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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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31 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-Voltage Phosphate Cathodes for Rechargeable Ca-Ion Batteries

Calcium-ion batteries (CIBs) are under investigation as next-generation energy storage devices due to their theoretically high operating potentials and lower costs tied to the high natural abundance of calcium. However, the development of CIBs has been limited by the lack of available positive electrode materials. In this study, for the first time, we report two functional polyanionic phosphate materials as high-voltage cathodes for CIBs at room temperature. NaV 2 (PO 4 ) 3 electrodes were found to reversibly intercalate 0.6 mol of Ca 2+ (81 mA h g –1 ) near 3.2 V (vs Ca 2+ /Ca) with stable cycling performance at a current density of 3.5 mA g –1 . The olivine framework material FePO 4 reversibly intercalates 0.2 mol of Ca 2+ (72 mA h g –1 ) near 2.9 V (vs Ca 2+ /Ca) at a current density of 7.5 mA g –1 in the first cycle. Structural, electronic, and compositional changes are consistent with reversible Ca 2+ intercalation into these two materials.

25 ENERGY STORAGE↗
DOE OSTI2023

Energy Optimization of Light and Heavy-Duty Vehicle Cohorts of Mixed Connectivity, Automation and Propulsion System Capabilities via Meshed V2V-V2I and Expanded Data Sharing (Final Scientific and Technical Report)

Vehicle connectivity and automated driving technologies individually have the potential to decrease energy consumption and/or increase safety on light, medium or heavy duty vehicles to varying degrees depending on the traffic infrastructure and specific driving scenarios. Due to advances in sensing, perception and computing power, research and development emphasis in the mobility sector has shifted away from connectivity. Prior research has shown that driving automation with the absence of connectivity can in certain circumstances increase energy consumption. The effectiveness of synergizing connectivity and driving automation technologies is the focus of this work, specifically applied to vehicle cohorts of mixed composition, light and heavy duty, and powertrains ranging from all electric to conventional internal combustion engine. The project team is led by Michigan Technological University (MTU) and partnered with AVL Mobility Technologies Inc. (AVL), Borg Warner (BW), Traffic Technology Services (TTS), American Center for Mobility (ACM) and Navistar (NAV). The main thrusts for the team are to develop a micro-traffic simulation environment with specific VD&PT system attributes and CAV capabilities, 2) field a vehicle test fleet of mixed classification, propulsion and CAV capacity, 3) develop artificial intelligence (AI) and machine learning (ML) based multi-agent optimization methods for various traffic infrastructures, 4) integrate the virtual environment and the optimization methods then deploy the system as a CAV hardware in the loop (HiL) for the vehicle test fleet and 5) conduct closed track and public road testing to validate simulation and demonstrated energy and mobility improvements at multiple scales. For a cohort of mixed vehicles, the team will demonstrate a reduction of energy consumption of 10-50% at intersection, arterial roadway and limited access highway scenarios through connectivity and automation in simulation and at a closed test track. The energy reduction objectives of the project are summarized in Table 1, indicating the infrastructure and over what distances are relevant considered. Single scenario energy reductions are not relevant and thus, the research team took the approach to vary parameters associated with the infrastructure, vehicle cohort composition and dynamic behavior to generate energy consumption distributions for both unconnected and connected scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Doppler Lidar Motion-Correction (DLMC) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) second ARM Mobile Facility (AMF2) Doppler lidar (S/N 0319-160) was deployed on the German ice breaker Polarstern during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign during 2019-2020 (see Figure 1). This was the first deployment of the new AMF2 Doppler lidar, as well as the first ship-based deployment of a Doppler lidar (DL) by ARM. In contrast to land-based deployments, the lidar’s heading (a.k.a. home point) and tilt are constantly changing, and lidar’s radial velocity measurements are impacted by the ship’s motion. Since the beam directions are reported relative to the instrument’s frame of reference, derivation of higher-order data products such as wind speed and direction require that the lidar’s attitude and translational velocity be properly accounted for. The Doppler Lidar Motion-Correction (DLMC) Value-Added-Product (VAP) was developed specifically for ship-based deployments of the Doppler lidar. This VAP combines raw uncorrected data from the DL and simultaneous measurements from the ARM Navigation system (NAV) (Walton 2019) to transform the beam angles from the lidar coordinate system to an Earth-fixed coordinate system. The VAP also removes the contribution of the lidar’s platform velocity from the radial velocity measurements. This report documents the methods used by the DLMC to perform these corrections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemical Imaging for In Situ Detection and Discrimination of Aquatic Toxins Targeting Voltage Gated Sodium Channels

