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At least 109 records · Page 6

Deciphering the local structure of Prussian blue analogue cathodes with Raman spectroscopy for sodium-ion batteries

Iron-based Prussian blue analogues (PBAs) have gained attention as low-cost, relatively higher-potential cathodes for sodium-ion batteries, due to their open 3D-framework structures. However, understanding the local structural changes is critical to unveiling the intercalation pathways and degradation mechanisms. We employ here operando Raman spectroscopy to probe the changes in the cyanide vibrational modes during cycling and degradation after cycling, which are not adequately resolved by X-ray diffraction due to the low structure factor and limited X-ray sensitivity of the cyanide groups. Vibrational spectroscopy has thus proven essential for deciphering these complex materials. Additionally, we implement pre-sodiation strategies to assess the impact of sodium inventory loss by pairing PBAs with a hard carbon anode in a full-cell configuration. Operando galvanostatic electrochemical impedance spectroscopy (EIS) and ex situ X-ray photoelectron spectroscopy (XPS) further elucidate the interface evolution and the role of water molecules in forming the cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI). The insights gained advance the understanding of PBAs and enhance their practical viability.

25 ENERGY STORAGE↗

Software and Human-Machine Interface Development for Environmental Controls Subsystem Support

The Space Launch System (SLS) is the next premier launch vehicle for NASA. It is the next stage of manned space exploration from American soil, and will be the platform in which we push further beyond Earth orbit. In preparation of the SLS maiden voyage on Exploration Mission 1 (EM-1), the existing ground support architecture at Kennedy Space Center required significant overhaul and updating. A comprehensive upgrade of controls systems was necessary, including programmable logic controller software, as well as Launch Control Center (LCC) firing room and local launch pad displays for technician use. Environmental control acts as an integral component in these systems, being the foremost system for conditioning the pad and extremely sensitive launch vehicle until T-0. The Environmental Controls Subsystem (ECS) required testing and modification to meet the requirements of the designed system, as well as the human factors requirements of NASA software for Validation and Verification (V&V). This term saw significant strides in the progress and functionality of the human-machine interfaces used at the launch pad, and improved integration with the controller code.

Dobson, Matthew↗

Correlating Protein Dynamics and Catalytic Activity of a Model Hydrogenase Using Paramagnetic and Biological Nuclear Magnetic Resonance Spectroscopy

Rational catalyst design remains a significant challenge, with electronic structure, steric, and electrostatic effects known to contribute to activity. Recently, dynamics has been recognized as another factor that impacts catalysis, though identifying and predicting these effects has remained out of reach. Nickel-substituted rubredoxin (NiRd), a protein-based mimic of a hydrogenase enzyme, serves as a model catalytic system in which dynamics can be systematically investigated with respect to activity. While over 30 secondary-sphere mutants of NiRd have been shown to be catalytically active, no significant correlation was observed between the rates and catalytic overpotential or electronic structure, prompting questions about the protein-derived factors that modulate activity. Here, in this work, NMR spectroscopy was used to investigate the roles of substrate accessibility, protein dynamics, and protein stability in controlling catalysis. Significant paramagnetic effects from the nickel center (S = 1) isolate the methylene proton resonances of the metal-coordinating cysteine residues. The sensitivity of resonance positions and linewidths to local environment offers an opportunity to study dynamical molecular changes around the metal center with high resolution. Machine learning algorithms were employed to identify correlations between the catalytic activity and the paramagnetic NMR spectra. These analyses revealed spectroscopic features of specific cysteine protons that report on catalytic overpotential and increased turnover rates, which are further supported by the results obtained using high-field NMR techniques. Collectively, these studies indicate the potential for multifrequency NMR techniques to resolve key contributors to catalytic activity and highlight the importance of local and outer-sphere dynamics.

