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Effects of Polymer Morphology on Solvent and Catalyst Accessibility during Polyethylene and Polystyrene Autoxidation

Efficient catalytic deconstruction of plastics requires facile solvent and catalyst access to polymer substrates to minimize mass transfer effects. Autoxidation using Co(II) acetate, Mn(II) acetate, and a radical carrier in acetic acid is a promising strategy to deconstruct mixed plastic waste, yet the role of polymer morphology in governing solvent and catalyst accessibility remains poorly understood. Here, in situ simultaneous small- and wide-angle X-ray scattering (SAXS/WAXS), complemented by X-ray fluorescence (XRF) imaging and high-pressure differential scanning calorimetry (DSC), were used to elucidate interactions between acetic acid, a Co/Mn catalyst solution, and semicrystalline polyethylene (PE) and amorphous polystyrene (PS) from room temperature to 160 °C. In PE, acetic acid and catalyst access were confined to amorphous regions and cryomilled particle interfaces at room temperature, while crystalline lamellae remained intact after soaking for up to 34 h. Increasing temperature enabled solvent uptake into PE, followed by solvent-assisted softening above 100 °C, and a modest melting-point depression that removed lamellar transport barriers upon melting. Conversely for PS, acetic acid penetrated the glassy polymer without inducing chain mobility until the glass transition was reached, above which the observed structural changes were consistent with enhanced segmental mobility which enabled bulk penetration. These results suggest that polymer morphology and thermally activated physical transitions arising from diffusion and polymer–solvent interactions can influence whether autoxidation of plastics is transport-limited or kinetically controlled, providing a framework for aligning reaction conditions with reaction outcomes.

09 BIOMASS FUELS↗

NASA Tech Briefs, May 2008

Topics covered inclde: Deployable Wireless Camera Penetrators; Hand-Held Units for Short-Range Wireless Biotelemetry; Wearable Wireless Telemetry System for Implantable BioMEMS Sensors; Electronic Escape Trails for Firefighters; Architecture for a High-to-Medium-Voltage Power Converter; 24-Way Radial Power Combiner/Divider for 31 to 36 GHz; Three-Stage InP Submillimeter-Wave MMIC Amplifier; Fast Electromechanical Switches Based on Carbon Nanotubes; Solid-State High-Temperature Power Cells; Fast Offset Laser Phase-Locking System; Fabricating High-Resolution X-Ray Collimators; Embossed Teflon AF Laminate Membrane Microfluidic Diaphragm Valves; Flipperons for Improved Aerodynamic Performance; System Estimates Radius of Curvature of a Segmented Mirror; Refractory Ceramic Foams for Novel Applications; Self-Deploying Trusses Containing Shape-Memory Polymers; Fuel-Cell Electrolytes Based on Organosilica Hybrid Proton Conductors; Molecules for Fluorescence Detection of Specific Chemicals; Cell-Detection Technique for Automated Patch Clamping; Redesigned Human Metabolic Simulator; Compact, Highly Stable Ion Atomic Clock; LiGa(OTf)(sub 4) as an Electrolyte Salt for Li-Ion Cells; Compact Dielectric-Rod White-Light Delay Lines; Single-Mode WGM Resonators Fabricated by Diamond Turning; Mitigating Photon Jitter in Optical PPM Communication; MACOS Version 3.31; Fiber-Optic Determination of N2, O2, and Fuel Vapor in the Ullage of Liquid-Fuel Tanks; Spiking Neurons for Analysis of Patterns; Symmetric Phase-Only Filtering in Particle-Image Velocimetry; Efficient Coupler for a Bessel Beam Dispersive Element; and Attitude and Translation Control of a Solar Sail Vehicle.

