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At least 739 records · Page 41

Aliovalent Doping of CeO 2 Improves the Stability of Atomically Dispersed Pt

Atomically dispersed supported catalysts hold considerable promise as catalytic materials. The ability to employ and stabilize them against aggregation in complex process environments remains a key challenge to the elusive goal of 100% atom utilization in catalysis. In this work, using a Gd-doped ceria support for atomically dispersed surface Pt atoms, we establish how the combined effects of aliovalent doping and oxygen vacancy generation provide dynamic mechanisms that serve to enhance the stability of supported single atom configurations. Using correlated, in situ X-ray absorption, photoelectron and vibrational spectroscopies for analysis of the samples on the two types of support (with and without Gd doping), we establish that the Pt atoms locate proximal to Gd dopants, forming a speciation that serves to enhance the thermal stability of Pt atoms against aggregation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

Abstract Land surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance.

54 ENVIRONMENTAL SCIENCES↗

Autonomous x-ray scattering

Autonomous experimentation (AE) is an emerging paradigm that seeks to automate the entire workflow of an experiment, including—crucially—the decision-making step. Beyond mere automation and efficiency, AE aims to liberate scientists to tackle more challenging and complex problems. We describe our recent progress in the application of this concept at synchrotron x-ray scattering beamlines. We automate the measurement instrument, data analysis, and decision-making, and couple them into an autonomous loop. We exploit Gaussian process modeling to compute a surrogate model and associated uncertainty for the experimental problem, and define an objective function exploiting these. We provide example applications of AE to x-ray scattering, including imaging of samples, exploration of physical spaces through combinatorial methods, and coupling to in situ processing platforms These uses demonstrate how autonomous x-ray scattering can enhance efficiency, and discover new materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Petrography of lunar soil 15601

Lunar soil 15601 has been studied petrographically using grain size analysis, modal analysis, and electron probe microanalysis of monomineralic fragments in the 90-150-micron size fraction. The soil is immature; the grain size distribution is unimodal and very symmetrical, indicating that the soil is a homogeneous product of a single set of processes. It is concluded that 15601 is mostly a simple Apollo 15 mare basalt soil, and its properties can be used to approximate an end product of the array of complex soils that the lunar sample missions have returned.

Basu, A.↗

SETI Pulse Detection Algorithm: Analysis of False-alarm Rates

Some earlier work by the Search for Extraterrestrial Intelligence (SETI) Science Working Group (SWG) on the derivation of spectrum analyzer thresholds for a pulse detection algorithm based on an analysis of false alarm rates is extended. The algorithm previously analyzed was intended to detect a finite sequence of i periodically spaced pulses that did not necessarily occupy the entire observation interval. This algorithm would recognize the presence of such a signal only if all i-received pulse powers exceeded a threshold T(i): these thresholds were selected to achieve a desired false alarm rate, independent of i. To simplify the analysis, it was assumed that the pulses were synchronous with the spectrum sample times. This analysis extends the earlier effort to include infinite and/or asynchronous pulse trains. Furthermore, to decrease the possibility of missing an extraterrestrial intelligence signal, the algorithm was modified to detect a pulse train even if some of the received pulse powers fall below the threshold. The analysis employs geometrical arguments that make it conceptually easy to incorporate boundary conditions imposed on the derivation of the false alarm rates. While the exact results can be somewhat complex, simple closed form approximations are derived that produce a negligible loss of accuracy.

Levitt, B. K.↗

Evidence of Microfossils in Carbonaceous Chondrites

Investigations have been carried out on freshly broken, internal surfaces of the Murchison, Efremovka and Orgueil carbonaceous chondrites using Scanning Electron Microscopes (SEM) in Russia and the Environmental Scanning Electron Microscope (ESEM) in the United States. These independent studies on different samples of the meteorites have resulted in the detection of numerous spherical and ellipsoidal bodies (some with spikes) similar to the forms of uncertain biogenicity that were designated "organized elements" by prior researchers. We have also encountered numerous complex biomorphic microstructures in these carbonaceous chondrites. Many of these complex bodies exhibit diverse characteristics reminiscent of microfossils of cyanobacteria such as we have investigated in ancient phosphorites and high carbon rocks (e.g. oil shales). Energy Dispersive Spectroscopy (EDS) analysis and 2D elemental maps shows enhanced carbon content in the bodies superimposed upon the elemental distributions characteristic of the chondritic matrix. The size, distribution, composition, and indications of cell walls, reproductive and life cycle developmental stages of these bodies are strongly suggestive of biology' These bodies appear to be mineralized and embedded within the meteorite matrix, and can not be attributed to recent surface contamination effects. Consequently, we have interpreted these in-situ microstructures to represent the lithified remains of prokaryotes and filamentous cyanobacteria. We also detected in Orgueil microstructures morphologically similar to fibrous kerite crystals. We present images of many biomorphic microstructures and possible microfossils found in the Murchison, Efremovka, and Orgueil chondrites and compare these forms with known microfossils from the Cambrian phosphate-rich rocks (phosphorites) of Khubsugul, Northern Mongolia.

