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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Heats of Formation for CF(sub n) (n = 1 - 4), CF(sup +, sub n) (n = 1 - 4), and CF(sup -, sub n) (n = 1 - 3)

Accurate heats of formation are computed for CF(sub n) (n = 1 - 4), CF(sup +, sub n) (n = 1 - 4), and CF(sup -, sub n) (n = 1 - 3). The geometries and vibrational frequencies are determined at the B3LYP level of theory. The energetics are determined at the CCSD(T) level of theory. Basis set limit values are obtained by extrapolation. In those cases where the CCSD(T) calculations become prohibitively large, the basis set extrapolation is performed at the MP2 level. The temperature dependence of the heat of formation, heat capacity, and entropy are computed for the temperature range 300 to 4000 K and fit to a polynomial.

Ricca, Alessandra↗
NASA NTRS2022

NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-29CF) provides recent estimates and five-day forecasts of atmospheric composition to the public in near-real time. To do this, the GEOS Earth system model is coupled with the GEOS-Chem tropospheric-stratospheric unified chemistry extension (UCX) to represent composition from the surface to the top of the GEOS atmosphere (0.01 hPa). The GEOS-CF system is described, including updates made to the GEOS-Chem UCX mechanism within GEOS-CF for improved representation of stratospheric chemistry. Comparisons are made against balloon, lidar and satellite observations for stratospheric composition, including measurements of ozone (O3) and important nitrogen and chlorine species related to stratospheric O3recovery. The GEOS-CF nudges the stratospheric O3towards the GEOS Forward Processing (GEOS FP) assimilated O3product; as a result the stratospheric O3in the GEOS-CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS-CF O3forecasts are more realistic than GEOS FP O3forecasts because of the inclusion of the complex GEOS-Chem UCX stratospheric chemistry. Overall, the spatial patterns of the GEOS-CF simulated concentrations of stratospheric composition agree well with satellite observations. However, there are notable biases – such as low NOx and HNO3 in the polar regions and generally low HCl throughout the stratosphere – and future improvements to the chemistry mechanism and emissions are discussed. GEOS-CF is a new tool for the research community and instrument teams observing trace gases in the stratosphere and troposphere, providing near-real-time three-dimensional gridded information on atmospheric composition.

GEOS-CF↗
NASA NTRS2020

High Resolution Global Coupled Chemistry-Meteorology Simulations Using the NASA GEOS Composition Forecast System, GEOS-CF

We will give an overview of the NASA Global Earth Observing System Composition Forecast system (GEOS-CF), a high-resolution (0.25 degree) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module (version 12) to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone, nitrogen oxides, volatile organic compounds, and fine particulate matter. The spatial resolution of 0.25 degrees (approx. 25 km) is fine enough to resolve local features such as nighttime ozone titration previously resolved only by urban or regional models. Furthermore, since there are no boundary conditions for a global model, the GEOS-CF captures large-scale processes such as long-range transport of air pollutants from forest fires. Comparisons against surface observations highlight the model’s overall capability to reproduce the diurnal variability of air pollutants under a variety of meteorological conditions. In addition, we show how machine learning techniques can be used to correct for sub-grid variability, which further improves model estimates at a given surface observation site. The GEOS-CF system offers a new tool for scientists and the public health community alike and is being developed jointly with several government and non-profit partners. As an example, we will show the use of GEOS-CF during the Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE). The campaign, conducted in collaboration between NASA and the Bureau of Ocean Energy Management (BOEM), aims to investigate the response of onshore air quality to Outer Continental Shelf (OCS) oil and gas exploration, development and production. Detailed gas-phase chemistry, as provided by GEOS-CF, is critical to understand the formation of air pollution related to hydrocarbon emissions from offshore oil and gas activities. The accuracy of GEOS-CF can be further improved by incorporating detailed offshore emissions compiled by BOEM.

Knowland, K. Emma↗
NASA NTRS2021

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25 degree) global constituent prediction system from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA’s broad range of space-based and in-situ observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.Evaluation of GEOS-CF against satellite, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 generally overestimates aerosols by 20-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions.The 5-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗
NASA NTRS2008

Increasing Discharge Capacities of Li-(CF)(sub n) Cells

An electrolyte additive has shown promise as a means of increasing the sustainable rates of discharge and, hence, the discharge capacities, of lithiumpoly(carbon monofluoride) electrochemical power cells. Lithium-poly(carbon monofluoride) [Li-(CF)n] cells and batteries offer very high specific energies practical values of about 600 W.h/g and a theoretical maximum value of 2,180 W.h/kg. However, because Li-(CF)n cells and batteries cannot withstand discharge at high rates, they have been relegated to niche applications that involve very low discharge currents over times of the order of hundreds to thousands of hours. Increasing the discharge capacities of Li- (CF)n batteries while maintaining high practical levels of specific energy would open new applications for these batteries. During the discharge of a Li-(CF)n cell, one of the electrochemical reactions causes LiF to precipitate at the cathode. LiF is almost completely insoluble in most non-aqueous solvents, including those used in the electrolyte solutions of Li-(CF)n cells. LiF is electrochemically inactive and can block the desired transport of ions at the cathode, and, hence, the precipitation of LiF can form an ever-thickening film on the cathode that limits the rate of discharge.

