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At least 595 records · Page 33

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗

Characterization of Digital Silicon Photomultipliers

Digital Silicon photomultipliers (Digital SiPMs) have become an increasingly viable option for single-photon detection due to their compact size and precise timing and resolution. The following work characterizes the noise performance of a diSiPM designed and tested in-house at Fermilab. The SiPM consists of a 26x32 array of single-photon avalanche diode (SPAD) cells. Through the implementation of a shift register masking circuit, individual SPAD cells can be enabled and disabled at will, allowing for precise detection measurements of single columns (accumulator channels) and cells. The provided circuit design operates on voltage clock pulses and collects data on clock edges allowing for precise tuning of the data collection process by varying the clock frequency, pulse width, and integration period.

Shoemaker, Oliver [U. Chicago (main)]↗

Determination of Small Animal Long Bone Properties Using Densitometry

Assessment of bone structural property changes due to loading regimens or pharmacological treatment typically requires destructive mechanical testing and sectioning. Our group has accurately and non-destructively estimated three dimensional cross-sectional areal properties (principal moments of inertia, Imax and Imin, and principal angle, Theta) of human cadaver long bones from pixel-by-pixel analysis of three non-coplanar densitometry scans. Because the scanner beam width is on the order of typical small animal diapbyseal diameters, applying this technique to high-resolution scans of rat long bones necessitates additional processing to minimize errors induced by beam smearing, such as dependence on sample orientation and overestimation of Imax and Imin. We hypothesized that these errors are correctable by digital image processing of the raw scan data. In all cases, four scans, using only the low energy data (Hologic QDR-1000W, small animal mode), are averaged to increase image signal-to-noise ratio. Raw scans are additionally processed by interpolation, deconvolution by a filter derived from scanner beam characteristics, and masking using a variable threshold based on image dynamic range. To assess accuracy, we scanned an aluminum step phantom at 12 orientations over a range of 180 deg about the longitudinal axis, in 15 deg increments. The phantom dimensions (2.5, 3.1, 3.8 mm x 4.4 mm; Imin/Imax: 0.33-0.74) were comparable to the dimensions of a rat femur which was also scanned. Cross-sectional properties were determined at 0.25 mm increments along the length of the phantom and femur. The table shows average error (+/- SD) from theory of Imax, Imin, and Theta) over the 12 orientations, calculated from raw and fully processed phantom images, as well as standard deviations about the mean for the femur scans. Processing of phantom scans increased agreement with theory, indicating improved accuracy. Smaller standard deviations with processing indicate increased precision and repeatability. Standard deviations for the femur are consistent with those of the phantom. We conclude that in conjunction with digital image enhancement, densitometry scans are suitable for non-destructive determination of areal properties of small animal bones of comparable size to our phantom, allowing prediction of Imax and Imin within 2.5% and Theta within a fraction of a degree. This method represents a considerable extension of current methods of analyzing bone tissue distribution in small animal bones.

Breit, Gregory A.↗

Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

Tilton, James C.↗

Machine Vision based Sample-Tube Localization for Mars Sample Return

A potential Mars Sample Return (MSR) architecture is being jointly studied by NASA and ESA. As currently envisioned, the MSR campaign consists of a series of 3 missions: sample cache, fetch and return to Earth. In this paper, we focus on the fetch part of the MSR, and more specifically the problem of autonomously detecting and localizing sample tubes deposited on the Martian surface. Towards this end, we study two machine-vision based approaches: First, a geometrydriven approach based on template matching that uses hardcoded filters and a 3D shape model of the tube; and second, a data-driven approach based on convolutional neural networks (CNNs) and learned features. Furthermore, we present a large benchmark dataset of sample-tube images, collected in representative outdoor environments and annotated with ground truth segmentation masks and locations. The dataset was acquired systematically across different terrain, illumination conditions and dust-coverage; and benchmarking was performed to study the feasibility of each approach, their relative strengths and weaknesses, and robustness in the presence of adverse environmental conditions.