Hoover, Richard B.↗

Efficacy of FTIR Analysis in Determining CO2 Loading on Diglycolamine

In support of advanced air revitalization technologies to enable human spaceflight beyond low earth orbit, performance studies have been conducted using a liquid amine, Diglycolamine (DGA) between teams at NASA's Johnson Spaceflight Center (JSC) and Ames Research Center (ARC). Liquid amines have been used in regenerable earth-based systems to remove CO2 from industrial systems as well as for closed-environment air revitalization because they can be regenerated at lower temperatures than solid sorbent systems. As an additional advantage to solid sorbent-based systems, liquid sorbents can be cycled between an adsorbing contactor and degassing chamber, thereby reducing system complexity by operation in a continuous loop. In an effort to inform a regeneration system design for micro-gravity applications, ARC has performed a number of tests to characterize the degas mechanics of DGA. In order to accurately measure the amount of CO2 captured or released by the amine, methods such as gravimetric weighing and chemical desorption are reasonable, however the first iteration test setup for a scaled down degas system required analysis on small sample sizes. Fourier-transform infrared spectroscopy (FTIR) analysis was experimentally evaluated to analyze CO2 concentration because it can produce measurements with sample sizes on the order of 100's of μL. Calibration against chemical desorption showed relatively good correlation and test data showed reasonable adherence to expected trends, however more extensive testing should be conducted to fully validate the usage of FTIR to determine CO2 loading on DGA.

Diglycolamine↗

Pyrolysis Vacuum-Assisted Plasma Ionization Ion Mobility–Mass Spectrometry for Insoluble Polymer Analysis

Wire-based metal additive manufacturing utilizes the ability of additive manufacturing to fabricate complex geometries with high deposition rates (above 7 kg/h), thus finding applications in the fabrication of large-scale components, such as stamping dies. Traditionally, the workhorse materials for stamping dies have been martensitic steels. However, the complex thermal gyrations induced during additive manufacturing can cause the evolution of an inhomogeneous microstructure, which leads to a significant scatter in the mechanical properties, especially the toughness. Therefore, to understand these phenomena, arc-based additive AISI 410 samples were fabricated using robotic gas metal arc welding (GMAW) and were subjected to a detailed characterization campaign. The results show significant scatter in the tensile properties as well as Charpy V-notch impact toughness data, which was then correlated to the microstructural heterogeneity and delta (δ) ferrite formation. Post-processing (austenitizing and tempering) treatments were developed and an ~70% reduction in the scatter of tensile data and a four-times improvement in the toughness were obtained. The changes in mechanical properties were rationalized based on the microstructure evolution during additive manufacturing. Based on these, an outline to tailor the composition of “printable” steels for tooling with isotropic and uniform mechanical properties is presented and discussed.

36 MATERIALS SCIENCE↗

Interpreting mixing relationships in energetic melts to estimate vapor contribution and composition

Heterogeneous, glassy debris can be produced by energetic events such as near surface nuclear explosions and asteroid impacts. In these events, the resultant debris comprises a rapidly-cooled mixture of the projectile or bomb material with proximate materials such as soil and anthropogenic structures. Glasses formed in these events preserve inter and/or intra sample compositional variation reflecting complex mixtures of the precursor materials or their chemically fractionated products. Understanding formation mechanisms and chemical processes relating to energetic glass formation based on study of the end products requires an objective method for calculating the precursor components that mixed together to produce the final product. Here, we compare a set of multivariate linear-least squares approaches to address the unmixing problem of heterogeneous glasses including classical least squares (CLS), principal component analysis (PCA) and two multivariate curve resolution – alternating least squares (MCR-ALS) approaches. We generate a synthetic data set representing spatially resolved, compositional data in a set of heterogeneously mixed glasses to understand model sensitivity to precursor abundance and composition. We explore the impact of incomplete knowledge of the system prior to the formation of the melts on the resulting confidence and accuracy of the solution (i.e., the number, composition, and abundances of the precursor materials). We conclude that a closure and equality constrained MCR-ALS approach succeeds in identifying unrecognized precursor components and is a suitable alternative to CLS approaches when the investigator has incomplete knowledge of the starting precursor chemical compositions. Finally, we demonstrate application of this MCR-ALS approach to measurements of Trinitite.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