Whitacre, Jay↗
NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRS1991

Examination of the discharge mechanism of Li/CF(x) cells: Comparison of the electrochemical reduction mechanisms of PTFE and (CF(x))n by lithium

Swelling of (CF(x))(sub n) electrodes in commercial Li/(CF(x))(sub n) cells presents a limiting factor in cell design optimization. Examination of cathodes from such cells, after discharge, reveals a relation between cell operating temperatures and cathode swelling. Attempts to explain the swelling using the prevailing model for the cathode reaction have failed. A more suitable reaction mechanism is proposed based on the observed behavior of (CF(x))(sub n) electrodes on discharge and a comparison of the reaction products of (CF(x))(sub n) and polytetra fluoroethylene (PTFE) with lithium amalgams. The proposed mechanism is in agreement with the experimental data found in the literature.

Baxam, Carl C.↗
NASA NTRS2009

Additive for Low-Temperature Operation of Li-(CF)n Cells

Some progress has been reported in continuing research on the use of anion-receptor compounds as electrolyte additives to increase the sustainable rates of discharge and, hence, the discharge capacities, of lithium-poly(carbon monofluoride) [Li-(CF)n, where n >1] primary electrochemical power cells. Some results of this research at a prior stage were summarized in Increasing Discharge Capacities of Li(CF)n Cells (NPO-42346), NASA Tech Briefs, Vol. 32, No. 2 (February 2008), page 37. A major difference between the present and previously reported results is that now there is some additional focus on improving performance at temperatures from ambient down to as low as 40 C. To recapitulate from the cited prior article: During the discharge of a Li-(CF)n cell, one of the electrochemical reactions causes LiF to precipitate at the cathode. LiF is almost completely insoluble in most non-aqueous solvents, including those used in the electrolyte solutions of Li- (CF)n cells. LiF is electrochemically inactive and can block the desired transport of electrons at the cathode, and, hence, the precipitation of LiF can form an ever-thickening film on the cathode that limits the rate of discharge. An anion-receptor electrolyte additive helps to increase the discharge capacity in two ways: It renders LiF somewhat soluble in the non-aqueous electrolyte solution, thereby delaying precipitation until a high concentration of LiF in solution has been reached. When precipitation occurs, it promotes the formation of large LiF grains that do not conformally coat the cathode. The net effect is to reduce the blockage caused by precipitation of LiF, thereby maintaining a greater degree of access of electrolyte to the cathode and greater electronic conductivity.

West, William↗
NASA NTRSDate not supplied

NASA GEOS Composition Forecast System: GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework compared to the GEOS-5 Nature Run with Chemistry (used in the post-processing to make the TEMPO Proxy Data), 2) description of the file used to support the TEMPO retrieval team, and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation.

K. Emma Knowland↗
NASA NTRSDate not supplied

NASA GEOS Composition Forecast System, GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework and data/visualization access, 2) examples of current and future applications to support NASA missions (e.g., a priori for trace gas retrievals by TEMPO, ground-based instrument teams and field campaigns), and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation, near-real time emission adjustment estimates, down-scaling methods to urban-scale, and data access on Google Earth Engine, Amazon Web Services, and other platforms to integrate our state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

K. Emma Knowland↗
NASA NTRS2022

GMAO Office Note No. 17 (Version 1.3) File Specification for GEOS-CF Products

The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (about 25 km). This GEOS Composition Forecast (GEOS-CF) system combines the GEOS weather analysis and forecasting system with the state-of-the-science GEOS-Chem chemistry module (Bey et al., 2001; Keller et al., 2014; Long et al., 2015) to provide detailed chemical analysis of a wide range of air pollutants including ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Full model description and evaluation of the GEOS-CF tropospheric simulation and forecast skill is given in Keller et al. (2021). For evaluation of GEOS-CF stratospheric composition see Knowland et al. (2021).

