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At least 19 records

Materials Data on Ca(VN)2 by Materials Project

Ca(VN)2 crystallizes in the tetragonal P-4m2 space group. The structure is two-dimensional and consists of one Ca(VN)2 sheet oriented in the (0, 0, 1) direction. Ca2+ is bonded in a 4-coordinate geometry to four equivalent N3- atoms. All Ca–N bond lengths are 2.32 Å. V2+ is bonded in a bent 120 degrees geometry to two equivalent N3- atoms. Both V–N bond lengths are 1.85 Å. N3- is bonded to two equivalent Ca2+ and two equivalent V2+ atoms to form corner-sharing NCa2V2 tetrahedra.

36 MATERIALS SCIENCE↗

Materials Data on VN by Materials Project

VN is Zincblende, Sphalerite structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. V3+ is bonded to four equivalent N3- atoms to form corner-sharing VN4 tetrahedra. All V–N bond lengths are 1.92 Å. N3- is bonded to four equivalent V3+ atoms to form corner-sharing NV4 tetrahedra.

36 MATERIALS SCIENCE↗

Materials Data on VN by Materials Project

VN is Tetraauricupride structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. V3+ is bonded in a body-centered cubic geometry to eight equivalent N3- atoms. All V–N bond lengths are 2.21 Å. N3- is bonded in a body-centered cubic geometry to eight equivalent V3+ atoms.

36 MATERIALS SCIENCE↗

Materials Data on VN by Materials Project

VN is Halite, Rock Salt structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. V3+ is bonded to six equivalent N3- atoms to form a mixture of edge and corner-sharing VN6 octahedra. The corner-sharing octahedral tilt angles are 0°. All V–N bond lengths are 2.06 Å. N3- is bonded to six equivalent V3+ atoms to form a mixture of edge and corner-sharing NV6 octahedra. The corner-sharing octahedral tilt angles are 0°.

36 MATERIALS SCIENCE↗

Materials Data on VN by Materials Project

VN is Molybdenum Carbide MAX Phase-like structured and crystallizes in the hexagonal P6_3/mmc space group. The structure is three-dimensional. V3+ is bonded to six equivalent N3- atoms to form a mixture of edge, face, and corner-sharing VN6 octahedra. The corner-sharing octahedral tilt angles are 45°. All V–N bond lengths are 2.07 Å. N3- is bonded to six equivalent V3+ atoms to form a mixture of distorted edge and corner-sharing NV6 pentagonal pyramids.

36 MATERIALS SCIENCE↗

Materials Data on VN by Materials Project

VN is Tungsten Carbide structured and crystallizes in the hexagonal P-6m2 space group. The structure is three-dimensional. V3+ is bonded to six equivalent N3- atoms to form a mixture of distorted face, edge, and corner-sharing VN6 pentagonal pyramids. All V–N bond lengths are 2.07 Å. N3- is bonded to six equivalent V3+ atoms to form a mixture of distorted face, edge, and corner-sharing NV6 pentagonal pyramids.

36 MATERIALS SCIENCE↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was -1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching -3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

Climatology of Global Precipitation Measurement Mission Precipitation Regimes and Implications for Global Estimates of Vertical Winds