Probabilistic Life and Reliability Analysis of Model Gas Turbine Disk

In 1939, W. Weibull developed what is now commonly known as the "Weibull Distribution Function" primarily to determine the cumulative strength distribution of small sample sizes of elemental fracture specimens. In 1947, G. Lundberg and A. Palmgren, using the Weibull Distribution Function developed a probabilistic lifing protocol for ball and roller bearings. In 1987, E. V. Zaretsky using the Weibull Distribution Function modified the Lundberg and Palmgren approach to life prediction. His method incorporates the results of coupon fatigue testing to compute the life of elemental stress volumes of a complex machine element to predict system life and reliability. This paper examines the Zaretsky method to determine the probabilistic life and reliability of a model gas turbine disk using experimental data from coupon specimens. The predicted results are compared to experimental disk endurance data.

Holland, Frederic A.↗

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment.

Source record↗

Reduced-order Modeling for Spacecraft Thermal-structural Applications

Leveraging the speed of reduced-order models (ROMs), thermal analysis teams have previously had access to rapid optimization, sensitivity studies, rapid model correlation, and uncertainty quantification, to name a few. An advantage of the developed approach is its relative robustness, which enabled expansion to include structural models in addition to thermal models leading to both rapid thermal-structural and rapid structural-only analyses. This method was tested for a sample thermal-structural application and showed good performance. It was then applied to a complex NASA mission and showed how ROMs could be used to quickly evaluate system uncertainties. Finally, these methods were applied to a structural-only application and used to better optimize and understand the structural design.

Derek Hengeveld↗

Regolith and Environment Science and Oxygen and Lunar Volatile Extraction (RESOLVE): Lunar Advanced Volatile Analysis (LAVA) Capillary Fluid Dynamic Restriction Effects on Gas Chromatography

The Resource Prospector (RP) mission with the Regolith and Environment Science and Oxygen Lunar Volatile Extraction (RESOLVE) payload aims to show the presence of water in lunar regolith, and establish a proving ground for NASAs mission to Mars. One of the analysis is performed by the Lunar Advanced Volatiles Analysis (LAVA) subsystem, which consists of a fluid network that facilitates the transport of volatile samples to a gas chromatograph and mass spectrometer (GC-MS) instrument. The understanding of fluid dynamics directed from the GC to the MS is important due to the influence of flow rates and pressures that affect the accuracy of and prevent the damage to the overall GC-MS instrument. The micro-scale capillary fluid network within the GC alone has various lengths and inner-diameters; therefore, determination of pressure differentials and flow rates are difficult to model computationally, with additional complexity from the vacuum conditions in space and lack of a lunar atmosphere. A series of tests were performed on an experimental set-up of the system where the inner diameters of the GC transfer line connecting to the MS were varied. The effect on chromatography readings were also studied by applying these lines onto a GC instrument. It was found that a smaller inner diameter transfer line resulted in a lower flow rate, as well as a lower pressure differential across the thermal conductivity detector (TCD) unit of the GC and a negligible pressure drop across the mock-up capillary column. The chromatography was affected with longer retention times and broader peak integrations. It was concluded that a 0.050 mm inner diameter line still proved most suitable for the systems flow rate preferences. In addition, it was evident that this small transfer line portrayed some expense to GC signal characteristics and the wait time for steady-state operation.

