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NASA NTRS2024

The Radio Fundamental Catalogue. I. Astrometry

We present the all-sky catalogue of absolute positions and estimates of correlated flux density of 21,942 compact radio sources determined from processing interferometric visibility data of virtually all VLBI observing sessions at 2 to 23~GHz from 72 programs suitable for absolute astrometry collected for 30 years. We used a novel technique of generation of a dataset of fused observables that allowed us to incorporate all available data in our analysis. The catalogue is the most complete and most precise to date. It forms the foundation and reference for positional astronomy, space geodesy, space navigation, population analysis of active galactic nuclei (AGNs), and provides calibrators for phase-referencing for differential astrometry and VLBI astrophysical observations. Its accuracy was evaluated through a detailed accounting systematic errors, rigorous decimation tests, comparison of different datasets, and comparison with other catalogues. The catalogue samples preferentially the AGNs with a strong contemporary parsec-scale synchrotron emission. Its milliarcsecond level positional accuracy allows association of these AGNs with detections in a wide range of the electromagnetic spectrum from low-frequency radio to gamma-rays and high energy neutrinos. We describe the innovative data processing and calibration technique in full detail, report the in depth analysis of random and systematic positional errors, and provide the list of associations with large surveys at different wavelengths.

Astronomy↗

NASA NTRSDate not supplied

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗

NASA NTRS2000

Hierarchical Statistical 3D ' Atomistic' Simulation of Decanano MOSFETs: Drift-Diffusion, Hydrodynamic and Quantum Mechanical Approaches

When MOSFETs are scaled to deep submicron dimensions the discreteness and randomness of the dopant charges in the channel region introduces significant fluctuations in the device characteristics. This effect, predicted 20 year ago, has been confirmed experimentally and in simulation studies. The impact of the fluctuations on the functionality, yield, and reliability of the corresponding systems shifts the paradigm of the numerical device simulation. It becomes insufficient to simulate only one device representing one macroscopical design in a continuous charge approximation. An ensemble of macroscopically identical but microscopically different devices has to be characterized by simulation of statistically significant samples. The aims of the numerical simulations shift from predicting the characteristics of a single device with continuous doping towards estimating the mean values and the standard deviations of basic design parameters such as threshold voltage, subthreshold slope, transconductance, drive current, etc. for the whole ensemble of 'atomistically' different devices in the system. It has to be pointed out that even the mean values obtained from 'atomistic' simulations are not identical to the values obtained from continuous doping simulations. In this paper we present a hierarchical approach to the 'atomistic' simulation of aggressively scaled decanano MOSFETs. A full scale 3D drift-diffusion'atomostic' simulation approach is first described and used for verification of the more economical, but also more restricted, options. To reduce the processor time and memory requirements at high drain voltage we have developed a self-consistent option based on a thin slab solution of the current continuity equation only in the channel region. This is coupled to the Poisson's equation solution in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison with the full self-consistent solution. At low drain voltage only single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. A pilot version of a hydrodynamic 'atomistic' simulator has been developed in order to study the effect of the nonequilibrium, non local transport in decanano MOSFETs on the random dopant induced current fluctuations. For the first time we have also applied the density gradient approach in 3D to investigate the effect of the quantum confinement on the threshold voltage fluctuations. The developed 'atomistic' simulation techniques have been applied to study various fluctuation resistant MOSFET architectures including epitaxial and delta doped devices.

Asenov, Asen↗

NASA NTRS1990

Thermal advection and stratification effects on surface winds and the low level meridional mass transport

Statistical tests are performed on the Seasat scatterometer observations to examine if and to what degree thermal advection and stratification effects manifest themselves in these remotely sensed measurements of mean wind and wind stress over the ocean. On the basis of a two layer baroclinic boundary layer model which is presented, it is shown that the thermal advection and stratification of the entire boundary layer as well as the geostrophic forcing influence the modeled near surface wind and wind stress profiles. Evidence of diurnal variation in the stratification under barotropic conditions is found in the data, with the daytime marine boundary layer being more convective than its nighttime counterpart. The temporal and spacial sampling pattern of the satellite makes it impossible to recover the full diurnal cycle, however. The observed effects of the thermal advection are shown to be statistically significant during the day (and presumed more convective) hours, causing a systematic increase in the poleward transport of mass and heat. The statistical results are in a qualitative agreement with the model simulations and cannot be reproduced in randomized control tests.

