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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Have Tropical Cyclones Been Feeding More Extreme Rainfall?

We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events and 21% of rain amount in WNP. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slight more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Omega are mixed, and the long-term relationship between TC rain and warm pool areas are strongly influenced by interannual and interdecadal variability.

Lau, K.-M.↗
NASA NTRS2008

Have Tropical Cyclones been Feeding More Extreme Rainfall?

We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data ; and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-gain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events, and 21% of rain amount in WN.P. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for bout periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slightly more than 50% of the change in observed trend in total TC rainfall. In. WNP, trend signals for Omega are mixed, and the loner term relationship between TC rain and warm pool area is strongly influenced by interannual and interdecadal variability.

Lau, K.-M.↗
NASA NTRS2018

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗
NASA NTRS2020

Revisiting the Relationship between Atlantic Dust and Tropical Cyclone Activity using Aerosol Optical Depth Reanalyses: 2003-2018

Previous studies have noted a relationship between African dust and Atlantic tropical cyclone (TC) activity. However, due to the limitations of past dust analyses, the strength of this relationship remains uncertain. The emergence of aerosol reanalyses, including the Navy Aerosol Analysis and Prediction System (NAAPS) aerosol optical depth (AOD) reanalysis, NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and ECMWF Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA), enables an investigation of the relationship between African dust and TC activity over the tropical Atlantic and Caribbean in a consistent temporal and spatial manner for 2003–2018. Although June–July–August (JJA) 550 nm dust AOD (DAOD) from all three reanalysis products correlates significantly over the tropical Atlantic and Caribbean, the difference in DAOD magnitude between products can be as large as 60 % over the Caribbean and 20 % over the tropical North Atlantic. Based on the three individual reanalyses, we have created an aerosol multi-reanalysis consensus (MRC). The MRC presents overall better root mean square error over the tropical Atlantic and Caribbean compared to individual reanalyses when verified with ground-based AErosol RObotic NETwork (AERONET) AOD measurements. Each of the three individual reanalyses and the MRC have significant negative correlations between JJA Caribbean DAOD and seasonal Atlantic accumulated cyclone energy (ACE), while the correlation between JJA tropical North Atlantic DAOD and seasonal ACE is weaker. Possible reasons for this regional difference are provided. A composite analysis of 3 high-JJA-Caribbean-DAOD years versus 3 low-JJA-Caribbean-DAOD years reveals large differences in overall Atlantic TC activity. We also show that JJA Caribbean DAOD is significantly correlated with large-scale fields associated with variability in interannual Atlantic TC activity including zonal wind shear, mid-level moisture, and sea surface temperature (SST), as well as the El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), implying confounding effects of these factors on the dust–TC relationship. We find that seasonal Atlantic DAOD and the AMM, the leading mode of coupled Atlantic variability, are inversely related and intertwined in the dust–TC relationship. Overall, DAOD in both the tropical Atlantic and Caribbean is negatively correlated with Atlantic hurricane frequency and intensity, with stronger correlations in the Caribbean than farther east in the tropical North Atlantic.

Dust particles↗
NASA NTRSDate not supplied

Analyzing the Tropical Cyclone Diurnal Cycle using GPM, TROPICS, and other Spaceborne Observations

