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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Report of Viscosity Measurements on Reaction Simulant and 2-(methylamino) ethanol carbamate (NMEA carbamate) for the Explosives Destruction System (EDS) P3 System

The reaction products for the proposed chemistry for phosgene treatment in the Explosive Destruction System (EDS) are viscous. This will affect the time required to drain the EDS vessel. Viscosity measurements were made on two samples and the results for one sample have been fit to curves.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Monitoring, Verification, and Accounting (MVA) Strategy for a North Dakota Carbon Capture and Storage Project Integrated with Ethanol Production: Developing and Demonstrating Sustainable Monitoring Techniques

Conference presentation at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, March 28–30, 2022. An overview of the novel and sustainable monitoring techniques developed by the University of North Dakota's Energy & Environmental Research Center (EERC) and its commercial partners for the Red Trail Energy (RTE) carbon capture and storage (CCS) project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Replication Data for: Mechanistic and Electronic Insights into a Working NiAu Single-Atom Alloy Ethanol Dehydrogenation Catalyst

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Replication Data for: Stabilization of a nanoporous NiCu dilute alloy catalyst for non-oxidative ethanol dehydrogenation

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Deployment of a Fast-GCMS System to Measure C2 to C5 Carbonyls, Methanol and Ethanol Aboard Aircraft

Through funding of this proposal, a fast response gas chromatograph/mass spectrometer (FGCMS) instrument to measure less than or equal to C4 carbonyl compounds and methanol was developed for the NASA GTE TRACE-P (Global Tropospheric Experiment, Transport And Chemical Evolution Over The Pacific) mission. The system consists of four major components: sample inlet, preconcentration system, gas chromatograph (GC), and detector. The preconcentration system is a custom-built cryogen-conservative system. The GC is a compact, custom-built unit that can be temperature programmed and rapidly cooled. Detection is accomplished with an Agilent Technologies 5973 mass spectrometer. The FGCMS instrument provides positive identification because the compounds are chromatographically separated and mass selected. During TRACE-P, a sample was analyzed every 5 minutes. The FGCMS limit of detection was between 5 and 75 pptv, depending on the compound. The entire instrument package is contained in a standard NASA instrument rack (106 cm x 61 cm x 135 cm), consumes less than 1200 watts and is fully automated with LabViEW 6i. Methods were developed or producing highly accurate gas phase standards for the target compounds and for testing the system in the presence of potential interferents. This report presents data on these tests and on the general overall performance of the system in the laboratory and aboard the DC-8 aircraft during the mission. Vertical profiles for acetaldehyde, methanol, acetone, propanal, methyl ethyl ketone, and butanal from FGCMS data collected over the entire mission are also presented.

Apel, Eric C.↗
NASA NTRS2008

Assessing blood brain barrier dynamics or identifying or measuring selected substances, including ethanol or toxins, in a subject by analyzing Raman spectrum signals

A non-invasive method for analyzing the blood-brain barrier includes obtaining a Raman spectrum of a selected portion of the eye and monitoring the Raman spectrum to ascertain a change to the dynamics of the blood brain barrier.Also, non-invasive methods for determining the brain or blood level of an analyte of interest, such as glucose, drugs, alcohol, poisons, and the like, comprises: generating an excitation laser beam at a selected wavelength (e.g., at a wavelength of about 400 to 900 nanometers); focusing the excitation laser beam into the anterior chamber of an eye of the subject so that aqueous humor, vitreous humor, or one or more conjunctiva vessels in the eye is illuminated; detecting (preferably confocally detecting) a Raman spectrum from the illuminated portion of the eye; and then determining the blood level or brain level (intracranial or cerebral spinal fluid level) of an analyte of interest for the subject from the Raman spectrum. In certain embodiments, the detecting step may be followed by the step of subtracting a confounding fluorescence spectrum from the Raman spectrum to produce a difference spectrum; and determining the blood level and/or brain level of the analyte of interest for the subject from that difference spectrum, preferably using linear or nonlinear multivariate analysis such as partial least squares analysis. Apparatus for carrying out the foregoing methods are also disclosed.

Lambert, James L.↗
DOE OSTI2020

Engineering an increase in ethanol production by altering cofactor specificity

The present invention provides for the manipulation of cofactor usage in a recombinant host cell to increase the formation of desirable products. In some embodiments, the invention provides for a recombinant microorganism comprising a mutation in one or more native enzymes such that their cofactor specificity is altered in such a way that overall cofactor usage in the cell is balanced for a specified pathway and there is an increase in a specific product formation within the cell. In some embodiments, endogenous enzymes are replaced by enzymes with an alternate cofactor specificity from a different species.

09 BIOMASS FUELS↗
DOE OSTI2020

Assessing the Additional Carbon Savings with Biofuel

A recent study claims that corn used for ethanol should not be considered to be inherently biogenically carbon-neutral because not all that corn was grown additional to the level otherwise. By assessing the extent of carbon neutrality of corn for ethanol using the reference point baseline approach and historical data that study concluded that the carbon intensity of US corn ethanol is 27% higher than that of gasoline. We develop a framework to determine the carbon neutrality of corn for ethanol by assessing the additional carbon uptake by crops using an anticipated baseline approach. We also apply this framework to determine the additional corn produced for ethanol and include the direct life cycle carbon emissions of only that portion of corn in the direct life cycle carbon intensity of corn ethanol. We implement this framework by integrating an economic model of the agricultural sector in the USA with a biogenic carbon model and life cycle analysis to quantify biogenic carbon uptake and direct life cycle emissions with and without corn ethanol expansion over the 2007–2027 period. We find that the combined biogenic carbon emissions and direct life cycle carbon emission intensity of corn ethanol (not including indirect land use related emissions) is 21% lower than gasoline. In conclusion, the lower value of this carbon intensity of corn ethanol compared with gasoline is robust to a wide range of parametric assumptions.

09 BIOMASS FUELS↗