Biologically derived neurotoxins from cyanobacteria and algae impact environmental resources in addition to being considered a potential biological threat to human and animal health. Activity based assays are essential to detecting and responding to toxic neurotoxin events either naturally occurring or deliberate. Two toxins of interest include saxitoxin and brevetoxin. These toxins bind to and alter the function of voltage-gated sodium channels (NaV channels) which are essential for generating cell membrane action potential. We report the development and refinement of a System for Analysis at Liquid Vacuum Interface (SALVI) to assess the functional activity of saxitoxin and brevetoxin. This approach utilizes a vacuum-compatible microfluidic reactor that permits analysis at the liquid vacuum interface of human derived cells with a neurotoxin of interest in a biologically relevant environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

dlmcfpt.c1

The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

dlmcusr.c1

The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Role of a Multivalent Ion–Solvent Interaction on Restricted Mg 2+ Diffusion in Dimethoxyethane Electrolytes

The diffusion behavior of Mg 2+ in electrolytes is not as readily accessible as that from Li + or Na + utilizing PFG NMR, due to the low sensitivity, poor resolution, and rapid relaxation encountered when attempting 25 Mg NMR. In MgTFSI 2 /DME solutions, “bound” DME (coordinating to Mg 2+ ) and “free” DME (bulk) are distinguishable from 1 H NMR. With the exchange rates between them obtained from 2D 1 H EXSY NMR, we can extract the self-diffusivities of free DME and bound DME (which are equal to that of Mg 2+ ) before the exchange occurs using PFG diffusion NMR measurements coupled with analytical formulas describing diffusion under two-site exchange. Further, the high activation enthalpy for exhange (65–70 kJ/mol) can be explained by the structural change of bound DME as evidenced by its reduced C–H bond length. Comparison of the diffusion behaviors of Mg 2+ , TFSI – , DME, and Li + reveals a relative restriction to Mg 2+ diffusion that is caused by the long-range interaction between Mg 2+ and solvent molecules, especially those with suppressed motions at high concentrations and low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Decarbonization of the Chemical Industry Through Electrification: Barriers and Opportunities

The chemical industry is a major source of economic productivity and employment globally and among the top 3 industrial sources of greenhouse gas (GHG) emissions, along with steel and cement. As global demand for chemical products continues to grow, there is an urgency to develop and deploy sustainable chemical production pathways and to reconsider continued investment in current emission-intensive production technologies. This perspective describes the challenges and opportunities to decarbonize the chemical industry via electrification powered by low-carbon electricity supply, both in the near term and long term, and it discusses four technological pathways ranging from the more mature direct substitution of heat with electricity and use of hydrogen to technologically less mature, yet potentially more selective, approaches based on electrochemistry and plasma. Finally, we highlight the key elements of integrating an electrified industrial process with the power sector to leverage process flexibility to reduce energy costs of chemical production and provide valuable power grid support services. Unlocking such plant-to-grid coordination and the four electrification pathways has significant potential to facilitate rapid and deep decarbonization of the chemical industry sector.

chemical synthesis↗
DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2023

Non-polar ether-based electrolyte solutions for stable high-voltage non-aqueous lithium metal batteries

The electrochemical instability of ether-based electrolyte solutions hinders their practical applications in high-voltage Li metal batteries. To circumvent this issue, here, we propose a dilution strategy to lose the Li + /solvent interaction and use the dilute non-aqueous electrolyte solution in high-voltage lithium metal batteries. We demonstrate that in a non-polar dipropyl ether (DPE)-based electrolyte solution with lithium bis(fluorosulfonyl) imide salt, the decomposition order of solvated species can be adjusted to promote the Li + /salt-derived anion clusters decomposition over free ether solvent molecules. This selective mechanism favors the formation of a robust cathode electrolyte interphase (CEI) and a solvent-deficient electric double-layer structure at the positive electrode interface. When the DPE-based electrolyte is tested in combination with a Li metal negative electrode (50 μm thick) and a LiNi 0.8 Co 0.1 Mn 0.1 O 2 -based positive electrode (3.3 mAh/cm 2 ) in pouch cell configuration at 25 °C, a specific discharge capacity retention of about 74% after 150 cycles (0.33 and 1 mA/cm 2 charge and discharge, respectively) is obtained.

25 ENERGY STORAGE↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