Tropical cyclones (TCs) exhibit a distinct diurnal cycle of high clouds and rainfall, marked by an expansion of the TC cirrus canopy during the day and enhanced rainfall overnight. Recent modeling work also has uncovered a diurnal cycle of low-level radial and tangential winds in simulated storms, marked by an expansion of the surface wind field overnight and into the morning, along with increasing maximum wind speed in the eyewall. These results suggest that diurnal changes in radiative heating tendencies not only affect upper-level cirrus clouds and precipitating convection, but also the low-level circulation. This presentation will characterize expansions of the TC rain field using the Global Precipitation Measurement (GPM) Mission’s Integrated Multi-Satellite Retrievals for GPM (IMERG) half-hourly precipitation estimates. The Level 3 IMERG-Final rainfall data are azimuthally averaged about TC center positions in the Atlantic and Eastern Pacific basins, accounting for asymmetries due to vertical wind shear and storm motion. Preliminary results indicate that the TC rain field expands overnight and through the morning, reaching its maximum extent during the afternoon. This evolution is considerably asymmetric, however, with expansion favored downshear of the storm center. The results are broadly consistent with previous work that characterized the TC diurnal cycle using other observations and simulations. A similar analysis is performed using microphysical retrievals from the GPM Goddard Profiling algorithm and lightning data from the Geostationary Lightning Mapper to understand the relationship between the diurnal cycle, ice microphsyics, and lightning. Finally, with the ongoing Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, we will discuss our plans to leverage TROPICS for enhanced observation of the TC diurnal cycle.

Patrick Duran↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗
DOE OSTI2023

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tri-structural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty due to the nub-to-shell clearance caused by a design error of AGR-5/6/7 capsules. The thermal model was revised to examine the most probable graphite offset position for six different days during the irradiation for Capsules 1 and 2. The analysis varied the offset distance and azimuthal direction at both the top and bottom of the holder. The best-fit offset was estimated based on the minimum root mean square error of the residuals (measured minus calculated) for the operational thermocouples (TCs). From these results, the following conclusions were made: (1) The holder offsets led to slightly lower average temperatures but wider temperature variations (lower minimum and higher peak fuel temperatures) for both Capsule 1 and Capsule 2. (2) During earlier cycles (162A–164B), when numerous TCs were still operational, the best-fit offset distance varied over a specific range for both the top and bottom ([0.002–0.0035 in.] for Capsule 1 and [0.003-0.004 in] for Capsule 2). In contrast, the offset azimuthal direction varied widely, especially for the offset at the bottom of the Capsule 1 holder. This is because holder movement was somewhat constrained at the top of Capsule 1 by the TC leads running through the capsule head and into the holder and by the through tubes in Capsule 2, but the Capsule 1 bottom did not have this type of constraint. (3) During later cycles, when all TCs failed, applying the maximum possible offset of 0.006 in. to the northwest direction for both the top and bottom resulted in a calculated peak fuel temperature of 1557? in Capsule 1 (i.e., a 135? increase from 1422? with zero offset on September 20, 2019 (166A)); the maximum offset of 0.0068 in. to the south for both top and bottom resulted in a calculated peak fuel temperature of 1110°C in Capsule 2 on April 20, 2020 (i.e., a 116? increase from 994? with zero offset (168A)). High peak fuel temperatures in Capsule 1 during Cycle 166A could be the cause of massive particle failure near the end of this cycle. (4) Even though the highest temperature at the tip of Type-N TCs, such as TC-1-7, slightly exceeded 1000?, the temperature along the TC wire reached as high as 1335? assuming an offset of 0.006 in. in the northwest of Capsule 1 holder near the end of Cycle 166A. This temperature significantly exceeds the temperature threshold at which TC degradation is expected to occur, ultimately contributing to considerable particle failures in Capsule 1. For eight Type-N TCs in Capsule 2, the peak TC line temperature was much lower (i.e., 1029°C for TC-2-5), assuming maximum offset of 00068 in. to the south during cycle 168A.