The Global Precipitation Measurement (GPM) mission Validation Network (VN) framework leverages over 118 ground-based polarimetric Doppler radars to validate a large subset of precipitation measurements and retrievals from the GPM Dual-frequency Precipitation Radar (DPR). Recently, GPM DPR reflectivity profiles within the VN have been classified according to their convective regime using unsupervised machine learning techniques. The archetypal regimes are stratiform, convective, mixed stratiform-convective (e.g., transition regions), and “other” (e.g., peripheral regions of light precipitation). Subcategories within these four primary regimes vary according to the characteristic depth of included reflectivity profiles, resulting in 12 main GPM DPR precipitation profile categories. Polarimetry of ground-based Doppler radars in the VN offers additional insights into the types of precipitation, while pairs of radars positioned near each other enable retrieval of vertical winds via dual-Doppler analysis. Geometrically matched to the DPR reflectivity profiles in the GPM VN, these ground-based data and retrievals contribute more detailed characterization of the distinct kinematic and microphysical structures associated with each of the 12 DPR precipitation regimes. DPR reflectivity profiles linked with wind in the VN are restricted to GPM overpasses of proximal radar pairs that allow dual-Doppler analysis. Although a limited subset of DPR profiles in the VN are matched with vertical motion, agreement between the reflectivity structures paired with wind data and those of the greater DPR dataset in the VN suggest that estimates of vertical motion may be inferred in regions without ground-based measurements. We present a climatology of the 12 convective regimes identified within the DPR VN dataset as well as early efforts to estimate the kinematic and microphysical structures of precipitation profiles within the greater GPM DPR dataset by applying machine learning techniques. Precipitation data paired with global estimates of vertical winds from these efforts offer early insight to and support upcoming missions to retrieve convective mass flux, including the Investigation of Convective Updrafts (INCUS) in the Tropics and the global Atmosphere Observing System (AOS).

Precipitation↗

Nystagmus induced by electrical stimulation of the vestibular and prepositus hypoglossi nuclei in the monkey: evidence for site of induction of velocity storage

Electrical stimulation of the vestibular nuclei (VN) and prepositus hypoglossi nuclei (PPH) of alert cynomolgus monkeys evoked nystagmus and eye deviation while they were in darkness. At some sites in VN, nystagmus and after-nystagmus were induced with characteristics suggesting that velocity storage had been excited. We analyzed these responses and compared them to the slow component of optokinetic nystagmus (OKN) and to optokinetic after-nystagmus (OKAN). We then recorded unit activity in VN and determined which types of nystagmus would be evoked from the sites of recording. Nystagmus and eye deviations were also elicited by electrical stimulation of PPH, and we characterized the responses where unit activity was recorded in PPH. Horizontal slow phase velocity of the VN "storage" responses was contralateral to the side of stimulation. The rising time constants and peak steady-state velocities were similar to those of OKN, and the falling time constants of the after-nystagmus and of OKAN were approximately equal. Both the induced after-nystagmus and OKAN were habituated by stimulation of the VN. When horizontal after-nystagmus was evoked with animals on their sides, it developed yaw and pitch components that tended to shift the vector of the slow phase velocity toward the spatial vertical. Similar "cross-coupling" occurs for horizontal OKAN or for vestibular post-rotatory nystagmus elicited in tilted positions. Thus, the storage component of nystagmus induced by VN stimulation had the same characteristics as the slow component of OKN and the VOR. Positive stimulus sites for inducing nystagmus with typical storage components were located in rostral portions of VN. They lay in caudal ventral superior vestibular nucleus (SVN), dorsal portions of central medial vestibular nucleus (MVN) caudal to the abducens nuclei and in adjacent lateral vestibular nucleus (LVN). More complex stimulus responses, but with contralateral after-nystagmus, were induced from surrounding regions of ventral MVN and LVN, rostral descending vestibular nucleus and the marginal zone between MVN and PPH. Vestibular-only (VO), vestibular plus saccade (VPS) and tonic vestibular pause (TVP) units were identified by extracellular recording. Stimulation near type I lateral and vertical canal-related VO units elicited typical "storage" responses with after-nystagmus in 23 of 29 tracks (79%). Stimulus responses were more complex from the region of neurons with oculomotor-related signals, i.e., TVP or VPS cells, although after-nystagmus was also elicited from these sites. Effects of vestibular nerve and nucleus stimulation were compared.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗

Methods and Results for a Global Precipitation Measurement (GPM) Validation Network Prototype