Detry, R.↗

20 kV Gallium Nitride pn Diode Electro-Magnetic Pulse Arrestor for Grid Reliability (Final Scientific/Technical Report)

This project developed vertical Gallium Nitride (GaN) pn diodes under two main thrusts: (1) A focus on relatively higher-voltage devices for use as fast EMP arrestors to protect the electric grid; and (2) A focus on a Foundry effort to establish the manufacturability of relatively lower voltage devices. For the first thrust, the aim was to develop devices that go into avalanche breakdown to clamp the voltage across sensitive grid equipment subject to voltage transients induced by electromagnetic pulses (EMPs). Devices with breakdown voltages exceeding 6.5 kV were achieved, and breakdown times shorter than 1 ns were demonstrated, which is sufficiently fast to protect against the fast component of an EMP-induced signal. Key challenges included the epitaxial growth of thick (50 µm or more), low-doped (low 10 15 cm -3 range) GaN layers comprising the drift regions of the diodes, as well as the design and fabrication of edge termination structures (step-etched junction termination extensions) to prevent premature breakdown. Midway through the project, an additional emphasis was put on large-area, high-current devices, and forward currents of approximately 400 A were achieved in composite devices towards the end of the project. Experimental and theoretical studies of impact ionization and avalanche ruggedness were also conducted. For the second thrust (the Foundry), the focus was primarily on 1.2-kV-class devices, although towards the end of the project outstanding results on 3.3-kV class devices were also achieved. The aim of the Foundry was to develop a high-yield, reliable, and economic vertical GaN pn diode process. The Foundry conducted characterization of incoming epitaxial material and correlated this information with the yield and performance of fully processed devices. Wafer maps of diode characteristics such as forward and reverse current as well as capacitance-voltage curves were measured using auto-probing. Several mask sets comprising different-area devices as well as multiple edge termination designs (implanted junction termination extensions, guard rings, and combinations thereof) were studied, and machine-learning-based approaches were utilized to analyze the data. Packaging and reliability efforts were also undertaken for the Foundry diodes, which are necessary for a viable commercial process.

20KV↗

20 kV Gallium Nitride pn Diode Electro-Magnetic Pulse Arrestor for Grid Reliability (Final Report)

This project developed vertical Gallium Nitride (GaN) pn diodes under two main thrusts: (1) A focus on relatively higher-voltage devices for use as fast EMP arrestors to protect the electric grid; and (2) A focus on a Foundry effort to establish the manufacturability of relatively lower-voltage devices. For the first thrust, the aim was to develop devices that go into avalanche breakdown to clamp the voltage across sensitive grid equipment subject to voltage transients induced by electromagnetic pulses (EMPs). Devices with breakdown voltages exceeding 6.5 kV were achieved, and breakdown times shorter than 1 ns were demonstrated, which is sufficiently fast to protect against the fast component of an EMP-induced signal. Key challenges included the epitaxial growth of thick (50 um or more), low-doped (low 10 15 cm -3 range) GaN layers comprising the drift regions of the diodes, as well as the design and fabrication of edge termination structures (step-etched junction termination extensions) to prevent premature breakdown. Midway through the project, an additional emphasis was put on large-area, high-current devices, and forward currents of approximately 400 A were achieved in composite devices towards the end of the project. Experimental and theoretical studies of impact ionization and avalanche ruggedness were also conducted. For the second thrust (the Foundry), the focus was primarily on 1.2-kV-class devices, although towards the end of the project outstanding results on 3.3-kV-class devices were also achieved. The aim of the Foundry was to develop a high-yield, reliable, and economic vertical GaN pn diode process. The Foundry conducted characterization of incoming epitaxial material and correlated this information with the yield and performance of fully processed devices. Wafer maps of diode characteristics such as forward and reverse current as well as capacitance-voltage curves were measured using auto-probing. Several mask sets comprising different-area devices as well as multiple edge termination designs (implanted junction termination extensions, guard rings, and combinations thereof) were studied, and machine-learning-based approaches were utilized to analyze the data. Packaging and reliability efforts were also undertaken for the Foundry diodes, which are necessary for a viable commercial process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Space Construction Experiment Definition Study (SCEDS), part 2. Volume 2: Study results

The Space Construction Experiment (SCE) was defined for integration into the Space Shuttle. This included development of flight assignment data, revision and update of preliminary mission timelines and test plans, analysis of flight safety issues, and definition of ground operations scenarios. New requirements for the flight experiment and changes for a large space antenna feed mask test article were incorporated. The program plan and cost estimates were updated. Revised SCE structural dynamics characteristics were provided for simulation and analysis of experimental tests to define and verify control limits and interactions effects between the SCE and the Orbiter digital automatic pilot.

Source record↗

Compositions of near-Earth asteroids

The goal is to determine whether any of the near-earth asteroids contain water-bearing phyllosilicate (clay) minerals. If these minerals are present, they would provide a readily available source of water for propellant generation and use in life support systems. Telescopic detection of water on the near-earth asteroids is complicated because thermal emission from the asteroid itself masks the diagnostic absorption features for objects this close to the sun. Sophisticated thermal models are necessary to determine whether the absorption features are present. This year, development of these models was continued and more telescopic data to test the models was obtained.