Protein Engineering↗

Impact of Halogen Groups on the Properties of PEA–Based 2D Pb–Sn Halide Perovskites

Tuning broad emission in 2D Pb–Sn halide perovskites (HPs) is essential for advancing optoelectronic applications, particularly for color-tunable and white-light-emitting devices. This broad emission is linked to structural factors, such as defects and phase segregation of the Pb component within the Pb–Sn system, which are strongly influenced by the molecular structure and chemical properties of spacer cations. Atomic tuning of the spacers via halogenation opens up a new way to fine-tune the molecular properties, enabling further augmentations of HP functionalities. Nevertheless, the distinct broad emission's sensitivity to spacer chemistry remains underexplored. Here, halogenation's influence is systematically investigated on 2D HP emission characteristics using a high-throughput workflow. These findings reveal that the F-containing phenethylammonium (4F-PEA) spacer narrows the broadband PL, whereas Cl broadens it. Through a correlative study, it is found that 4F-PEA reduces not only the local phase segregation but also the defect levels and microstrains in 2D HPs. This is likely attributed to the manifestation of less lattice distortion via stronger surface coordination of the dipole-augmented 4F-PEA. Furthermore, these results highlight halogenation as a key factor in modulating phase segregation and defect density in 2D Pb–Sn HPs, offering a promising pathway to tune the emission for enhanced optoelectronic performance.

2D Pb-Sn halide perovskites↗

Ferroelectricity in hafnia controlled via surface electrochemical state

Ferroelectricity in binary oxides including hafnia and zirconia has riveted the attention of the scientific community due to the highly unconventional physical mechanisms and the potential for the integration of these materials into semiconductor workflows. Over the last decade, it has been argued that behaviours such as wake-up phenomena and an extreme sensitivity to electrode and processing conditions suggest that ferroelectricity in these materials is strongly influenced by other factors, including electrochemical boundary conditions and strain. Here we argue that the properties of these materials emerge due to the interplay between the bulk competition between ferroelectric and structural instabilities, similar to that in classical antiferroelectrics, coupled with non-local screening mediated by the finite density of states at surfaces and internal interfaces. Via the decoupling of electrochemical and electrostatic controls, realized via environmental and ultra-high vacuum piezoresponse force microscopy, we show that these materials demonstrate a rich spectrum of ferroic behaviours including partial-pressure-induced and temperature-induced transitions between ferroelectric and antiferroelectric behaviours. In conclusion, these behaviours are consistent with an antiferroionic model and suggest strategies for hafnia-based device optimization.

36 MATERIALS SCIENCE↗

Magnetic field sensors for detection of trapped flux in superconducting radio frequency cavities

Superconducting radio-frequency (SRF) cavities are fundamental building block of modern particle accelerators. They operate at liquid helium temperatures 2-4 K to achieve very high quality factors 1e10-1e11. Trapping of magnetic flux within the superconductor is a significant contribution to the residual RF losses which limit the achievable quality factor. Suitable diagnostic tools are in high demand to understand the mechanisms of flux trapping in technical superconductors and the fundamental components of such diagnostic tool are magnetic field sensors. We have studied the performance of commercially available Hall probes, anisotropic magnetoresistive sensors and flux-gate magnetometers with respect to their sensitivity and capability to detect localized, low magnetic flux amplitudes, of the order of few tens of magnetic flux quantum at liquid helium temperature. Although Hall probes have the lowest magnetic field sensitivity (~96$ nV$/microT at 2 K), their physical dimensions are such that they have the ability to detect the lowest number of trapped vortices among the three type of sensors. Hall probes and anisotropic magnetoresistive sensors have been selected to be used in a setup to map regions of trapped flux on the surface of a single-cell SRF cavity.

47 OTHER INSTRUMENTATION↗

Effects of negative triangularity on microinstabilities in a low-recycling lithium-wall spherical tokamak

In this work, we present a linear gyrokinetic study of the impact of negative triangularity (NT) on microinstabilities in the Lithium Tokamak eXperiment-β (LTX-β), a low-recycling spherical tokamak with liquid lithium plasma-facing components that produce flat electron-temperature profiles [Elliott et al., IEEE Trans. Plasma Sci. 48, 1382 (2020)]. While NT is widely recognized as a stabilizing mechanism and often associated with improved confinement in conventional tokamaks, this study reveals that its effect is not universally stabilizing in the parameter regime of LTX-β and is shown to be highly sensitive to local equilibria. Using local linear simulations with the GS2 code [Kotschenreuther et al., Comput. Phys. Commun. 88, 128 (1995)] at ρ=0.3, 0.5, and 0.8 for two representative discharges (#103955 and #109355), and employing the Miller equilibrium model to isolate shaping effects, we find that NT can transition from stabilizing to destabilizing depending on magnetic shear, safety factor, and electron-temperature gradient. In shot #103955, NT reduces growth rates across radii, with strongest stabilization at the edge, whereas in shot #109355, it is stabilizing in the core but destabilizing at mid-radius and edge under experimental conditions. Parametric scans show that flattening the electron-temperature profile, increasing magnetic shear, and reducing the safety factor recover NT stabilization. These results demonstrate that NT stabilization is tunable rather than intrinsic and requires coordinated control of magnetic geometry and gradient drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Adjoint Techniques for Topology Optimization of Structures Under Damage Conditions

