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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗
NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗
DOE OSTI2019

Evolution of Solid Electrolyte Interface on TiO 2 Electrodes in an Aqueous Li-Ion Battery Studied Using Scanning Electrochemical Microscopy

Scanning electrochemical microscopy (SECM) was applied for in situ visualization of solid electrolyte interface (SEI) evolution on the TiO 2 anode in a concentrated aqueous electrolyte during cycling. In nonaqueous electrolytes, the SEI is an electronic insulative layer composed of organic and inorganic components covering the electrode surface. However, in concentrated aqueous electrolytes, the SEI is mostly composed of inorganic compounds formed by electrolyte decomposition, such as LiF and Li 2 CO 3 , which are randomly distributed over the TiO 2 surface. In addition, the Ti 3+ and Li residuals accumulated through multiple cycling lead to an increase in the overall electronic conductivity of the TiO 2 anode. Furthermore during the resting period after cycling, an inverse process is observed with partial dissolution of the formed SEI and the diffusion of Li residuals back into the electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2017

Modeling DNP3 Traffic Characteristics of Field Devices in SCADA Systems of the Smart Grid

In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impacts of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

In Situ Visualization of the Pinning Effect of Planar Defects on Li Ion Insertion

Longevity of Li ion batteries strongly depends on the interaction of transporting Li ions in electrode crystals with defects. However, detailed interactions between the Li ion flux and structural defects in the host crystal remain obscure due to the transient nature of such interactions. Here, by in situ transmission electron microscopy and density function theory calculations, we reveal how the diffusion pathways and transport kinetics of a Li ion can be affected by planar defects in a tungsten trioxide lattice. We uncover that changes in charge distribution and lattice spacing along the planar defects disrupt the continuity of ion conduction channels and dramatically increase the energy barrier of Li diffusion, thus, arresting Li ions at the defect sites and twisting the lithiation front. In conclusion, the atomic-scale understanding holds critical implications for rational interface design in solid-state batteries and solid oxide fuel cells.

25 ENERGY STORAGE↗
NASA NTRS2013

Science Opportunity Analyzer (SOA) Version 8

SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability

Witoff, Robert J.↗
DOE OSTI2023

Operando characterization and regulation of metal dissolution and redeposition dynamics near battery electrode surface

Mn dissolution has been a longstanding, ubiquitous issue that negatively impacts the performance of Mn-based battery materials. Mn dissolution involves complex chemical and structural transformations at the electrode-electrolyte interface. The continuously evolving electrodeelectrolyte interface has posed great challenges for characterizing the dynamic interfacial process and quantitatively establishing the correlation with battery performance. In this study, we visualize and quantify the temporally and spatially resolved Mn dissolution/redeposition (D/R) dynamics of electrochemically operating Mn-containing cathodes. The particle-level and electrode-level analyses reveal that the D/R dynamics is associated with distinct interfacial degradation mechanisms at different states of charge. Our results statistically differentiate the contributions of surface reconstruction and Jahn-Teller distortion to the Mn dissolution at different operating voltages. Introducing sulfonated polymers (Nafion) into composite electrodes can modulate the D/R dynamics through trapping the dissolved Mn species and rapidly establishing the local Mn D/R equilibrium. This work represents an inaugural effort to pinpoint the chemical and structural transformations responsible for Mn dissolution via an operando synchrotron study and develops an effective method to regulate Mn interfacial dynamics for improving battery performance.

25 ENERGY STORAGE↗
DOE OSTI2020

Supercooled liquid sulfur maintained in three-dimensional current collector for high-performance Li-S batteries

In lithium-sulfur (Li-S) chemistry, the electrically/ionically insulating nature of sulfur and Li 2 S leads to sluggish electron/ion transfer kinetics for sulfur species conversion. Sulfur and Li 2 S are recognized as solid at room temperature, and solid-liquid phase transitions are the limiting steps in Li-S batteries. Here, we visualize the distinct sulfur growth behaviors on Al, carbon, Ni current collectors and demonstrate that (i) liquid sulfur generated on Ni provides higher reversible capacity, faster kinetics, and better cycling life compared to solid sulfur; and (ii) Ni facilitates the phase transition (e.g., Li 2 S decomposition). Accordingly, light-weight, 3D Ni-based current collector is designed to control the deposition and catalytic conversion of sulfur species toward high-performance Li-S batteries. This work provides insights on the critical role of the current collector in determining the physical state of sulfur and elucidates the correlation between sulfur state and battery performance, which will advance electrode designs in high-energy Li-S batteries.