advanced gas reactors↗
DOE OSTI2023

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tri-structural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty due to the nub-to-shell clearance caused by a design error of AGR-5/6/7 capsules. The thermal model was revised to examine the most probable graphite offset position for six different days during the irradiation for Capsules 1 and 2. The analysis varied the offset distance and azimuthal direction at both the top and bottom of the holder. The best-fit offset was estimated based on the minimum root mean square error of the residuals (measured minus calculated) for the operational thermocouples (TCs). From these results, the following conclusions were made: (1) The holder offsets led to slightly lower average temperatures but wider temperature variations (lower minimum and higher peak fuel temperatures) for both Capsule 1 and Capsule 2. (2) During earlier cycles (162A–164B), when numerous TCs were still operational, the best-fit offset distance varied over a specific range for both the top and bottom ([0.002–0.0035 in.] for Capsule 1 and [0.003-0.004 in] for Capsule 2). In contrast, the offset azimuthal direction varied widely, especially for the offset at the bottom of the Capsule 1 holder. This is because holder movement was somewhat constrained at the top of Capsule 1 by the TC leads running through the capsule head and into the holder and by the through tubes in Capsule 2, but the Capsule 1 bottom did not have this type of constraint. (3) During later cycles, when all TCs failed, applying the maximum possible offset of 0.006 in. to the northwest direction for both the top and bottom resulted in a calculated peak fuel temperature of 1557? in Capsule 1 (i.e., a 135? increase from 1422? with zero offset on September 20, 2019 (166A)); the maximum offset of 0.0068 in. to the south for both top and bottom resulted in a calculated peak fuel temperature of 1110°C in Capsule 2 on April 20, 2020 (i.e., a 116? increase from 994? with zero offset (168A)). High peak fuel temperatures in Capsule 1 during Cycle 166A could be the cause of massive particle failure near the end of this cycle. (4) Even though the highest temperature at the tip of Type-N TCs, such as TC-1-7, slightly exceeded 1000?, the temperature along the TC wire reached as high as 1335? assuming an offset of 0.006 in. in the northwest of Capsule 1 holder near the end of Cycle 166A. This temperature significantly exceeds the temperature threshold at which TC degradation is expected to occur, ultimately contributing to considerable particle failures in Capsule 1. For eight Type-N TCs in Capsule 2, the peak TC line temperature was much lower (i.e., 1029°C for TC-2-5), assuming maximum offset of 00068 in. to the south during cycle 168A.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tri-structural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty due to the nub-to-shell clearance caused by a design error of AGR-5/6/7 capsules. The thermal model was revised to examine the most probable graphite offset position for six different days during the irradiation for Capsules 1 and 2. The analysis varied the offset distance and azimuthal direction at both the top and bottom of the holder. The best-fit offset was estimated based on the minimum root mean square error of the residuals (measured minus calculated) for the operational thermocouples (TCs). From these results, the following conclusions were made: (1) The holder offsets led to slightly lower average temperatures but wider temperature variations (lower minimum and higher peak fuel temperatures) for both Capsule 1 and Capsule 2. (2) During earlier cycles (162A–164B), when numerous TCs were still operational, the best-fit offset distance varied over a specific range for both the top and bottom ([0.002–0.0035 in.] for Capsule 1 and [0.003-0.004 in] for Capsule 2). In contrast, the offset azimuthal direction varied widely, especially for the offset at the bottom of the Capsule 1 holder. This is because holder movement was somewhat constrained at the top of Capsule 1 by the TC leads running through the capsule head and into the holder and by the through tubes in Capsule 2, but the Capsule 1 bottom did not have this type of constraint. (3) During later cycles, when all TCs failed, applying the maximum possible offset of 0.006 in. to the northwest direction for both the top and bottom resulted in a calculated peak fuel temperature of 1557? in Capsule 1 (i.e., a 135? increase from 1422? with zero offset on September 20, 2019 (166A)); the maximum offset of 0.0068 in. to the south for both top and bottom resulted in a calculated peak fuel temperature of 1110°C in Capsule 2 on April 20, 2020 (i.e., a 116? increase from 994? with zero offset (168A)). High peak fuel temperatures in Capsule 1 during Cycle 166A could be the cause of massive particle failure near the end of this cycle. (4) Even though the highest temperature at the tip of Type-N TCs, such as TC-1-7, slightly exceeded 1000?, the temperature along the TC wire reached as high as 1335? assuming an offset of 0.006 in. in the northwest of Capsule 1 holder near the end of Cycle 166A. This temperature significantly exceeds the temperature threshold at which TC degradation is expected to occur, ultimately contributing to considerable particle failures in Capsule 1. For eight Type-N TCs in Capsule 2, the peak TC line temperature was much lower (i.e., 1029°C for TC-2-5), assuming maximum offset of 00068 in. to the south during cycle 168A.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Materials Data on Al6Tc by Materials Project