Levy, Gad↗

NASA NTRS2009

M-BAND Study of Radiation-Induced Chromosome Aberrations in Human Epithelial Cells: Radiation Quality and Dose Rate Effects

The advantage of the multicolor banding in situ hybridization (mBAND) technique is its ability to identify both inter- (translocation to unpainted chromosomes) and intra- (inversions and deletions within a single painted chromosome) chromosome aberrations simultaneously. To study the detailed rearrangement of low- and high-LET radiation induced chromosome aberrations in human epithelial cells (CH184B5F5/M10) in vitro, we performed a series of experiments with Cs-137 gamma rays of both low and high dose rates, neutrons of low dose rate and 600 MeV/u Fe ions of high dose rate, with chromosome 3 painted with multi-binding colors. We also compared the chromosome aberrations in both 2- and 3-dimensional cell cultures. Results of these experiments revealed the highest chromosome aberration frequencies after low dose rate neutron exposures. However, detailed analysis of the radiation induced inversions revealed that all three radiation types induced a low incidence of simple inversions. Most of the inversions in gamma-ray irradiated samples were accompanied by other types of intra-chromosomal aberrations but few inversions were accompanied by inter-chromosomal aberrations. In contrast, neutrons and Fe ions induced a significant fraction of inversions that involved complex rearrangements of both inter- and intrachromosomal exchanges. The location of the breaks involved in chromosome exchanges was analyzed along the painted chromosome. The breakpoint distribution was found to be randomly localized on chromosome 3 after neutron or Fe ion exposure, whereas non-random distribution with clustering breakpoints was observed after -ray exposure. Our comparison of chromosome aberration yields between 2- and 3-dimensional cell cultures indicated a significant difference for gamma exposures, but not for Fe ion exposures. These experimental results indicated that the track structure of the radiation and the cellular/chromosome structure can both affect radiation-induced chromosome aberrations.

Hada, Megumi↗

NASA NTRS2007

Detectors for the James Webb Space Telescope Near-Infrared Spectrograph I: Readout Mode, Noise Model, and Calibration Considerations

We describe how the James Webb Space Telescope (JWST) Near-Infrared Spectrograph's (NIRSpec's) detectors will be read out, and present a model of how noise scales with the number of multiple non-destructive reads sampling-up-the-ramp. We believe that this noise model, which is validated using real and simulated test data, is applicable to most astronomical near-infrared instruments. We describe some non-ideal behaviors that have been observed in engineering grade NIRSpec detectors, and demonstrate that they are unlikely to affect NIRSpec sensitivity, operations, or calibration. These include a HAWAII-2RG reset anomaly and random telegraph noise (RTN). Using real test data, we show that the reset anomaly is: (1) very nearly noiseless and (2) can be easily calibrated out. Likewise, we show that RTN affects only a small and fixed population of pixels. It can therefore be tracked using standard pixel operability maps.

Rauscher, Bernard J.↗

NASA NTRS2013

The Radial Distribution of Star Formation in Galaxies at Z approximately 1 from the 3D-HST Survey

The assembly of galaxies can be described by the distribution of their star formation as a function of cosmic time. Thanks to the WFC3 grism on the Hubble Space Telescope (HST) it is now possible to measure this beyond the local Universe. Here we present the spatial distribution of H emission for a sample of 54 strongly star-forming galaxies at z 1 in the 3D-HST Treasury survey. By stacking the H emission, we find that star formation occurred in approximately exponential distributions at z approximately 1, with a median Sersic index of n = 1.0 +/- 0.2. The stacks are elongated with median axis ratios of b/a = 0.58 +/- 0.09 in H consistent with (possibly thick) disks at random orientation angles. Keck spectra obtained for a subset of eight of the galaxies show clear evidence for rotation, with inclination corrected velocities of 90.330 km s(exp 1-). The most straightforward interpretation of our results is that star formation in strongly star-forming galaxies at z approximately 1 generally occurred in disks. The disks appear to be scaled-up versions of nearby spiral galaxies: they have EW(H alpha) at approximately 100 A out to the solar orbit and they have star formation surface densities above the threshold for driving galactic scale winds.