As one component of a ground validation system to meet requirements for the upcoming Global Precipitation Measurement (GPM) mission, a quasi-operational prototype a system to compare satellite- and ground-based radar measurements has been developed. This prototype, the GPM Validation Network (VN), acquires data from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite and from ground radar (GR) networks in the continental U.S. and participating international sites. PR data serve as a surrogate for similar observations from the Dual-frequency Precipitation Radar (DPR) to be present on GPM. Primary goals of the VN prototype are to understand and characterize the variability and bias of precipitation retrievals between the PR and GR in various precipitation regimes at large scales, and to improve precipitation retrieval algorithms for the GPM instruments. The current VN capabilities concentrate on comparisons of the base reflectivity observations between the PR and GR, and include support for rain rate comparisons. The VN algorithm resamples PR and GR reflectivity and other 2-D and 3-D data fields to irregular common volumes defined by the geometric intersection of the instrument observations, and performs statistical comparisons of PR and GR reflectivity and estimated rain rates. Algorithmic biases and uncertainties introduced by traditional data analysis techniques are minimized by not performing interpolation or extrapolation of data to a fixed grid. The core VN dataset consists of WSR-88D GR data and matching PR orbit subset data covering 21 sites in the southeastern U. S., from August, 2006 to the present. On average, about 3.5 overpass events per month for these WSR-88D sites meet VN criteria for significant precipitation, and have matching PR and GR data available. This large statistical sample has allowed the relative calibration accuracy and stability of the individual ground radars, and the quality of the PR reflectivity attenuation correction in convective and stratiform precipitation to be evaluated. We will present results of PR-GR reflectivity and rain rate bias comparisons for each OR site, and for different rain types, for the full data set and as time series. The capabilities of the statistical analysis and vertical cross section tools for display and analysis of individual site overpass event data will be described, and examples of the tools' outputs will be shown.

Morris, Kenneth R.↗

Exploring Controls on the Fluvial Breaching of Degraded Impact Craters

Many lakes on early Mars were hosted in degraded impact craters. Past work has suggested that landscape erosion and crater degradation were very active prior to the valley network (VN)-forming era on Mars. Rim relief reduction during degradation may have primed craters for subsequent inlet incision during the VN-forming era. However, not all old, rimless craters on Mars are breached, so extensive rim degradation could not have been the only control on VN inlet formation. In this study, we ask: Why were some, but not all, degraded craters breached during the VN-forming era? Here, we focus on testing whether there are any measurable distinctions between VN-breached and non-breached degraded Noachian craters.

E R Bamber↗

Identification of Active Metal Carbide and Nitride Catalytic Facets for Hydrodeoxygenation Reactions

The catalytic hydrodeoxygenation (HDO) reaction is of considerable interest for biomass conversion to valuable chemicals and fuels, where one of the critical bottlenecks is the lack of cost-effective and efficient catalysts. To discover cost-efficient catalysts for the HDO reaction, we employed a density functional theory-based hierarchical catalyst design strategy based on catalytic descriptors, reaction energy profiles, and microkinetic modeling (MKM). We focused on the carbide and nitride catalyst space, for which we calculated 121 catalyst surfaces of Mo 2 C, MoC, Mo 2 N, W 2 C, NbC, VC, VN, and NbN catalysts. Based on the computed surface energies, reaction energies of oxygen removal, carbon binding strength, and the surface area of nanoparticles, the likely active facets are the Mo 2 C(111), MoC(011), VN(100), Mo 2 N(001), Mo 2 N(011), and Mo 2 N(100) surfaces. Further, detailed energy profiles were obtained, and MKM was performed for a model reaction (glycolaldehyde + 2H 2 . ethylene + 2H 2 O) on the Mo 2 C(111), VN(100), and MoC(100) surfaces. Based on the computed volcano map obtained from MKM, the predicted active facets for this HDO reaction are the Mo 2 C(111), MoC(011), VN(011), Mo 2 N(001), Mo 2 N(011), and Mo 2 N(100) surfaces. Additionally, none of the carbide and nitride catalyst surfaces are located in the optimal catalytic activity part. Therefore, it is essential to modify the catalyst via adding dopants or alloying to improve the catalytic activity. Catalytic modifications that can destabilize the surface adsorption of O*/H 2 O* and decrease the energy barriers of O-H bond formation are recommended to facilitate the HDO on the carbide and nitride catalysts. These a priori investigations provide guidelines for future low-cost HDO catalyst development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Performance of the NAS HSPs in 1st Half of 1994

