Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Nb”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Fabricating with Crystalline Si to Improve Superconducting Detector Performance

We built and measured radio-frequency (RF) loss tangent, tan d, evaluation structures using float-zone quality silicon-on-insulator (SOI) wafers with 5 µ m thick device layers. Superconducting Nb components were fabricated on both sides of the SOI Si device layer. Our main goals were to develop a robust fabrication for using crystalline Si (c-Si) dielectric layers with superconducting Nb components in a wafer bonding process and to confirm that tan d with c-Si dielectric layers was reduced at RF frequencies compared to devices fabricated with amorphous dielectrics, such as SiO2 and SixNy, where tan d ~ 10-3. Our primary test structure used a Nb coplanar waveguide (CPW) readout structure capacitively coupled to LC resonators, where the capacitors were defined as parallel-plate capacitors on both sides of a c-Si device layer using a wafer bonding process with benzocyclobutene (BCB) wafer bonding adhesive. Our control experiment, to determine the intrinsic tan d in the SOI device layer without wafer bonding, also used Nb CPW readout coupled to LC resonators; however, the parallel-plate capacitors were fabricated on both sides of the Si device layer using a deep reactive ion etch (DRIE) to access the c-Si underside through the buried oxide and handle Si layers in the SOI wafers. We found that our wafer bonded devices demonstrated F· d = (8 ± 2) × 10-5, where F is the filling fraction of two-level states (TLS). For the control experiment, F· d = (2.0 ± 0.6) × 10-5, and we discuss what may be degrading the performance in the wafer bonded devices as compared to the control devices.

Beyer, A D↗

CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Molecular dynamics simulation of effects of solutes on dislocation propagation in Ni-based superalloys

Ni-based superalloys are used in the hot sections of jet turbine engines because of their high strength, stability and resistance to oxidation. The properties of these alloys can be further optimized by adding alloying elements. Therefore, a fundamental knowledge on the effect of different elements on properties of Ni-based superalloys is required. Molecular dynamics simulation could shed light here but its application is hindered by the absence of reliable and computationally cheap semi-empirical potential of the interatomic interaction for 4 and more element alloys. We will present a new Ni-Al-Cr-Nb Finnis-Sinclair (FS) potential specially designed to simulate the dislocation propagation from to  phase. In order to construct this potential, we designed a special algorithm to incorporate the data on element partitioning in the potential development procedure. For example, it is known from experiment, that Cr is mostly present in the gamma phase. Figure 1 shows a snapshot obtained after equilibration of the model of the Ni68Al17Cr15 alloy at T=1000 K using the hybrid Monte-Carlo (MC)/molecular dynamics (MD) simulation with the developed semi-empirical potential. One can clearly see that the Cr partitioning is in agreement with the experimental data. We will discuss the developed algorithm to incorporate the solute partition data in details. Using the developed semi-empirical potential, we first investigated the effect of anti-site defects in the  phase on the single dislocation propagation. It was found that the dislocation velocity increases with the increasing of the anti-site defect concentration. This effect was attributed to smaller number of Al-Al pairs forming during the dislocation migration in the presence of the anti-site defects. Next, we investigated the effect of Nb on the dislocation pair propagation in the Kolbe mechanism. It was found that the addition of Nb leads to considerable decrease in the dislocation propagation rate. This is in agreement with the experimental data on the effect of Nb on the creep resistance of the Ni-based superalloys. We will discuss the origin of this effect.

Mikhail I. Mendelev↗

Flux Improvement based on Machine Learning for the CERES FluxByCldTyp Data Product

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere and surface flux data for climate studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models. The FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate their broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Improving Radiative Fluxes for the CERES FluxByCldTyp Data Product Using Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

Short-Term Elevated Temperature Mechanical Performance and Microstructure of A Niobium-Zirconium Alloy Produced via Laser Powder Bed Fusion In-Situ Alloying

Nb-1Zr is a readily fabricable, dispersion-strengthened niobium alloy with improved elevated temperature properties compared to commercially pure niobium. This low to moderate strength niobium alloy is desirable in thermal management systems for fission power and propulsion applications; however, pre-alloyed spherical feedstock for powder-based additive manufacturing processes is generally unavailable. Laser powder bed fusion (L-PBF) in-situ alloying of a Nb-1Zr chemistry was performed using a high-purity niobium feedstock coated with 1 wt% of zirconium-based ceramic compound nano-powders: ZrO 2 , ZrC, and ZrH 2 . The additively manufactured material was mechanically tested at elevated temperatures within a controlled environment in the as-built condition. For comparison, traditionally manufactured wrought feedstock was also tested within an identical environment. Examination of the materials’ microstructure and short-term elevated temperature mechanical response determined: in-situ alloying of spherical Nb powder feedstock with Zr-based ceramic nanoparticles can be successfully implemented; the ZrO 2 addition offered the greatest elevated temperature stability and strength but exhibited brittle behavior; the ZrC addition achieved a balance of room temperature ductility and elevated temperature strength; and the ZrH 2 -modified material had the lowest as-built interstitial content and showed high ductility with mechanical performance most similar to wrought Nb-1Zr.

