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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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NASA NTRS1986

Undercooled and rapidly quenched Ni-Mo alloys

Hypoeutectic, eutectic, and hypereutectic nickel-molybdenum alloys were rapidly solidified by both bulk undercooling and melt spinning techniques. Alloys were undercooled in both electromagnetic levitation and differential thermal analysis equipment. The rate of recalescence depended upon the degree of initial undercooling and the nature (faceted or nonfaceted) of the primary nucleating phase. Alloy melts were observed to undercool more in the presence of primary Beta (NiMo intermetallic) phase than in gamma (fcc solid solution) phase. Melt spinning resulted in an extension of molybdenum solid solubility in gamma nickel, from 28 to 37.5 at % Mo. Although the microstructures observed by undercooling and melt spinning were similar the microsegregation pattern across the gamma dendries was different. The range of microstructures evolved was analyzed in terms of the nature of the primary phase to nucleate, its subsequent dendritic growth, coarsening and fragmentation, and final solidification of interfenderitic liquid.

Tewari, S. N.↗
NASA NTRS1987

Effect of undercooling on the microstructure of Ni-35 at. pct Mo (eutectic) and Ni-38 at. pct Mo (hypereutectic) alloys

Ni-35 at. pct Mo and Ni-38 at. pct Mo alloy specimens have been solidified from various levels of undercooling in the differential thermal analysis and the electromagnetic levitation units in a pyrex/vycor bed. The evolution of the microstructure in the solified specimens has been examined in terms of the degree of undercooling, the nature of the first phase to nucleate from the melt, and the specimen cooling rate. The melt has been observed to undercool more in the presence of intermetallic NiMo (beta) phase as compared to that in the presence of nickel-rich solid solution (gamma). The 'anomalous eutectic' type of microstructure has been shown to result from the initial formation of the dendritic skeleton of either of the two phases, its segmentation due to convection and ripening, and the subsequent nucleation of the other phase in the interdendritic liquid regions. The recalescence behavior has been examined as a function of undercooling and the nature of the phase nucleating first in the melt.

Tewari, S. N.↗
NASA NTRS1987

Characterization of ion beam modified ceramic wear surfaces using Auger electron spectroscopy

An investigation of the surface chemistry and morphology of the wear surfaces of ceramic material surfaces modified by ion beam mixing has been conducted using Auger electron spectroscopy and secondary electron microscopy. Studies have been conducted on ceramic/ceramic friction and wear couples made up of TiC and NiMo-bonded TiC cermet pins run against Si3N4 and partially stabilized zirconia disc surfaces modified by the ion beam mixing of titanium and nickel, as well as ummodified ceramic/ceramic couples in order to determine the types of surface changes leading to the improved friction and wear behavior of the surface modified ceramics in simulated diesel environments. The results of the surface analyses indicate that the formation of a lubricating oxide layer of titanium and nickel, is responsible for the improvement in ceramic friction and wear behavior. The beneficial effect of this oxide layer depends on several factors, including the adherence of the surface modified layer or subsequently formed oxide layer to the disc substrate, the substrate materials, the conditions of ion beam mixing, and the environmental conditions.

Wei, W.↗
NASA NTRS1987

Undercooled and rapidly quenched Ni-Mo alloys

Hypoeutectic, eutectic, and hypereutectic nickel-molybdenum alloys were rapidly solidified by both bulk undercooling and melt spinning techniques. Alloys were undercooled in both electromagnetic levitation and differential thermal analysis equipment. The rate of recalescence depended upon the degree of initial undercooling and the nature (faceted or nonfaceted) of the primary nucleating phase. Alloy melts were observed to undercool more in the presence of primary Beta (NiMo intermetallic) phase than in gamma (fcc solid solution) phase. Melt spinning resulted in an extension of molybdenum solid solubility in gamma nickel, from 28 to 37.5 at. pct Mo. Although the microstructures observed by undercooling and melt spinning were similar, the microsegregation pattern across the gamma dendries was different. The range of microstructures evolved was analyzed in terms of the nature of the primary phase to nucleate, its subsequent dendritic growth, coarsening and fragmentation, and final solidification of interfenderitic liquid.

Tewari, S. N.↗
NASA NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗
NASA NTRS2024

Urban Air Quality Management at Low-Cost Using Micro Air Sensors: A Case Study From Accra, Ghana

Urban air quality management is dependent on the availability of local air pollution data. In many major urban centers of Africa, there is limited to non-existent information on air quality. This is gradually changing in part due to the increasing use of micro air sensors which have the potential to enable the generation of ground-based air quality data at fine scales for understanding local emission trends. Regional literature on the application of the high-resolution data for emission source identification in this region is limited. In this study a micro air sensor was co-located at the Physics Department, University of Ghana with a reference grade instrument to evaluate its performance for estimating PM2.5 pollution accurately at fine scales and the value of this data in identification of local sources and their behavior over time. For this study 15 weeks of data at hourly resolution with approximately 2500 data pairs are generated and analyzed (June 01, 2023, to September 15, 2023). For this time period a coefficient of determination (r 2 ) of 0.83 was generated with a mean absolute error (MAE) of 5.44 μgm -3 between the pre local calibration micro air sensor (i.e. out of box) and the reference-grade instrument. Following currently accepted best practice methods (see e.g., PAS4023) a domain specific (i.e. local) calibration factor was generated using a multi-linear regression model and when this factor is applied to the micro air sensor data, a reduction i.e., improvement in MAE to 1.43 μgm -3 was found. Daily variation was calculated, a receptor model was applied, and time series plots as a function of wind direction were generated, including PM2.5/PM10 ratio scatter and count plots to explore the utility of this observational approach for local source identification. The 3 data sets were compared (out of box, domain calibrated and reference-grade) and it was found that although there were variations in the data reported, source areas highlighted based on these data were similar, with input from local sources such as traffic emissions and biomass burning. As the temporal resolution of observational data associated with these micro air sensors is higher than for reference grade instruments (primarily due to costs and logistics limitations), they have the potential to provide insight into the complex, often hyper localized sources associated with urban areas, such as those found in major African cities.

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