abstract We develop an open-source python workflow package, py GWBSE to perform automated first-principles calculations within the GW-BSE (Bethe-Salpeter) framework. GW-BSE is a many body perturbation theory based approach to explore the quasiparticle (QP) and excitonic properties of materials. GW approximation accurately predicts bandgaps of materials by overcoming the bandgap underestimation issue of the more widely used density functional theory (DFT). BSE formalism produces absorption spectra directly comparable with experimental observations. py GWBSE package achieves complete automation of the entire multi-step GW-BSE computation, including the convergence tests of several parameters that are crucial for the accuracy of these calculations. py GWBSE is integrated with Wannier90 , to generate QP bandstructures, interpolated using the maximally-localized wannier functions. py GWBSE also enables the automated creation of databases of metadata and data, including QP and excitonic properties, which can be extremely useful for future material discovery studies in the field of ultra-wide bandgap semiconductors, electronics, photovoltaics, and photocatalysis.

36 MATERIALS SCIENCE↗

KG-Hub—building and exchanging biological knowledge graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract–transform–load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial–environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification.

59 BASIC BIOLOGICAL SCIENCES↗

Bioinformatic Teaching Resources – For Educators, by Educators – Using KBase, a Free, User-Friendly, Open Source Platform

Over the past year, biology educators and staff at the U.S. Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free web-based platform where anyone can conduct sophisticated and reproducible bioinformatic analyses via a graphical user interface. Here, we demonstrate the utility of KBase as a platform for bioinformatics education, and present a set of modular, adaptable, and customizable instructional units for teaching concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. Each module contains teaching resources, publicly available data, analysis tools, and Markdown capability, enabling instructors to modify the lesson as appropriate for their specific course. We present initial student survey data on the effectiveness of using KBase for teaching bioinformatic concepts, provide an example case study, and detail the utility of the platform from an instructor’s perspective. Even as in-person teaching returns, KBase will continue to work with instructors, supporting the development of new active learning curriculum modules. For anyone utilizing the platform, the growing KBase Educators Organization provides an educators network, accompanied by community-sourced guidelines, instructional templates, and peer support, for instructors wishing to use KBase within a classroom at any educational level–whether virtual or in-person.

59 BASIC BIOLOGICAL SCIENCES↗

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

54 ENVIRONMENTAL SCIENCES↗

EEL: A MOOSE-based Application for 3D Electro-Chemo-Thermo-Mechanical Modeling of Solid-State Batteries

This report describes a tool for three dimensional, high fidelity, coupled electro-chemo-thermo-mechanical modeling of solid-state batteries. A complete version of the tool is available as open source software at https://github.com/hugary1995/eel.git. The theoretical framework of the tool revolves around an inf-sup statement on a total potential, comprising the Helmholtz free energy, the electrical kinetic potential, the chemical potential, the Fourier potential, the chemical reaction potential, and the external power expenditure. The tool uses the finite element framework of Multiphysics Object-Oriented Simulation Environment (MOOSE) and a variational formulation to solve the boundary value problem for solid-state battery incorporating the full set of multiphysics couplings. The variational formulation also enables a modular software architecture for the tool so additional physics can be easily included by specifying the new contribution to the total potential. The report discusses several method of manufactured solutions that were used to verify the implementation of different physics and the Butler-Volmer reaction kinetics at the electrolyte-electrode interface. Finally, the report discusses results from complete charge/discharge simulations of a quasi-1D and a 3D solid-state battery.

25 ENERGY STORAGE↗

An efficient three-dimensional rhizosphere modeling capability to study the effect of root system architecture on soil water and reactive transport

This research was to develop a rhizosphere modeling capability for plant-soil interactions by integrating water and ion uptake and release from three dimensional (3D) root systems and 3D variably saturated flow and multicomponent reactive transport in soil. We combined open source software for simulating plant and soil interactions with parallel processing computational technologies to address highly-resolved root system architecture and soil hydrobiogeochemical processes. Simulation capability was demonstrated on Brachypodium distachyon . Our demonstration problem showed that availability of water and plant nutrients is controlled by the interplay between 1) transpiration-driven cycles of water uptake, root zone saturation and desaturation; 2) sorption and desorption via competitive ion exchange; 3) buildup of ions not taken up during kinetic uptake of nutrients/ions from pore water; and 4) advection, dispersion, and diffusion of ions in the soil. The uptake of water and ions by individual roots leads to dynamic, local gradients in ion concentrations. The resulting higher solution ionic strength can lead to increasing sorption of K+ and NH4+ on the soil exchange sites, despite their preferential absorption by roots. The modeling framework makes it possible to explore alternative conceptual models and improve the understanding of the biogeochemical and physical environment within the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