Nelson, Erica June↗

NASA NTRS1987

Micro and macro approaches to tough polymers for composites

The progress to date on the development of techniques to toughen continuous thermoplastic composites is summarized. The work, using the approach of toughening the polycarbonate composite matrix with rubber particles, has focused on determining the differences between Double Cantilever Beam (DCB) samples molded inhouse and those molded by NASA. Specifically, an effort was made to account for the differences in fracture toughness observed between the various specimens. In addition, preliminary results of tensile dilatometry tests are described; these tests suggest that processes leading to increased volume and enhanced shear banding are occurring within the rubber toughened system. The results of the effort using another approach, the preparation of random block copolycarbonates, are presented. The synthetic route to these species was modified so that higher molecular weights of these materials can be obtained. In addition, an attempt is being made to determine the exact block length or the number of functional groups in the oligomers since this procedure also should lead to high molecular weight materials. Dynamic mechanical analysis of the copolymer prepared so far indicates that the scale of cooperative molecular motion of the PBA polycarbonate at sub-Tg temperatures is larger than five monomer units. Efforts to find a suitable rubber-toughener for a thermoset system (bismaleimides) is also discussed. Included is a description of the various tougheners intended for use or currently being used.

Yee, Albert F.↗

NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗

NASA NTRS1999

Random Dopant Induced Threshold Voltage Lowering and Fluctuations in Sub 50 nm MOSFETs: a Statistical 3D 'Atomistic' Simulation Study

A 3D 'atomistic' simulation study of random dopant induced threshold voltage fluctuations and lowering in sub 50 nm MOSFETs is presented. The attention is focused mainly on devices with 30 nm effective channel length which represent the expected level of scaling at the end of the Silicon Roadmap. An efficient algorithm, based on a single 3D ap solution of the Poisson equation and a simplified current continuity equation, is used in the simulations. Large samples of microscopically different devices (typically 200) arc used in order to obtain statistically reliable results. The influence of different aspects of the conventional MOSFET design on the threshold voltage fluctuations and lowering are investigated. Results for fluctuation resistant device architectures based on low-doped epitaxial channel MOSFETs are also presented.

Asenov, Asen↗

NASA NTRSDate not supplied

Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization

Recent Large Language Models (LLMs) have demonstrated impressive capabilities at tasks that require human intelligence and are a significant step towards human-like artificial intelligence (AI). Yet the performance of LLMs at reasoning tasks have been subpar and the reasoning capability of LLMs is a matter of significant debate. While it has been shown that the choice of the prompting technique to the LLM can alter its performance on a multitude of tasks, including reasoning, the best performing techniques require human-made prompts with the knowledge of the tasks at hand. We introduce a framework for what we call Combinatorial Reasoning (CR), a fully-automated prompting method, where reasons are sampled from an LLM pipeline and mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem. The framework investigates whether QUBO solutions can be profitably used to select a useful subset of the reasons to construct a Chain-of-Thought style prompt. We explore the acceleration of CR with specialized solvers. We also investigate the performance of simpler zero-shot strategies such as linear majority rule or random selection of reasons. Our preliminary study indicates that coupling a combinatorial solver to generative AI pipelines is an interesting avenue for AI reasoning and elucidates design principles for future CR methods.

combinatorial reasoning↗

NASA NTRS1979

Industrial ion source technology

In reactive ion etching of Si, varying amounts of O2 were added to the CF4 background. The experimental results indicated an etch rate less than that for Ar up to an O2 partial pressure of about .00006 Torr. Above this O2 pressure, the etch rate with CF4 exceeded that with Ar alone. For comparison the random arrival rate of O2 was approximately equal to the ion arrival rate at a partial pressure of about .00002 Torr. There were also ion source and ion pressure gauge maintenance problems as a result of the use of CF4. Large scale (4 sq cm) texturing of Si was accomplished using both Cu and stainless steel seed. The most effective seeding method for this texturing was to surround the sample with large inclined planes. Designing, fabricating, and testing a 200 sq cm rectangular beam ion source was emphasized. The design current density was 6 mA/sq cm with 500 eV argon ions, although power supply limitations permitted operation to only 2 mA/sq cm. The use of multiple rectangular beam ion sources for continuous processing of wider areas than would be possible with a single source was also studied. In all cases investigated, the most uniform coverage was obtained with 0 to 2 cm beam overlay. The maximum departure from uniform processing at optimum beam overlap was found to be +15%.