The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation (Haftka and Gurdal, 1992) in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers (Akgun et al., 1998a and 1999). It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages (Haftka et al., 1983). A common method for topology optimization is that of compliance minimization (Bendsoe, 1995) which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local and represents a small change in the stiffness matrix compared to the baseline (undamaged) structure. The exact solution to a slightly modified set of equations can be obtained from the baseline solution economically without actually solving the modified system.. Shennan-Morrison-Woodbury (SMW) formulas are matrix update formulas that allow this (Akgun et al., 1998b). SMW formulas were therefore used here to compute adjoint displacements for sensitivity computation and structural displacements in damaged configurations.

Akgun, Mehmet A.↗

Factors governing the ratio of inward to outward diffusing flux of satellite ions

The sensitivity of the flux ratio to the uncertainties in the boundary conditions and diffusion coefficient is analyzed. The principal result is that if the diffusion is driven externally, for example, by winds in Jupiter's ionosphere, the inward flux exceeds or is of the same order of magnitude as the outward flux. On the other hand, if the diffusion is driven locally by the centrifugal interchange instability, as suggested by one interpretation of Voyager plasma data, the outward flux can be one or two orders of magnitude greater than the inward flux. Fits to the Voyager in situ plasma torus data obtained through solutions to the transport equations appropriate to wind driven and centrifugally driven diffusion are compared.

Richardson, J. D.↗

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗

Experimental determination of Mercury's mass and oblateness

The ratio of the mass of the sun to that of Mercury deduced from the first and third flybys of Mercury by Mariner 10 is 6,023,600 plus or minus 600 and 6,023,700 plus or minus 300, respectively. Additional analysis should improve these uncertainties by a factor of 2 to 5. Assuming an equatorial radius of 2439 km, the mean density of the planet is 5.44 g/cu cm. The gravitational oblateness deduced from the first encounter is discussed. Data received from the third encounter are better suited for this determination and yield J2 of 0.00008 plus or minus 0.00006. In addition, the third-encounter data are sensitive to local gravity effects or anomalies.

Esposito, P. B.↗

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

Space Based Ornithology: On the Wings of Migration and Biophysics

The study of bird migration on a global scale is one of the compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties. Space based technology offers new opportunities to shed understanding on the distribution and migration of organisms on the planet and their sensitivity to human disturbances and environmental changes. Migration is an incredibly diverse and complex behavior. A broad outline of space based research must address three fundamental questions: (1) where could birds be, i.e. what is their fundamental niche constrained by their biophysical limits? (2) where do we actually find birds, i.e. what is their realizable niche as modified by local or regional abiotic and biotic factors, and (3) how do they get there (and how do we know?), that is what are their migration patterns and associated mechanisms? Our working hypothesis is that individual organism biophysical models of energy and water balance, driven by satellite measurements of spatio-temporal gradients in climate and habitat, will help us to explain the variability in avian species richness and distribution. Dynamic state variable modeling provides one tool for studying bird migration across multiple scales and can be linked to mechanistic models describing the time and energy budget states of migrating birds. Such models yield an understanding of how a migratory flyway and its component habitats function as a whole and link stop-over ecology with biological conservation and management. Further these models provide an ecological forecasting tool for science and application users to address what are the possible consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration.