CT Scans of Cores Metadata, Utqiagvik (Barrow), Alaska, 2015

Individual ice cores were collected from Barrow Environmental Observatory in Barrow, Alaska, throughout 2013 and 2014. Cores were drilled along different transects to sample polygonal features (i.e. the trough, center and rim of high, transitional and low center polygons). Most cores were drilled around 1 meter in depth and a few deep cores were drilled around 3 meters in depth. Three-dimensional images of the frozen cores were constructed using a medical X-ray computed tomography (CT) scanner. TIFF files can be uploaded to ImageJ (an open-source imaging software) to examine soil structure and soil densities within each core.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Development of Single Photon Sources in GaN

The recent discovery of bright, room-temperature, single photon emitters in GaN leads to an appealing alternative to diamond best single photon emitters given the widespread use and technological maturity of III-nitrides for optoelectronics (e.g. blue LEDs, lasers) and high-speed, high-power electronics. This discovery opens the door to on-chip and on-demand single photon sources integrated with detectors and electronics. Currently, little is known about the underlying defect structure nor is there a sense of how such an emitter might be controllably created. A detailed understanding of the origin of the SPEs in GaN and a path to deterministically introduce them is required. In this project, we develop new experimental capabilities to then investigate single photon emission from GaN nanowires and both GAN and AlN wafers. We ion implant our wafers with the ion implanted with our focused ion beam nanoimplantation capabilities at Sandia, to go beyond typical broad beam implantation and create single photon emitting defects with nanometer precision. We've created light emitting sources using Li + and He + , but single photon emission has yet to be demonstrated. In parallel, we calculate the energy levels of defects and transition metal substitutions in GaN to gain a better understanding of the sources of single photon emission in GaN and AlN. The combined experimental and theoretical capabilities developed throughout this project will enable further investigation into the origins of single photon emission from defects in GaN, AlN, and other wide bandgap semiconductors.

36 MATERIALS SCIENCE↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

database↗

Matter in Extreme Conditions Upgrade (Conceptual Design Report)

The Linac Coherent Light Source (LCLS) X-ray Free Electron Laser (XFEL) is an open-access user facility that delivers ultrashort X-ray pulses that are nine orders of magnitude brighter than any prior source, able to probe the characteristics of matter with unprecedented spatial and temporal precision. The Matter in Extreme Conditions (MEC) instrument at LCLS combines the XFEL with high-power, short-pulse lasers to produce and study high energy density (HED) plasmas to develop the fundamental understanding of plasmas and matter in extreme environments. This has driven a remarkably rich array of high-profile scientific results with applications in fusion energy, isotope production, advanced materials, and medical and nuclear technology. The Matter in Extreme Conditions Upgrade (MEC-U) Project proposes a major upgrade to MEC that would significantly increase the power and repetition rate of the high intensity laser system to the petawatt level (PW, 10 15 Watts) at 10 Hz, increase the energy of the shock-driver laser to the kilojoule level (kJ), and expand the capabilities of the MEC instrument to support groundbreaking experiments enabled by the combination of high-power lasers with the world’s brightest X-ray source.

36 MATERIALS SCIENCE↗

Identifying Band Inversions in Topological Materials Using Diffusion Monte Carlo

Topological insulators are characterized by insulating bulk states and robust metallic surface states. Band inversion is a hallmark of topological insulators. At time-reversal invariant points in the Brillouin zone, spin–orbit coupling (SOC) induces a swapping of orbital character at the bulk band edges. Reliably detecting band inversion in solid-state systems with many-body methods would aid in identifying possible candidates for spintronics and quantum computing applications and improve our understanding of the physics behind topologically nontrivial systems. Density functional theory (DFT) methods are a well-established means of investigating these interesting materials due to their favorable balance of computational cost and accuracy but often struggle to accurately model the electron–electron correlations present in the many materials containing heavier elements. In this work, we develop a novel method to detect band inversion within continuum quantum Monte Carlo (QMC) methods that can accurately treat the electron correlation and spin–orbit coupling that are crucial to the physics of topological insulators. Our approach applies a momentum-space-resolved atomic population analysis throughout the first Brillouin zone utilizing the Löwdin method and the one-body reduced density matrix produced with diffusion Monte Carlo (DMC). We integrate this method into QMCPACK, an open source ab initio QMC package, so that these ground-state methods can be used to complement experimental studies and validate prior DFT work on predicting the band structures of correlated topological insulators. Here, we demonstrate this new technique on the topological insulator bismuth telluride, which displays band inversion between its Bi-p and Te-p states at the Γ-point. We show an increase in charge on the bismuth-p orbital and a decrease in charge on the tellurium-p orbital when comparing band structures with and without SOC. Additionally, we use our method to compare the degree of band inversion present in monolayer Bi 2 Te 3 , which has no interlayer van der Waals interactions, to that seen in the bilayer and bulk. The method presented here will enable future many-body studies of band inversion that can shed light on the delicate interplay between correlation and topology in correlated topological materials.

Band structure↗