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NASA Tech Briefs, April 2005

Gas-Tolerant Device Senses Electrical Conductivity of Liquid Nanoactuators Based on Electrostatic Forces on Dielectrics Replaceable Microfluidic Cartridges for a PCR Biosensor CdZnTe Image Detectors for Hard-X-Ray Telescopes High-Aperture-Efficiency Horn Antenna Full-Circle Resolver-to-Linear-Analog Converter Continuous, Full-Circle Arctangent Circuit Advanced Three-Dimensional Display System Automatic Focus Adjustment of a Microscope Topics covered include: FastScript3D - A Companion to Java 3D; Generating Mosaics of Astronomical Images; Simulating Descent and Landing of a Spacecraft; Simulating Vibrations in a Complex Loaded Structure; Rover Sequencing and Visualization Program; Software Template for Instruction in Mathematics; Support for User Interfaces for Distributed Systems; Nanostructured MnO2-Based Cathodes for Li-Ion/Polymer Cells; Multi-Layer Laminated Thin Films for Inflatable Structures; Two-Step Laser Ranging for Precise Tracking of a Spacecraft; Growing Aligned Carbon Nanotubes for Interconnections in ICs; Multilayer Composite Pressure Vessels; Texturing Blood-Glucose-Monitoring Optics Using Oxygen Beams; Fault-Tolerant Heat Exchanger; Atomic Clock Based on Opto-Electronic Oscillator; Microfocus/Polycapillary-Optic Crystallographic X-Ray Sys; Depth-Penetrating Luminescence Thermography of Thermal- Barrier Coatings; One-Dimensional Photonic Crystal Superprisms; Measuring Low-Order Aberrations in a Segmented Telescope; Mapping From an Instrumented Glove to a Robot Hand; Application of the Hilbert-Huang Transform to Financial Data; Optimizing Parameters for Deep-Space Optical Communication; and Low-Shear Microencapsulation and Electrostatic Coating.

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Stochastic parametric skeletal dosimetry model for humans: Pediatric and adult computational skeleton phantoms for internal bone marrow dosimetry

Currently, computational phantoms that simulate skeletal tissues are used in active red bone marrow (AM) internal dosimetry. Up-to-date reference computational phantoms recommended by the ICRP are based on the analysis of CT-images of cadavers. Such phantoms have significant disadvantages. One disadvantage is that the assessment of uncertainty due to the population variability of skeleton dimensions and microstructure results from the limited availability of autopsy material. Another disadvantage is the simplified modelling of cortical layer and bone microarchitecture. A method of stochastic parametric skeletal dosimetry modelling of the bone structures – SPSD modelling – has been developed as an alternative to the ICRP reference phantoms. In the framework of this approach, skeletal phantom parameters are evaluated based on extensively reviewed results of published measurements of real bones. The SPSD approach allows for the assessment of both population-average values and their variability. SPSD-phantoms of the skeleton are modelled in voxel representation. They consist of smaller phantoms of the bone sites – segments – described by simple geometric shapes with uniform microarchitecture parameters. Such segmentation makes it possible to account for non-homogeneous skeletal microarchitecture and to model the bone structure with the required voxel resolution to elaborate suitable skeletal phantoms. The current study presents the parameters of the SPSD skeletal phantoms for the following age-groups: newborn, 1-year-old, 5-year-old, 10-year-old, 15-year-old (male and female), and adult (male and female). This skeletal phantom can be used for dosimetry as an alternative to available reference phantoms for bone-seeking radionuclides. The above-mentioned age- and sex-specific skeletal phantoms are comprised of 289 unique segments. The characteristics of the SPSD phantoms do not contradict published data and are in good agreement with the measurement results of real bones.