Smith, James A.↗

ORIGIN: Metal Creation and Evolution from the Cosmic Dawn

ORIGIN is a proposal for the M3 mission call of ESA aimed at the study of metal creation from the epoch of cosmic dawn. Using high-spectral resolution in the soft X-ray band, ORIGIN will be able to identify the physical conditions of all abundant elements between C and Ni to red-shifts of z=10, and beyond. The mission will answer questions such as: When were the first metals created? How does the cosmic metal content evolve? Where do most of the metals reside in the Universe? What is the role of metals in structure formation and evolution? To reach out to the early Universe ORIGIN will use Gamma-Ray Bursts (GRBs) to study their local environments in their host galaxies. This requires the capability to slew the satellite in less than a minute to the GRB location. By studying the chemical composition and properties of clusters of galaxies we can extend the range of exploration to lower redshifts (z approx. 0.2). For this task we need a high-resolution spectral imaging instrument with a large field of view. Using the same instrument, we can also study the so far only partially detected baryons in the Warm-Hot Intergalactic Medium (WHIM). The less dense part of the WHIM will be studied using absorption lines at low redshift in the spectra for GRBs. The ORIGIN mission includes a Transient Event Detector (coded mask with a sensitivity of 0.4 photon/sq cm/s in 10 s in the 5-150 keV band) to identify and localize 2000 GRBs over a five year mission, of which approx.65 GRBs have a redshift >7. The Cryogenic Imaging Spectrometer, with a spectral resolution of 2.5 eV, a field of view of 30 arcmin and large effective area below 1 keV has the sensitivity to study clusters up to a significant fraction of the virial radius and to map the denser parts of the WHIM (factor 30 higher than achievable with current instruments). The payload is complemented by a Burst InfraRed Telescope to enable onboard red-shift determination of GRBs (hence securing proper follow up of high-z bursts) and also probes the mildly ionized state of the gas. Fast repointing is achieved by a dedicated Controlled Momentum Gyro and a low background is achieved by the selected low Earth orbit.

Kouveliotou, C.↗

Environment-sensitivity functions for gross primary productivity in light use efficiency models

The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO 2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full factorial light use efficiency (LUE) model structure, leading to a collection of 5600 distinct LUE models. Each model was optimized against daily GPP and evapotranspiration fluxes from 196 FLUXNET sites and ranked across sites based on a bootstrap approach. The GPP sensitivity to each environmental factor, including CO 2 fertilization, was shown to be significant, and that none of the previously published model structures performed as well as the best model selected. From daily and weekly to monthly scales, the best model's median Nash-Sutcliffe model efficiency across sites was 0.73, 0.79 and 0.82, respectively, but poorer at annual scales (0.23), emphasizing the common limitation of current models in describing the interannual variability of GPP. Although the best global model did not match the local best model at each site, the selection was robust across ecosystem types. The contribution of light saturation and cloudiness to GPP was observed across all biomes (from 23% to 43%). Temperature and W dominates GPP and LUE but responses of GPP to temperature and W are lagged in cold and arid ecosystems, respectively. The findings of this study provide a foundation towards more robust LUE-based estimates of global GPP and may provide a benchmark for other empirical GPP products.

54 ENVIRONMENTAL SCIENCES↗

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗

Ada software productivity prototypes: A case study

A case study of the impact of Ada on a Command and Control project completed at the Jet Propulsion Laboratory (JPL) is given. The data for this study was collected as part of a general survey of software costs and productivity at JPL and other NASA sites. The task analyzed is a successful example of the use of rapid prototyping as applied to command and control for the U.S. Air Force and provides the U.S. Air Force Military Airlift Command with the ability to track aircraft, air crews and payloads worldwide. The task consists of a replicated database at several globally distributed sites. The local databases at each site can be updated within seconds after changes are entered at any one site. The system must be able to handle up to 400,000 activities per day. There are currently seven sites, each with a local area network of computers and a variety of user displays; the local area networks are tied together into a single wide area network. Using data obtained for eight modules, totaling approximately 500,000 source lines of code, researchers analyze the differences in productivities between subtasks. Factors considered are percentage of Ada used in coding, years of programmer experience, and the use of Ada tools and modern programming practices. The principle findings are the following. Productivity is very sensitive to programmer experience. The use of Ada software tools and the use of modern programming practices are important; without such use Ada is just a large complex language which can cause productivity to decrease. The impact of Ada on development effort phases is consistent with earlier reports at the project level but not at the module level.

Hihn, Jairus M.↗

Magnetic Penetration Effects in Small Superconducting Devices

The temperature dependent behavior of a superconducting body in an applied magnetic field involves flux penetration/expulsion both from screening currents (within a magnetic penetration depth) and variations in the superconducting order parameter (locally to form vortices or a mixed state, or globally in the Meissner effect). The temperature dependence of the magnetic penetration depth, in particular, has been used to make highly sensitive macroscopic thermometers. For the microscopic device volumes required in sensitive low temperature photon detectors, properties of actual thin film materials, non-uniformity of applied magnetic fields, and the influence of measurement circuit dynamics are complicating factors. We discuss the various penetration effects as demonstrated in a particularly promising combination of material and geometry that we have used to make sensitive x-ray microcalorimeters.

Stevenson, T. R.↗