During the first six months of 1994, the NAS (National Airspace System) 16-CPU Y-MP C90 Von Neumann (VN) delivered an average throughput of 4.045 GFLOPS while the ACSF (Aeronautics Consolidated Supercomputer Facility) 8-CPU Y-MP C90 Eagle averaged 1.658 GFLOPS. The VN rate represents a machine efficiency of 26.3% whereas the Eagle rate corresponds to a machine efficiency of 21.6%. VN displayed a greater efficiency than Eagle primarily because the stronger workload demand for its CPU cycles allowed it to devote more time to user programs and less time to idle. An additional factor increasing VN efficiency was the ability of the UNICOS 8.0 Operating System to deliver a larger fraction of CPU time to user programs. Although measurements indicate increasing vector length for both workloads, insufficient vector lengths continue to hinder HSP (High Speed Processor) performance. To improve HSP performance, NAS should continue to encourage the HSP users to modify their codes to increase program vector length.

Bergeron, Robert J.↗

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, Kenneth R.↗

Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

Morris, K. Robert↗

Fidelity and entanglement entropy for infinite-order phase transitions

Here, we study the fidelity and the entanglement entropy for the ground states of quantum systems that have infinite-order quantum phase transitions. In particular, we consider the quantum O(2) model with a spin-S truncation, where there is an infinite-order Gaussian (IOG) transition for S = 1 and there are Berezinskii-Kosterlitz-Thouless (BKT) transitions for S ≥ 2. We show that the height of the peak in the fidelity susceptibility (χ F ) converges to a finite thermodynamic value as a power law of 1 / L for the IOG transition and as 1 / ln (L) for BKT transitions. The peak position of χ F resides inside the gapped phase for both the IOG transition and BKT transitions. On the other hand, the derivative of the block entanglement entropy with respect to the coupling constant $S^{'}_{vN}$ has a peak height that diverges as ln 2 (L) for S = 1 and ln 3 (L) for S ≥ 2 and can be used to locate both kinds of transitions accurately. We include higher-order corrections for finite-size scalings and obtain the value of the central charge consistent with c = 1 predicted by conformal field theory. The crossing point of χ F between different system sizes is at the IOG point for S = 1 but is inside the gapped phase for S ≥ 2, while those of $S^{'}_{vN}$ are at the phase-transition points for all S truncations. Our work elaborates on how to use the finite-size scaling of χ F or $S^{'}_{vN}$ to detect infinite-order quantum phase transitions and discusses the efficiency and accuracy of the two methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Premotor neurons encode torsional eye velocity during smooth-pursuit eye movements

Responses to horizontal and vertical ocular pursuit and head and body rotation in multiple planes were recorded in eye movement-sensitive neurons in the rostral vestibular nuclei (VN) of two rhesus monkeys. When tested during pursuit through primary eye position, the majority of the cells preferred either horizontal or vertical target motion. During pursuit of targets that moved horizontally at different vertical eccentricities or vertically at different horizontal eccentricities, eye angular velocity has been shown to include a torsional component the amplitude of which is proportional to half the gaze angle ("half-angle rule" of Listing's law). Approximately half of the neurons, the majority of which were characterized as "vertical" during pursuit through primary position, exhibited significant changes in their response gain and/or phase as a function of gaze eccentricity during pursuit, as if they were also sensitive to torsional eye velocity. Multiple linear regression analysis revealed a significant contribution of torsional eye movement sensitivity to the responsiveness of the cells. These findings suggest that many VN neurons encode three-dimensional angular velocity, rather than the two-dimensional derivative of eye position, during smooth-pursuit eye movements. Although no clear clustering of pursuit preferred-direction vectors along the semicircular canal axes was observed, the sensitivity of VN neurons to torsional eye movements might reflect a preservation of similar premotor coding of visual and vestibular-driven slow eye movements for both lateral-eyed and foveate species.

Non-NASA Center↗