TcAl6 crystallizes in the orthorhombic Cmcm space group. The structure is three-dimensional. Tc is bonded in a distorted q6 geometry to ten Al atoms. There are a spread of Tc–Al bond distances ranging from 2.52–2.67 Å. There are three inequivalent Al sites. In the first Al site, Al is bonded in a 2-coordinate geometry to two equivalent Tc and nine Al atoms. There are a spread of Al–Al bond distances ranging from 2.69–2.96 Å. In the second Al site, Al is bonded in a 2-coordinate geometry to two equivalent Tc and eight Al atoms. All Al–Al bond lengths are 2.97 Å. In the third Al site, Al is bonded in a 1-coordinate geometry to one Tc and ten Al atoms. There are one shorter (2.53 Å) and one longer (2.70 Å) Al–Al bond lengths.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on U4Si6Tc7 by Materials Project

U4Tc7Si6 crystallizes in the cubic Im-3m space group. The structure is three-dimensional. U+3.25+ is bonded in a hexagonal planar geometry to six equivalent Tc3- atoms. All U–Tc bond lengths are 2.91 Å. There are two inequivalent Tc3- sites. In the first Tc3- site, Tc3- is bonded to four equivalent U+3.25+, four equivalent Tc3-, and four equivalent Si+1.33+ atoms to form distorted TcU4Si4Tc4 cuboctahedra that share corners with four equivalent TcU4Si4Tc4 cuboctahedra, corners with four equivalent TcSi6 octahedra, edges with eight equivalent TcU4Si4Tc4 cuboctahedra, and faces with six equivalent TcU4Si4Tc4 cuboctahedra. The corner-sharing octahedral tilt angles are 53°. All Tc–Tc bond lengths are 2.91 Å. All Tc–Si bond lengths are 2.58 Å. In the second Tc3- site, Tc3- is bonded to six equivalent Si+1.33+ atoms to form corner-sharing TcSi6 octahedra. All Tc–Si bond lengths are 2.55 Å. Si+1.33+ is bonded in a 5-coordinate geometry to five Tc3- atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on LiTc2Pd by Materials Project

LiTc2Pd is Heusler structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Li is bonded in a distorted body-centered cubic geometry to eight equivalent Tc and six equivalent Pd atoms. All Li–Tc bond lengths are 2.64 Å. All Li–Pd bond lengths are 3.05 Å. Tc is bonded in a body-centered cubic geometry to four equivalent Li and four equivalent Pd atoms. All Tc–Pd bond lengths are 2.64 Å. Pd is bonded in a 8-coordinate geometry to six equivalent Li and eight equivalent Tc atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on MnTcPd by Materials Project

TcMnPd is half-Heusler structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Tc is bonded to four equivalent Mn and six equivalent Pd atoms to form distorted TcMn4Pd6 tetrahedra that share corners with four equivalent PdMn4Tc6 tetrahedra, corners with six equivalent TcMn4Pd6 tetrahedra, edges with six equivalent PdMn4Tc6 tetrahedra, and faces with twelve equivalent TcMn4Pd6 tetrahedra. All Tc–Mn bond lengths are 2.51 Å. All Tc–Pd bond lengths are 2.89 Å. Mn is bonded in a body-centered cubic geometry to four equivalent Tc and four equivalent Pd atoms. All Mn–Pd bond lengths are 2.51 Å. Pd is bonded to six equivalent Tc and four equivalent Mn atoms to form distorted PdMn4Tc6 tetrahedra that share corners with four equivalent TcMn4Pd6 tetrahedra, corners with six equivalent PdMn4Tc6 tetrahedra, edges with six equivalent TcMn4Pd6 tetrahedra, and faces with twelve equivalent PdMn4Tc6 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on ZnTcMo by Materials Project