25 ENERGY STORAGE↗
NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗
DOE OSTI2020

Using operando techniques to understand and design high performance and stable alkaline membrane fuel cells

There is a need to understand the water dynamics of alkaline membrane fuel cells under various operating conditions to create electrodes that enable high performance and stable, long-term operation. Here we show, via operando neutron imaging and operando micro X-ray computed tomography, visualizations of the spatial and temporal distribution of liquid water in operating cells. We provide direct evidence for liquid water accumulation at the anode, which causes severe ionomer swelling and performance loss, as well as cell dryout from undesirably low water content in the cathode. We observe that the operating conditions leading to the highest power density during polarization are not generally the conditions that allow for long-term stable operation. This observation leads to new catalyst layer designs and gas diffusion layers. This study reports alkaline membrane fuel cells that can be operated continuously for over 1000 h at 600 mA cm -2 with voltage decay rate of only 32-μV h -1 – the best-reported durability to date.

25 ENERGY STORAGE↗
DOE OSTI2025

Isolation and conversion of electrolyte components into a value-added product

The overall objective of this work was to develop a process for effectively (i) recycling the electrolyte components from the end-of-life batteries and reduce the environmental hazard, (ii) understand the fundamental differences between pristine and recycled electrolyte components, (iii) electrochemically and analytically evaluate the recycled electrolyte components and (iv) establish deviations from the pristine electrolyte, and effectively separation of value-added product. We focused on determining scaling up the electrolyte recovery process by distillation of end-of-life batteries to get yield enough to use it for electrolyte formulation of reuse in the battery cell. The used cells from the ORNL battery manufacture facility (BMF)as well as received from the industry partner, Austin Elements Inc., was scaled to 10 used multilayered pouch cells in each batch of distillation and systematically separated and identified the electrolyte components of the used cells with FTIR and NMR studies. We were able to recovery 10g of solvent mass from the used pouch cells. NMR spectroscopy showed that the solvent was pure EMC,DMC and the sample was used to make a new battery cell. The end-of-life battery, it was noted that some cells were visually drier than the other cells and were more advanced in aged. In that case, even though the same distillation conditions were utilized, no usable mass of electrolyte solvent was recovered. It is expected that most of the solvent was decomposed during the battery charge-discharge cycling. The solid salt residue was separated by chemical and water treatment processes. Components of resulting solid product was analyzed by XRD and XPS measurements. The solid products are very much related to the salts used in the electrolyte solution.

25 ENERGY STORAGE↗
DOE OSTI2019

Visualizing percolation and ion transport in hybrid solid electrolytes for Li–metal batteries

Hybrid solid electrolytes are composed of organic (polymer) and inorganic (ceramic) ion conducting materials, and are promising options for large-scale production of solid state lithium–metal batteries. Hybrid solid electrolytes containing 15 vol% Al-LLZO demonstrate optimal ionic conductivity properties. Ionic conductivity is shown to decrease at high inorganic loadings. This optimum is most obvious above the melting temperature of polyethylene oxide where the polymer is amorphous. Structural analysis using synchrotron nanotomography reveals that the inorganic particles are highly aggregated. The aggregation size grows with inorganic content and the largest percolating clusters measured for 5 vol%, 15 vol% and 50 vol% were ~12 μm 3 , 206 μm 3 , and 324 μm 3 , respectively. Enhanced transport in hybrid electrolytes is shown to be due to polymer|particle (Al-LLZO) interactions and ionic conductivity is directly related to the accessible surface area of the inorganic particles within the electrolyte. Finally, ordered and well-dispersed structures are ideal for next generation hybrid solid electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2022

Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints

Vast volumes of data are produced by today's scientific simulations and advanced instruments. These data cannot be stored and transferred efficiently because of limited I/O bandwidth, network speed, and storage capacity. Error-bounded lossy compression can be an effective method for addressing these issues: not only can it significantly reduce data size, but it can also control the data distortion based on user-defined error bounds. In practice, many scientific applications have specific requirements or constraints for lossy compression, in order to guarantee that the reconstructed data are valid for post hoc analysis. For example, some datasets contain irrelevant data that should be isolated in particular and users often have intuition regarding value ranges, geospatial regions, and other data subsets that are crucial for subsequent analysis. Existing state-of-the-art error-bounded lossy compressors, however, do not consider these constraints during compression, resulting in inferior compression ratios with respect to user's post hoc analysis, due to the fact that the data itself provides little or no value for post hoc analysis. In this work we address this issue by proposing an optimized framework that can preserve diverse constraints during the error-bounded lossy compression, e.g., cleaning the irrelevant data, efficiently preserving different precision for multiple value intervals, and allowing users to set diverse precision over both regular and irregular regions. We perform our evaluation on a supercomputer with up to 2,100 cores. Experiments with six real-world applications show that our proposed diverse constraints based error-bounded lossy compressor can obtain a higher visual quality or data fidelity on reconstructed data with the same or even higher compression ratios compared with the traditional state-of-the-art compressor SZ. Furthermore, our experiments also demonstrate very good scalability in compression performance compared with the I/O throughput of the parallel file system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation

Long-term seismic monitoring of carbon capture and storage projects is needed to verify that the injected gas is safely stored in the subsurface until permanence can be assured. Conventional surface seismic monitoring techniques are usually expensive, require highly invasive surface operations, and need significant time investments on the part of personnel for both the field effort and processing the acquired data. For these reasons, permanent reservoir monitoring technologies are preferred, as they can offer a cost-effective solution for long-term monitoring. As part of the monitoring program of the Archer Daniels Midland’s large-scale injection of CO 2 in Decatur, Illinois, USA, a continuous seismic monitoring array was installed using a combination of surface orbital vibrator (SOV) sources and fiber-optic cables for distributed acoustic sensing (DAS) acquisition with the objective to build a continuous monitoring array. The aim of the presented project was to build a monitoring array and platform that integrates real-time seismic data with conventional data streams and provides continuous data analysis using dynamic computational models to deliver a comprehensive real-time assessment of subsurface conditions. It is in this context that the Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation project was proposed with the objective to develop an integrated architecture that utilizes a permanent seismic monitoring network, combines the real-time geophysical and process data with reservoir flow and geomechanical models to create a comprehensive monitoring, visualization, and control system that delivers critical information for process surveillance and optimization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Characterization of dynamic morphological changes of tin anode electrode during (de)lithiation processes using in operando synchrotron transmission X-ray microscopy

The morphological evolution of tin particles with different sizes during the first lithiation and delithiation processes has been visualized by an in operando synchrotron transmission X-ray microscope (TXM). Here, the in operando lithium ion battery cell was operated at constant current condition during TXM imaging. Two-dimensional projection images with 40 nm resolution showing morphological evolution were obtained and analyzed. The analysis of relative area change shows that the morphology of tin particles with different sizes changed simultaneously. This phenomenon is mainly because of a negative feedback mechanism among tin particles in the battery electrode at a constant current operating condition. For irregular-shaped tin particles, the contour analysis demonstrates that the regions with higher curvature started volume expansion first, and then the entire particle expanded almost homogeneously. This study provides insights for understanding the dynamic morphological change and the particle-particle interactions in high capacity lithium ion battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2025