RESOLVE↗

Probing multiscale dissolution dynamics in natural rocks through microfluidics and compositional analysis

Mineral dissolution significantly impacts many geological systems. Carbon released by diagenesis, carbon sequestration, and acid injection are examples where geochemical reactions, fluid flow, and solute transport are strongly coupled. The complexity in these systems involves interplay between various mechanisms that operate at timescales ranging from microseconds to years. Current experimental techniques characterize dissolution processes using static images that are acquired with long measurement times and/or low spatial resolution. These limitations prevent direct observation of how dissolution reactions progress within an intact rock with spatially heterogeneous mineralogy and morphology. We utilize microfluidic cells embedded with thin rock samples to visualize dissolution with significant temporal resolution (100 ms) in a large observation window (3 × 3 mm). Here we injected acidic fluid into eight shale samples ranging from 8 to 86 wt % carbonate. The pre- and postreaction microstructures are characterized at the scale of pores (0.1 to 1 µm) and fractures (1 to 1,000 µm). We observe that nonreactive particle exposure, fracture morphology, and loss of rock strength are strongly dependent on both the relative volume of reactive grains and their distribution. Time-resolved images of the rock unveil the spatiotemporal dynamics of dissolution, including two-phase flow effects in real time and illustrate the changes in the fracture interface across the range of compositions. Moreover, the dynamical data provide an approach for characterizing reactivity parameters of natural heterogeneous samples when porous media effects are not negligible. The platform and workflow provide real-time characterization of geochemical reactions and inform various subsurface engineering processes.

58 GEOSCIENCES↗

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Sensitivity in Targeted Single-Cell Proteomics by Coupling a Dual Ion Funnel Interface with Triple Quadrupole Mass Spectrometer

Single-cell proteomics (SCP) has emerged as a powerful approach for understanding cellular heterogeneity and biological processes at unprecedented resolution. However, the extremely limited protein content of individual cells (femtogram to picogram levels) pushes current mass spectrometry instrumentation to its sensitivity limits, creating a critical analytical bottleneck. While selected reaction monitoring (SRM) using triple quadrupole (QqQ) instruments 1 offers advantages in sensitivity and reproducibility for targeted proteomics quantification, SRM still struggles with sensitivity for quantification of moderate- or low-abundance proteins from single-cell sample amounts. Here, we report the development and systematic evaluation of a dual ion funnel interface designed to address the sensitivity limitation by significantly enhancing ion transmission efficiency in commercial QqQ mass spectrometers. The dual ion funnel interface, composed of a curved S-funnel followed by a conventional ion funnel, improves ion transmission efficiency while reducing chemical noise through selective ion focusing. The performance of the dual ion funnel interface was systematically compared to standard interface on a TSQ Vantage platform across samples with different levels of complexity. The dual funnel interface demonstrated to provide up to 25-fold improvement in sensitivity across a wide range of protein concentrations in different biological matrices (low complex mouse macrophage and high complex human cells). Critically, enhanced sensitivity was accompanied by increased analytical reproducibility with lower coefficient of variations. Most importantly, the dual funnel interface enabled reliable quantification of low-abundance proteins that were barely detectable or not detected by the standard interface, extending analysis to single-cell equivalent amounts while maintaining excellent reproducibility. These results demonstrate that the dual funnel interface addresses the critical bottleneck in quantitative targeted proteomics, providing a technological foundation for ultrasensitive targeted SCP that requires both high sensitivity and robust quantitative performance.

Min, Sehong↗

Evaluating Brightness and Stability of Cathodoluminescence from Colloidal Semiconductor Nanocrystals

Cathodoluminescence offers promise as a technique for correlation of atomic structure with electronic structure at the level of individual nanoparticles or even defects, with the ability to analyze complex nanostructures at length-scales far below those typically available to optical spectroscopy. Unlike other forms of electron microscopy, cathodoluminescence offers direct insights into the electronic structure of the visualized sample. Despite reports more than 10 years ago of individual nanoparticle cathodoluminescence, effective cathodoluminescence collection from colloidal semiconductor materials is relatively rare and remains challenging due to the instability of materials under the conditions of electron beam irradiation. In this work, to clarify the roadblocks for cathodoluminescence analysis of colloidal nanocrystals, we attempt a comprehensive study of the cathodoluminescence properties of semiconductor quantum shells, which have a thin concentric CdSe shell surrounding CdS nanoparticles, then surrounded by a further concentric CdS shell. These same materials were recently demonstrated to show promising scintillation performance in radioluminescence measurements, including high brightness (up to 100 ph/keV) and excellent durability. Comparative quantum yield measurements are designed to assess the brightness of semiconductor nanocrystal films, which show that the quantum shells are much less bright under electron irradiation compared to X-ray photons. Instability of CL emission is assigned to charging effects on the samples—and not thermal effects—through a series of voltage, current, dwell time, and atmospheric pressure experiments.

cathodoluminescence↗