Kaufman, H. R.↗

NASA NTRS1985

Processing of laser formed SiC powder

Superior SiC characteristics can be achieved through the use of ideal constituent powders and careful post-synthesis processing steps. High purity SiC powders of approx. 1000 A uniform diameter, nonagglomerated and spherical were produced. This required major revision of the particle formation and growth model from one based on classical nucleation and growth to one based on collision and coalescence of Si particles followed by their carburization. Dispersions based on pure organic solvents as well as steric stabilization were investigated. Although stable dispersions were formed by both, subsequent part fabrication emphasized the pure solvents since fewer problems with drying and residuals of the high purity particles were anticipated. Test parts were made by the colloidal pressing technique; both liquid filtration and consolidation (rearrangement) stages were modeled. Green densities corresponding to a random close packed structure (approx. 63%) were achieved; this highly perfect structure has a high, uniform coordination number (greater than 11) approaching the quality of an ordered structure without introducing domain boundary effects. After drying, parts were densified at temperatures ranging from 1800 to 2100 C. Optimum densification temperatures will probably be in the 1900 to 2000 C range based on these preliminary results which showed that 2050 C samples had experienced substantial grain growth. Although overfired, the 2050 C samples exhibited excellent mechanical properties. Biaxial tensile strengths up to 714 MPa and Vickers hardness values of 2430 kg/sq mm 2 were both more typical of hot pressed than sintered SiC. Both result from the absence of large defects and the confinement of residual porosity (less than 2.5%) to small diameter, uniformly distributed pores.

Haggerty, J. S.↗

NASA NTRSDate not supplied

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗

NASA NTRS2021

Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.

random forest↗

NASA NTRS1993

The effect of tidal fields on the shapes and kinematics of dark halos

We have carried out a series of N-body simulations to investigate the effect of tidal shear on the structure and kinematics of dark halos. We simulate the collapse of density perturbations using a tree code as described in Dubinski & Carlberg (1991). Density peaks are selected from a random realization of a CDM density field and used as the initial conditions for N-body simulations. We use an experimental approach to examine the effects of tidal shear on collapse. The cosmological tidal field is treated as an external time dependent potential whose strength and orientation can be varied freely. We examine the effects of the tidal field with two experiments. In the first experiment, we simulate a sample of 14 dark halos from the collapse of density peaks in the presence of a 1(sigma) tidal field. In the second experiment, we use the same initial conditions though the tidal field is turned off allowing an experimental control for comparison to highlight the influence of tidal shear on the development of the structure and kinematics of the dark halos.

Dubinski, John↗

NASA NTRS2010

Miniature Low-Mass Drill Actuated by Flextensional Piezo Stack

Recent experiments with a flextensional piezoelectric actuator have led to the development of a sampler with a bit that is designed to produce and capture a full set of sample forms including volatiles, powdered cuttings, and core fragments. The flextensional piezoelectric actuator is a part of a series of devices used to amplify the generated strain from piezoelectric actuators. Other examples include stacks, bimorphs, benders, and cantilevers. These devices combine geometric and resonance amplifications to produce large stroke at high power density. The operation of this sampler/drill was demonstrated using a 3x2x1-cm actuator weighing 12 g using power of about 10-W and a preload of about 10 N. A limestone block was drilled to a depth of about 1 cm in five minutes to produce powdered cuttings. It is generally hard to collect volatiles from random surface profiles found in rocks and sediment, powdered cuttings, and core fragments. Toward the end of collecting volatiles, the actuator and the bit are covered with bellows-shaped shrouds to prevent fines and other debris from reaching the analyzer. A tube with a miniature bellows (to provide flexibility) is connected to the bit and directs the flow of the volatiles to the analyzer. Another modality was conceived where the hose is connected to the bellows wall directly to allow the capture of volatiles generated both inside and outside the bit. A wide variety of commercial bellows used in the vacuum and microwave industries can be used to design the volatiles capture mechanism. The piezoelectric drilling mechanism can potentially be operated in a broad temperature range from about-200 to less than 450 C. The actuators used here are similar to the actuators that are currently baselined to fly as part of the inlet funnel shaking mechanism design of MSL (Mars Science Laboratory). The space qualification of these parts gives this drill a higher potential for inclusion in a future mission, especially when considering its characteristics of low mass, small size, low power, and low axial loads for sampling.

Sherrit, Stewart↗

NASA NTRS1980

The NASA/MSFC global reference atmospheric model: MOD 3 (with spherical harmonic wind model)

Improvements to the global reference atmospheric model are described. The basic model includes monthly mean values of pressure, density, temperature, and geostrophic winds, as well as quasi-biennial and small and large scale random perturbations. A spherical harmonic wind model for the 25 to 90 km height range is included. Below 25 km and above 90 km, the GRAM program uses the geostrophic wind equations and pressure data to compute the mean wind. In the altitudes where the geostrophic wind relations are used, an interpolation scheme is employed for estimating winds at low latitudes where the geostrophic wind relations being to mesh down. Several sample wind profiles are given, as computed by the spherical harmonic model. User and programmer manuals are presented.

Justus, C. G.↗