MoTcZn is half-Heusler structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Mo is bonded in a body-centered cubic geometry to four equivalent Tc and four equivalent Zn atoms. All Mo–Tc bond lengths are 2.59 Å. All Mo–Zn bond lengths are 2.59 Å. Tc is bonded to four equivalent Mo and six equivalent Zn atoms to form distorted TcZn6Mo4 tetrahedra that share corners with four equivalent ZnTc6Mo4 tetrahedra, corners with six equivalent TcZn6Mo4 tetrahedra, edges with six equivalent ZnTc6Mo4 tetrahedra, and faces with twelve equivalent TcZn6Mo4 tetrahedra. All Tc–Zn bond lengths are 2.99 Å. Zn is bonded to four equivalent Mo and six equivalent Tc atoms to form distorted ZnTc6Mo4 tetrahedra that share corners with four equivalent TcZn6Mo4 tetrahedra, corners with six equivalent ZnTc6Mo4 tetrahedra, edges with six equivalent TcZn6Mo4 tetrahedra, and faces with twelve equivalent ZnTc6Mo4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on CaTaTc by Materials Project

CaTaTc is half-Heusler structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Ca is bonded in a 10-coordinate geometry to four equivalent Ta and six equivalent Tc atoms. All Ca–Ta bond lengths are 2.78 Å. All Ca–Tc bond lengths are 3.21 Å. Ta is bonded in a body-centered cubic geometry to four equivalent Ca and four equivalent Tc atoms. All Ta–Tc bond lengths are 2.78 Å. Tc is bonded in a 10-coordinate geometry to six equivalent Ca and four equivalent Ta atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on MnAlTc by Materials Project

TcMnAl is half-Heusler structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Tc is bonded in a 4-coordinate geometry to six equivalent Mn and four equivalent Al atoms. All Tc–Mn bond lengths are 2.91 Å. All Tc–Al bond lengths are 2.52 Å. Mn is bonded in a 10-coordinate geometry to six equivalent Tc and four equivalent Al atoms. All Mn–Al bond lengths are 2.52 Å. Al is bonded in a body-centered cubic geometry to four equivalent Tc and four equivalent Mn atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on TaTcPb2 by Materials Project

TaTcPb2 crystallizes in the monoclinic Cm space group. The structure is three-dimensional. Ta is bonded in a distorted body-centered cubic geometry to four equivalent Tc and ten Pb atoms. There are a spread of Ta–Tc bond distances ranging from 2.99–3.04 Å. There are a spread of Ta–Pb bond distances ranging from 3.02–3.50 Å. Tc is bonded in a distorted body-centered cubic geometry to four equivalent Ta and four equivalent Pb atoms. There are one shorter (3.01 Å) and three longer (3.02 Å) Tc–Pb bond lengths. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Ta, four equivalent Tc, and four equivalent Pb atoms to form a mixture of distorted face and corner-sharing PbTa6Tc4Pb4 tetrahedra. All Pb–Pb bond lengths are 3.02 Å. In the second Pb site, Pb is bonded to four equivalent Ta and four equivalent Pb atoms to form distorted PbTa4Pb4 tetrahedra that share corners with twelve equivalent PbTa6Tc4Pb4 tetrahedra, edges with twelve equivalent PbTa4Pb4 tetrahedra, and faces with four equivalent PbTa6Tc4Pb4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Ti2AlTc by Materials Project

Ti2TcAl is Heusler structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Ti is bonded in a body-centered cubic geometry to four equivalent Tc and four equivalent Al atoms. All Ti–Tc bond lengths are 2.72 Å. All Ti–Al bond lengths are 2.72 Å. Tc is bonded in a distorted body-centered cubic geometry to eight equivalent Ti and six equivalent Al atoms. All Tc–Al bond lengths are 3.14 Å. Al is bonded in a distorted body-centered cubic geometry to eight equivalent Ti and six equivalent Tc atoms.

36 MATERIALS SCIENCE↗