Science & Technology - Other Topics↗

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗

NASA Tech Briefs, May 2012

Topics covered include: An "Inefficient Fin" Non-Dimensional Parameter to Measure Gas Temperatures Efficiently; On-Wafer Measurement of a Multi-Stage MMIC Amplifier with 10 dB of Gain at 475 GHz; Software to Control and Monitor Gas Streams; Miniaturized Laser Heterodyne Radiometer (LHR) for Measurements of Greenhouse Gases in the Atmospheric Column; Anomaly Detection in Test Equipment via Sliding Mode Observers; Absolute Position of Targets Measured Through a Chamber Window Using Lidar Metrology Systems; Goldstone Solar System Radar Waveform Generator; Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System; Iridium Interfacial Stack - IrIS; Downsampling Photodetector Array with Windowing; Optical Phase Recovery and Locking in a PPM Laser Communication Link; High-Speed Edge-Detecting Line Scan Smart Camera; Optical Communications Channel Combiner; Development of Thermal Infrared Sensor to Supplement Operational Land Imager; Amplitude-Stabilized Oscillator for a Capacitance-Probe Electrometer; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse; Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH; LEGION: Lightweight Expandable Group of Independently Operating Nodes; Real-Time Projection to Verify Plan Success During Execution; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Web-Based Customizable Viewer for Mars Network Overflight Opportunities; Fabrication of a Cryogenic Terahertz Emitter for Bolometer Focal Plane Calibrations; Fabrication of an Absorber-Coupled MKID Detector; Graphene Transparent Conductive Electrodes for Next- Generation Microshutter Arrays; Method of Bonding Optical Elements with Near-Zero Displacement; Free-Mass and Interface Configurations of Hammering Mechanisms; Wavefront Compensation Segmented Mirror Sensing and Control; Long-Life, Lightweight, Multi-Roller Traction Drives for Planetary Vehicle Surface Exploration; Reliable Optical Pump Architecture for Highly Coherent Lasers Used in Space Metrology Applications; Electrochemical Ultracapacitors Using Graphitic Nanostacks; Improved Whole-Blood-Staining Device; Monitoring Location and Angular Orientation of a Pill; Molecular Technique to Reduce PCR Bias for Deeper Understanding of Microbial Diversity; Laser Ablation Electrodynamic Ion Funnel for In Situ Mass Spectrometry on Mars; High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle; PRTs and Their Bonding for Long-Duration, Extreme-Temperature Environments; Mid- and Long-IR Broadband Quantum Well Photodetector; 3D Display Using Conjugated Multiband Bandpass Filters; Real-Time, Non-Intrusive Detection of Liquid Nitrogen in Liquid Oxygen at High Pressure and High Flow; Method to Enhance the Operation of an Optical Inspection Instrument Using Spatial Light Modulators; Dual-Compartment Inflatable Suitlock; Large-Strain Transparent Magnetoactive Polymer Nanocomposites; Thermodynamic Vent System for an On-Orbit Cryogenic Reaction Control Engine; Time Distribution Using SpaceWire in the SCaN Testbed on ISS; and Techniques for Solution- Assisted Optical Contacting.

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Potential Large Decadal Missions Enabled by Nasas Space Launch System

Large space telescope missions have always been limited by their launch vehicle's mass and volume capacities. The Hubble Space Telescope (HST) was specifically designed to fit inside the Space Shuttle and the James Webb Space Telescope (JWST) is specifically designed to fit inside an Ariane 5. Astrophysicists desire even larger space telescopes. NASA's "Enduring Quests Daring Visions" report calls for an 8- to 16-m Large UV-Optical-IR (LUVOIR) Surveyor mission to enable ultra-high-contrast spectroscopy and coronagraphy. AURA's "From Cosmic Birth to Living Earth" report calls for a 12-m class High-Definition Space Telescope to pursue transformational scientific discoveries. NASA's "Planning for the 2020 Decadal Survey" calls for a Habitable Exoplanet Imaging (HabEx) and a LUVOIR as well as Far-IR and an X-Ray Surveyor missions. Packaging larger space telescopes into existing launch vehicles is a significant engineering complexity challenge that drives cost and risk. NASA's planned Space Launch System (SLS), with its 8 or 10-m diameter fairings and ability to deliver 35 to 45-mt of payload to Sun-Earth-Lagrange-2, mitigates this challenge by fundamentally changing the design paradigm for large space telescopes. This paper reviews the mass and volume capacities of the planned SLS, discusses potential implications of these capacities for designing large space telescope missions, and gives three specific mission concept implementation examples: a 4-m monolithic off-axis telescope, an 8-m monolithic on-axis telescope and a 12-m segmented on-axis telescope.

