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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Supply Chain Energy and Greenhouse Gas Analysis Using the Materials Flows Through Industry (MFI) Tool: Examination of Alternative Technology Scenarios for the U.S. Chemical Sector

Chemical manufacturing is a large and diverse sector of the U.S. economy, with products, fuels, and a wide assortment of materials used daily by both the public and businesses. Currently, several of the largest volume chemicals produced in the United States rely on fossil fuels as a feedstock, energy source, or both. The list of chemicals includes steam cracking products such as ethylene, propylene, benzene, and xylenes as well as products such as ammonia and methanol. The focus for this work is on platform chemicals that are both produced in the largest volume and have a high potential for subsequent processing into more specialized products. In this study, we explore several new pathways that reduce the overall energy consumption and greenhouse gas (GHG) emissions for each product. These pathways include energy efficiency measures applied to existing production methods, the use of bio‐based fuels and/or feedstocks as new production methods, and electrification of high‐energy‐input stages within current production methods. Scenarios for energy demand and GHG reduction were conducted with the National Renewable Energy Laboratory's Materials Flows through Industry tool. Projections of the energy demand and GHG emissions in 2030 and 2050 are included, using grid composition projections from the NREL ReEDS model. The alternative scenarios selected showcase the effect of realistic changes the industry could make, focusing on technologies with a high level of technical readiness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2027

A multi-region approach for the analysis of porous materials and gas-solid reactions using USAXS-SAXS-WAXS: application to CaO carbonation

The reaction rate of gas-solid non-catalytic reactions is typically investigated using reactant conversion data over time and ex-situ measurements of the porous solid reactant textural properties; these data enable the experimental estimation of the initial intrinsic reaction rate, whereas the evolution of the textural properties and the reaction rate over time are evaluated theoretically using reaction models. In this work, a different methodology is presented, based on: a) in-situ time-resolved USAXS-SAXS-WAXS measurements of the solid sample, and b) a multi-region modeling approach; this methodology allows for the estimation of the textural properties and the intrinsic reaction rate at any time during the reaction. Referring to a reaction in which a solid product is obtained from a solid reactant and a gaseous reactant, the porous particle is described as consisting of several distinct regions with different microstructural properties, and both a gas-solid reaction model and a SAXS model are derived and applied to the carbonation of porous CaO. The proposed reaction model highlights the role of the inaccessible reactant and accurately predicts the solid reactant conversion versus time profile. The SAXS model accurately predicts the measured linear trends of the Porod invariant and of the pre-factor of the power law scattering profile versus CaO mass fraction; in the absence of chemical reactions, the proposed equations extend classical SAXS theory to porous materials containing macropores and nonporous solid phases in addition to standard nanoscale inhomogeneous regions.

CO2 solid sorbents↗
DOE OSTI2024

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1969

Preferred-orientation analysis of polycrystalline materials

Automatic device built around a goniometer examines characteristics of polycrystalline materials and determines preferred orientations of crystallites. It is automatically rotatable in each of two planes and has circuit regulated sequential rotation. A fixed X ray source in conjunction with a detector examines the material.

De Wys, E. C.↗
NASA NTRS1976

Cost/benefit analysis of advanced materials technologies for future aircraft turbine engines

The cost/benefits of advance commercial gas turbine materials are described. Development costs, estimated payoffs and probabilities of success are discussed. The materials technologies investigated are: (1) single crystal turbine blades, (2) high strength hot isostatic pressed turbine disk, (3) advanced oxide dispersion strengthened burner liner, (4) bore entry cooled hot isostatic pressed turbine disk, (5) turbine blade tip - outer airseal system, and (6) advance turbine blade alloys.

Bisset, J. W.↗
NASA NTRS1977

Cost/benefit analysis of advanced material technologies for small aircraft turbine engines

Cost/benefit studies were conducted on ten advanced material technologies applicable to small aircraft gas turbine engines to be produced in the 1985 time frame. The cost/benefit studies were applied to a two engine, business-type jet aircraft in the 6800- to 9100-Kg (15,000- to 20,000-lb) gross weight class. The new material technologies are intended to provide improvements in the areas of high-pressure turbine rotor components, high-pressure turbine rotor components, high-pressure turbine stator airfoils, and static structural components. The cost/benefit of each technology is presented in terms of relative value, which is defined as a change in life cycle cost times probability of success divided by development cost. Technologies showing the most promising cost/benefits based on relative value are uncooled single crystal MAR-M 247 turbine blades, cooled DS MAR-M 247 turbine blades, and cooled ODS 'M'CrAl laminate turbine stator vanes.

Comey, D. H.↗