Isolation and Conversion of Electrolyte Components into a Value-Added Product

The overall objective of this work was to develop a process for effectively (i) recycling the electrolyte components from the end-of-life batteries and reduce the environmental hazard, (ii) understand the fundamental differences between pristine and recycled electrolyte components, (iii) electrochemically and analytically evaluate the recycled electrolyte components and (iv) establish deviations from the pristine electrolyte, and effectively separation of value-added product. We focused on determining scaling up the electrolyte recovery process by distillation of end-of-life batteries to get yield enough to use it for electrolyte formulation of reuse in the battery cell. The used cells from the ORNL battery manufacture facility (BMF) as well as received from the industry partner, Austin Elements Inc., was scaled to 10 used multilayered pouch cells in each batch of distillation and systematically separated and identified the electrolyte components of the used cells with FTIR and NMR studies. We were able to recovery 10g of solvent mass from the used pouch cells. NMR spectroscopy showed that the solvent was pure EMC, DMC and the sample was used to make a new battery cell. The end-of-life battery, it was noted that some cells were visually drier than the other cells and were more advanced in aged. In that case, even though the same distillation conditions were utilized, no usable mass of electrolyte solvent was recovered. It is expected that most of the solvent was decomposed during the battery charge-discharge cycling. The solid salt residue was separated by chemical and water treatment processes. Components of resulting solid product was analyzed by XRD and XPS measurements. The solid products are very much related to the salts used in the electrolyte solution.

25 ENERGY STORAGE↗
DOE OSTI2023

Nondestructively Visualizing and Understanding the Mechano-Electro-chemical Origins of “Soft Short” and “Creeping” in All-Solid-State Batteries

All-solid-state Li-metal batteries (ASLMBs) represent a significant breakthrough in the quest to overcome limitations associated with traditional Li-ion batteries, particularly in energy density and safety aspects. However, widespread implementation is stymied due to a lack of profound understanding of the complex mechano-electro-chemical behavior of Li metal in the ASLMBs. Herein, operando neutron imaging and X-ray computed tomography (XCT) are leveraged to nondestructively visualize Li behaviors within ASLMBs. This approach offers real-time observations of Li evolutions, both pre- and post- occurrence of a “soft short”. The coordination of 2D neutron radiography and 3D neutron tomography enables charting of the terrain of Li metal deformation operando. Concurrently, XCT offers a 3D insight into the internal structure of the battery following a “soft short”. Despite the manifestation of a “soft short”, the persistence of Faradaic processes is observed. To study the elusive “soft short”, phase field modeling is coupled with electrochemistry and solid mechanics theory. The research unravels how external pressure curbs dendrite growth, potentially leading to dendrite fractures and thus uncovering the origins of both “soft” and “hard” shorts in ASLMBs. Furthermore, by harnessing finite element modeling, it dive deeper into the mechanical deformation and the fluidity of Li metal.

25 ENERGY STORAGE↗
DOE OSTI2022

Evolution of micro-pores in Ni–Cr alloys via molten salt dealloying

Porous materials with high specific surface area, high porosity, and high electrical conductivity are promising materials for functional applications, including catalysis, sensing, and energy storage. Molten salt dealloying was recently demonstrated in microwires as an alternative method to fabricate porous structures. The method takes advantage of the selective dissolution process introduced by impurities often observed in molten salt corrosion. This work further investigates molten salt dealloying in bulk Ni–20Cr alloy in both KCl–MgCl 2 and KCl–NaCl salts at 700 °C, using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffraction (XRD), as well as synchrotron X-ray nano-tomography. Micro-sized pores with irregular shapes and sizes ranging from sub-micron to several microns and ligaments formed during the process, while the molten salt dealloying was found to progress several microns into the bulk materials within 1–16 h, a relatively short reaction time, enhancing the practicality of using the method for synthesis. The ligament size increased from ~ 0.7 μm to ~ 1.3 μm in KCl–MgCl 2 from 1 to 16 h due to coarsening, while remaining ~ 0.4 μm in KCl–NaCl during 16 h of exposure. The XRD analysis shows that the corrosion occurred primarily near the surface of the bulk sample, and Cr 2 O 3 was identified as a corrosion product when the reaction was conducted in an air environment (controlled amount sealed in capillaries); thus surface oxides are likely to slow the morphological coarsening rate by hindering the surface diffusion in the dealloyed structure. 3D-connected pores and grain boundary corrosion were visualized by synchrotron X-ray nano-tomography. This study provides insights into the morphological and chemical evolution of molten salt dealloying in bulk materials, with a connection to molten salt corrosion concerns in the design of next-generation nuclear and solar energy power plants.

36 MATERIALS SCIENCE↗