Technology↗

Production and Performance of the InFOCmicronS 20-40 keV Graded Multilayer Mirror

The International Focusing Optics Collaboration for micron Crab Sensitivity (InFOC micronS) balloon-borne hard x-ray incorporates graded multilayer technology to obtain significant effective area at energies previously inaccessible to x-ray optics. The telescope mirror consists of 2040 segmented thin aluminum foils coated with replicated Pt/C multilayers. A sample of these foils was scanned using a pencil-beam reflectometer to determine, multilayer quality. The results of the reflectometer measurements demonstrate our capability to produce large quantity of foils while maintaining high-quality multilayers with a mean Nevot-Croce interface roughness of 0.5nm. We characterize the performance of the complete InFOC micronS telescope with a pencil beam raster scan to determine the effective area and encircled energy function of the telescope. The effective area of the complete telescope is 78, 42 and 22 square centimeters at 20 30 and 40 keV. respectively. The measured encircled energy fraction of the mirror has a half-power diameter of 2.0 plus or minus 0.5 arcmin (90% confidence). The mirror successfully obtained an image of the accreting black hole Cygnus X-1 during a balloon flight in July, 2001. The successful completion and flight test of this telescope demonstrates that graded-multilayer telescopes can be manufactured with high reliability for future x-ray telescope missions such as Constellation-X.

Berendse, F.↗

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder

Real-time data collection and analysis in large experimental facilities present a great challenge across multiple domains, including high energy physics, nuclear physics, and cosmology. To address this, machine learning (ML)-based methods for real-time data compression have drawn significant attention. However, unlike natural image data, such as CIFAR and ImageNet that are relatively small-sized and continuous, scientific data often come in as three-dimensional 3D data volumes at high rates with high sparsity (many zeros) and non-Gaussian value distribution. This makes direct application of popular ML compression methods, as well as conventional data compression methods, suboptimal. To address these obstacles, this work introduces a dual-head autoencoder to resolve sparsity and regression simultaneously, called Bicephalous Convolutional AutoEncoder (BCAE). This method shows advantages both in compression fidelity and ratio compared to traditional data compression methods, such as MGARD, SZ, and ZFP. To achieve similar fidelity, the best performer among the traditional methods can reach only half the compression ratio of BCAE. Moreover, a thorough ablation study of the BCAE method shows that a dedicated segmentation decoder improves the reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Large area position sensitive detector for thermal neutrons

Large area thermal neutron detectors are applied in many fields including industrial imaging, nuclear safeguarding, neutron scattering, and fundamental science. Historically, these detectors were based on 3 He gas proportional counters despite the limitations of 3 He detectors such as high cost, limited supply, non-uniform spatial resolution, and depth of absorption problems. Two alternatives to 3 He detectors are 6 Li-loaded glass scintillators, and powdered ZnS(Ag) scintillators mixed with 6LiF neutron converters. The 6 LiF/ZnS(Ag) scintillator has advantages over 6 Li glass as it is less expensive and can be produced in larger areas, although its self-absorption presents a problem. In this work, we developed a large area thermal neutron detector based on 6 LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding. We further modified and improved the method by 2D segmentation of the detector using modular multichannel readout electronics. This segmentation approach allows for a combination of large detector area, improved spatial resolution, and increased count rate. Furthermore, spatial resolution can be variable across the detector area by adjusting the segment size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dimensionally Aligned Signal Projection Algorithms Library

Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. This work seeks to provide an effective open-source implementation of the DASP algorithms proposed by Vann et al. (2018) as well as functionality to help explore and test how these algorithms work with an interactive dashboard and signal-generation tool. The DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. The HASP algorithms are variations of the algorithms originally presented by Vann et al. (2018). For consistency, FASP, which is the terminology used for the short-time Fourier transform (STFT), has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals. Finally, the library provides multiple interactive visualizations, each of which is implemented using IPyWidgets and works in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as for the artifical signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.

harmonics↗

Visible Nulling Coronagraphy Testbed Development for Exoplanet Detection

Three of the recently completed NASA Astrophysics Strategic Mission Concept (ASMC) studies addressed the feasibility of using a Visible Nulling Coronagraph (VNC) as the prime instrument for exoplanet science. The VNC approach is one of the few approaches that works with filled, segmented and sparse or diluted aperture telescope systems and thus spans the space of potential ASMC exoplanet missions. NASA/Goddard Space Flight Center (GSFC) has a well-established effort to develop VNC technologies and has developed an incremental sequence of VNC testbeds to advance the this approach and the technologies associated with it. Herein we report on the continued development of the vacuum Visible Nulling Coronagraph testbed (VNT). The VNT is an ultra-stable vibration isolated testbed that operates under high bandwidth closed-loop control within a vacuum chamber. It will be used to achieve an incremental sequence of three visible light nulling milestones of sequentially higher contrasts of 10(exp 8) , 10(exp 9) and 10(exp 10) at an inner working angle of 2*lambda/D and ultimately culminate in spectrally broadband (>20%) high contrast imaging. Each of the milestones, one per year, is traceable to one or more of the ASMC studies. The VNT uses a modified Mach-Zehnder nulling interferometer, modified with a modified "W" configuration to accommodate a hex-packed MEMS based deformable mirror, a coherent fiber bundle and achromatic phase shifters. Discussed will be the optical configuration laboratory results, critical technologies and the null sensing and control approach.

Lyon, Richard G.↗

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗

Effectiveness of Deep Learning Trained on SynthCity Data for Urban Point-Cloud Classification

3D object recognition is one of the most popular areas of study in computer vision. Many of the more recent algorithms focus on indoor point clouds, classifying 3D geometric objects, and segmenting outdoor 3D scenes. One of the challenges of the classification pipeline is finding adequate and accurate training data. Hence, this article seeks to evaluate the accuracy of a synthetically generated data set called SynthCity, tested on two mobile laser-scan data sets. Varying levels of noise were applied to the training data to reflect varying levels of noise in different scanners. The chosen deep-learning algorithm was Kernel Point Convolution, a convolutional neural network that uses kernel points in Euclidean space for convolution weights.

Geology↗

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Environmental Sciences & Ecology↗

Detection of Storm Damage Tracks with EOS Data

The damage surveys conducted by the NWS in the aftermath of a reported tornadic event are used to document the location of the tornado ground damage track (pathlength and width) and an estimation of the tornado intensity. This study explores the possibility of using near-real-time medium and high spatial resolution satellite imagery from the NASA Earth Observing System satellites to provide additional information for the surveys. Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to study the damage tracks from three tornadic storms: the La Plata, Maryland, storm of 28 April 2002 and the Ellsinore and Marquand, Missouri, storms of 24 April 2002. These storms varied in intensity and occurred over regions with significantly different land cover. It was found that, depending on the nature of the land cover, tornado damage tracks from intense storms (F1 or greater) and hail storms may be evident in ASTER, Landsat, and MODIS satellite imagery. In areas where the land cover is dominated by forests, the scar patterns can show up very clearly, while in areas of grassland and regions with few trees, scar patterns are not as obvious or cannot be seen at all in the satellite imagery. The detection of previously unidentified segments of a damage track caused by the 24 April 2002 Marquand, Missouri, tornado demonstrates the utility of satellite imagery for damage surveys. However, the capability to detect tornado tracks in satellite imagery depends on the ability to observe the ground without obstruction from space and appears to be as much dependent on the nature of the underlying surface and land cover as on the severity of the tornadic storm.

Jedlovec, Gary J.↗