Niobium Alloy↗

Low vapor pressure braze alloys for thermionic energy converters

The evaluation of cesium diode electrode materials called for braze fillers with very low vapor pressures and a wide range of melting points. Binary alloys of low vapor pressure refractory metals were chosen to fill this need. These alloys of Th, Zr, Hf, Ru, Nb, Ir, Mo, Ta, Os, Re, and W have reported melting point minima or eutectics from 1,510 K to above 3,000 K. Preliminary data are compiled on the use of several of these braze alloys. Melting points and surface wetting on a Ta base are given. Results of brazing Ir, LaB6, Nb, Re, W, and Zr-22 wt % ZrO2 materials into Ta and Nb-1% Zr bases are presented. Current braze usage is summarized.

Bair, V. L.↗

Low vapor pressure braze alloys for thermionic energy converters

Preliminary results in the use of some low-vapor-pressure braze alloys are reported; these are binary alloys of refractory metals (Th, Zr, Hf, Ru, Nb, Ir, Mo, Ta, Os, Re, W) with vapor pressures below 0.1 nanotorr at 1500 K or 10 microtorr at 2000 K. The melting point minima or eutectics of the alloys range from 1510 K to above 3000 K. Melting points and surface wetting on a Ta base are given. Results are presented on brazing of Ir, LaB6, Nb, Re, W, and ZrO2 (with 22 wt % Zr) into a Ta base or a Nb-1% Zr base. The results are applicable in electrode screening programs for thermionic cesium diodes.

Bair, V. L.↗

Flux-flow voltages during guided flux collapse from hollow superconducting cylinders

Voltages across diametrically opposite contact pairs on the outer surface of superconducting Nb tubes are found to depend dramatically upon the spatial configuration of the voltage-measuring leads relative to the positions of the moving magnetic flux lines. Experiments have been conducted to study these voltages for different wall thicknesses and for a variety of arrangements of the leads when flux in the hole and the wall of the Nb tube is made to exit or enter, completely or partially, by applying heat at a narrow strip along its length. Using the critical-state concept, a model for the change of flux and the resulting electric fields in the Nb tube on application of a heat pulse is presented. The resulting time-dependent and time-integrated voltages are calculated in excellent quantitative agreement with the experimental results. These results show that the flux-flow voltages across two contact points on a superconductor arise from the generation of an induced electric field over a chosen path in the superconductor between the contact points and from a change of magnetic flux through the surface bounded by the measuring leads and the chosen path in the superconductor.

Khanna, S. M.↗

Containerless undercooling and solidification in drop tubes

A containerless low-gravity environment, produced within a 32 m drop tube apparatus, has been used to undercool and solidify metals, alloys or glasses by eliminating crucible induced nucleation processes. Niobium droplets with diameters in the range of 2 to 5 mm have been undercooled by 525 K which corresponds to the maximum undercooling reported by Turnbull and others on fine dispersions of low melting point metals. Solidification at large undercooling resulted in single crystalline spheres with the formation of interdendritic shrinkage channels on the sample surface rather than interior shrinkage cavities. The grain refinement as observed for Ni samples undercooled and solidified in fused silica crucibles does not occur in free-falling drops of Nb. A calculated solidification speed of undercooled Nb is compared to Ni. A solidification speed of 320 m/s is found for the Nb drops. This solidification speed is greater than or comparable to the solidification speeds calculated in splat cooled samples. Thus, a drop tube apparatus can be useful in the preparation and study of high temperature metastable compounds or alloys in bulk form.

Lacy, L. L.↗

Sputtering of Al2O3 and LiNbO3 in the electronic stopping region

Because of recent interest in the role played by the thermal properties of materials that exhibit high energy sputtering, Al2O3 and LiNbO3 were sputtered with chlorine ions at energies between 3 MeV and 25 MeV. To detect the sputtered Al and Nb we employ thin carbon catcher foils, which are analyzed with Rutherford scattering in the forward direction. Al surface densities of 10 to the 14th/sq cm and Nb surface densities of 10 to the 13th/sq cm are easily measured. The sputtering yields for both Al2O3 and LiNbO3 increase rapidly with increasing chlorine energy, and the Al and Nb yields are both approximately 0.2 at 20 MeV. Tests for dose, beam current, and contamination effects will be discussed.