GEOS-CF↗
NASA NTRS2004

A Monte Carlo Sensitivity Analysis of CF2 and CF Radical Densities in a c-C4F8 Plasma

A Monte Carlo sensitivity analysis is used to build a plasma chemistry model for octacyclofluorobutane (c-C4F8) which is commonly used in dielectric etch. Experimental data are used both quantitatively and quantitatively to analyze the gas phase and gas surface reactions for neutral radical chemistry. The sensitivity data of the resulting model identifies a few critical gas phase and surface aided reactions that account for most of the uncertainty in the CF2 and CF radical densities. Electron impact dissociation of small radicals (CF2 and CF) and their surface recombination reactions are found to be the rate-limiting steps in the neutral radical chemistry. The relative rates for these electron impact dissociation and surface recombination reactions are also suggested. The resulting mechanism is able to explain the measurements of CF2 and CF densities available in the literature and also their hollow spatial density profiles.

Bose, Deepak↗
NASA NTRSDate not supplied

NASA GEOS-CF: Overview, Applications, Future Direction

Since 2019, the NASA Global Earth Observing System (GEOS) model has been used to generate global, near-real-time estimates and daily five-day forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). Because GEOS-CF includes atmospheric levels up through the stratosphere, this system has been leveraged to support the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission and provide stratospheric intrusion alerts to ground-based monitoring stations. We will present recent advances to GEOS-CF which includes assimilation of satellite observations to produce more accurate model analyses. We further discuss our future plans for a composition reanalysis.

K. Emma Knowland↗
NASA NTRS1990

A new method for using Cf-252 in SEU testing

A system using Cf-252 and associated nuclear instrumentation has determined the single-event upset (SEU) cross section versus linear energy transfer (LET) curve for several 2K x 8 static random access memories (SRAMs). The Cf-252 fission fragments pass through a thin-film organic scintillator detector (TFD) on the way to the device under test (DUT). The TFD provides energy information for each transiting fragment. Data analysis provides the energy of the individual ion responsible for each SEU; thus, separate upset cross sections can be developed for different energy and mass regions of the californium spectrum. This californium-based device is quite small and fits onto a bench top. It provides a convenient and inexpensive supplement or alternative to accelerator and high-altitude/space SEU testing.

Costantine, A.↗
NASA NTRS1999

Reactivity of CF(n) (n = 1-3) Radicals with a Silica Surface

The trends in reactivity of CF(n) radicals with SiO2 and the site selectivity of the attack are studied using two different cluster models. The reaction barriers for the most energetically favorable reaction are computed. It is shown that CF(n) radicals are fairly unreactive towards SiO2.

Ricca, Alessandra↗
NASA NTRS2020

Local to Global Air Quality Simulations using the NASA GEOS Composition Forecast Model, GEOS-CF

We give an overview of the NASA Global Earth Observing System Composition Forecast model (GEOS-CF), a high-resolution (roughly 25-km) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone,nitrogen oxides, volatile organic compounds, and fine particulate matter.Given the global extent of the model, GEOS-CF captures large-scale processes such as long-range transport of air pollutants, across ocean basins and continents.

Knowland, Emma K.↗
NASA NTRSDate not supplied

Mars Space Suit Materials Testing Using SHERLOC Calibration Target Data: The Max-CF Project

The Mars 2020/“Perseverance” rover carries a suite of space suit materials as part of the SHERLOC* calibration target [1]. The materials are periodically analyzed by SHERLOC as part of a regular calibration routine and are generating a rich data set regarding their degradation in the martian surface environment. The Maximization of Calibration Fabrics (Max-CF) project will effectively turn SHERLOC data into a measure of space suit material service lifetimes by exposing a second set of materials in a Mars chamber, replicating SHERLOC measurements using the analogous ACRONM** instrument at JSC, and then performing materials testing to include tensile testing. These data can be used to inform space suit design and/or materials development, improving crew safety for future Mars missions. This will partially address NASA’s Strategic Knowledge Gap 8 (Mars Surface Technology) which identifies a need to develop technologies to “sustain humans on the surface of Mars [and] enable human mobility and exploration” [2]. This abstract describes the overall Max-CF project and progress on the laboratory-based study to date.

M Fries↗
NASA NTRSDate not supplied

Extending CF Conventions to Enhance Data FAIRness for Atmospheric Composition Observations

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global, group, or variable attributes and are popular with the modeling community. HDF and NetCDF files are widely used with atmospheric remote sensing data and have been used to support measurements from numerous field campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of their metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. Recently, the Measurements of Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a CF-based template for the HDF and NetCDF files for field studies, with the aim of making the data products more interoperable and usable. This template seeks to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. The template would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. The draft template has been applied to recent field studies for various instruments and their merge files in support of the Atmosphere Observing System (AOS) project. The details of the revised template are to be presented, as well as examples of the implementation of these requirements for merge files and lidar observation data files and issues revealed during the implementation process.

Sean Leavor↗