Qiu, Y.↗

Backstreaming ions from oblique earth bow shocks

One-dimensional, hybrid (particle ions, fluid electrons) numerical simulations of oblique shock structure are used to analyze the mechanism by which solar wind ions can be reflected off the earth's bow shock front and escape upstream. It is shown that no backstreaming ions are produced in the simulation over 50-90 degrees of theta(nB), the angle between the interplanetary magnetic field and the shock normal. Backstreaming ions are emitted for theta(nB) of 45 degrees or less, with characteristics in reasonable agreement with those of observed reflected ion streams. The simulated shock structure becomes rather turbulent as theta(nB) decreases from 45 to 30 degrees. Analysis of the backstreaming ion trajectories shows that all backstreaming ions are originally specularly reflected. The oblique shock structure and effects such as whistler formation and ion heating are discussed.

Leroy, M. M.↗

Creep properties of PWC-11 base metal and weldments as affected by heat treatment

In a preliminary study using single specimens for each condition, PWC-11 (a niobium-base alloy with a nominal composition of Nb-1%Zr-0.1%C) was creep tested at 1350 K and 40 MPa. Base metal specimens and specimens with transverse electron beam welds were tested with and without a 1000 hr, 1350 K aging treatment prior to testing. In the annealed condition (1 hr at 1755 K + 2 hr at 1475 K), the base metal exhibited superior creep strength compared to the nonaged condition, reaching 1 percent strain in 3480 hr. A 1000 hr, 1350 K aging treatment prior to creep testing had a severe detrimental effect on creep strength of the base metal and transverse electron beam weldments, reducing the time to attain 1 percent strain by an order of magnitude. Extrapolated temperature compensated creep rates indicate that the present heat of PWC-11 may be four times as creep resistant as similarly tested Nb-1%Zr. The extrapolated stress to achieve 1 percent creep strain in 7 yr at 1350 K is 2.7 MPa for annealed Nb-1%Zr and 12 MPa for annealed and aged PWC-11 base metal with and without a transverse electron beam weld.

Titran, R. H.↗

Thermodynamic analysis of chemical compatibility of several reinforcement materials with niobium aluminides

Chemical compatibility of several reinforcement materials with three niobium aluminides, Nb3Al, Nb2Al, and NbAl3, were examined from thermodynamic considerations. The reinforcement materials considered in this study include carbides, borides, nitrides, oxides, silicides, and Engel-Brewer compounds. Thermodynamics of the Nb-Al system were reviewed and activities of Nb and Al were derived at desired calculation temperatures. Criteria for chemical compatibility between the reinforcement material and Nb-Al compounds have been defined and several chemically compatible reinforcement materials have been identified.

Misra, Ajay K.↗

Microstructures in rapidly solidified niobium aluminides

The microstructures of niobium aluminides produced by chill block melt spinning were compared to those of niobium aluminides produced by conventional casting. The rapidly solidified alloys were rapidly solidified by melt spinning in an argon atmosphere, and the melt-spun ribbons were examined by optical, X-ray, and TEM techniques. Microstructures were found to range from single-phase for Nb-75 at. pct Al (NbAl3) to two phase for Nb-46 at. pct Al (NbAl3 + Nb2Al). It was found that the melt spinning of Nb-aluminides produced finer grained microstructures than those produced in induction-melted ingots or in powders produced by the rotating electrode process. Ternary additions such as Cr, Ti, and Si tended to form intermetallic phases along the grain boundaries.

Hebsur, Mohan G.↗

Thermodynamic analysis of chemical compatibility of ceramic reinforcement materials with niobium aluminides

Chemical compatibility of several reinforcement materials with three niobium aluminides, Nb3Al, Nb2Al, and NbAl3, were examined from thermodynamic considerations. The reinforcement materials considered in this study include carbides, borides, nitrides, oxides, silicides, and Engel-Brewer compounds. Thermodynamics of the Nb-Al system were reviewed and activities of Nb and Al were derived at desired calculation temperatures. Criteria for chemical compatibility between the reinforcement material and Nb-Al compounds have been defined and several chemically compatible reinforcement materials have been identified.

Misra, Ajay K.↗