Lebofsky, L. A.↗

Spherical harmonic analysis of steady photospheric flows. II

The use of the spherical harmonic functions to analyze the nearly steady flows in the solar photosphere is extended to situations in which B(0) the latitude at disk center, is nonzero and spurious velocities are present. The procedures for extracting the rotation profile and meridional circulation are altered to account for the seasonal tilt of the sun's rotation axis toward and away from the observer. A more robust and accurate method for separating the limb shift and meridional circulation signals is described. The analysis procedures include the ability to mask out areas containing spurious velocities (velocity-like signals that do not represent true flow velocities in the photosphere). The procedures are shown to work well in extracting the various flow components from realistic artificial data with a broad, continuous spectrum for the supergranulation. The presence of this supergranulation signal introduces errors of a few m/s in the measurements of the rotation profile, meridional circulation, and limb shift from a single Doppler image.

Hathaway, David H.↗

MISR Level 2 TOA/Cloud Stereo parameters (MIL2TCST_V1)

The MISR Top-of-Atmosphere (TOA)/Cloud Stereo geophysical parameters include stereoscopically-derived cloud motion vectors (winds), cloud-top heights, and an accompanying cloud mask. The Stereo product geophysical parameters include a stereoscopically-derived cloud mask and cloud height on a 1.1 km grid. It also includes cloud motion vectors on a 70.4 km grid. The three types of stereo heights are: the BestWind heights are only calculated for those regions where the associated wind vectors passed the quality tests. Therefore, they have sparse coverage but since the wind correction is included, these contain our 'best guess' as to what the true heights are. The WithoutWind heights are calculated assuming a constant wind vector of zero. They have almost complete coverage and therefore form a nice 'pretty picture' of the relative cloud heights over small areas. The RawWind heights are a diagnostic product as they are calculated using all available wind vectors (even the bad ones). It is therefore recommended that one only use the Best and Without wind products. It is important to remember that the stereo matchers pick up the layer of maximum contrast, which is not necessarily the same as the highest cloud so all the stereo heights are keyed to this level of maximum contrast. Therefore, higher and thinner cirrus layers may not be detected by any of the height fields. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Horizontal_Resolution_Range=1 km - < 10 km or approximately .01 degree - < .09 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly].

EOSDIS↗

NASA Tech Briefs, December 2011

Topics covered include: 1) SNE Industrial Fieldbus Interface; 2) Composite Thermal Switch; 3) XMOS XC-2 Development Board for Mechanical Control and Data Collection; 4) Receiver Gain Modulation Circuit; 5) NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions; 6) Digital Interface Board to Control Phase and Amplitude of Four Channels; 7) CoNNeCT Baseband Processor Module; 8) Cryogenic 160-GHz MMIC Heterodyne Receiver Module; 9) Ka-Band, Multi-Gigabit-Per-Second Transceiver; 10) All-Solid-State 2.45-to-2.78-THz Source; 11) Onboard Interferometric SAR Processor for the Ka-Band Radar Interferometer (KaRIn); 12) Space Environments Testbed; 13) High-Performance 3D Articulated Robot Display; 14) Athena; 15) In Situ Surface Characterization; 16) Ndarts; 17) Cryo-Etched Black Silicon for Use as Optical Black; 18) Advanced CO2 Removal and Reduction System; 19) Correcting Thermal Deformations in an Active Composite Reflector; 20) Umbilical Deployment Device; 21) Space Mirror Alignment System; 22) Thermionic Power Cell To Harness Heat Energies for Geothermal Applications; 23) Graph Theory Roots of Spatial Operators for Kinematics and Dynamics; 24) Spacesuit Soft Upper Torso Sizing Systems; 25) Radiation Protection Using Single-Wall Carbon Nanotube Derivatives; 26) PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure; 27) Lidar Luminance Quantizer; 28) Distributed Capacitive Sensor for Sample Mass Measurement; 29) Base Flow Model Validation; 30) Minimum Landing Error Powered-Descent Guidance for Planetary Missions; 31) Framework for Integrating Science Data Processing Algorithms Into Process Control Systems; 32) Time Synchronization and Distribution Mechanisms for Space Networks; 33) Local Estimators for Spacecraft Formation Flying; 34) Software-Defined Radio for Space-to-Space Communications; 35) Reflective Occultation Mask for Evaluation of Occulter Designs for Planet Finding; and 36) Molecular Adsorber Coating

Source record↗

Antarctic Surface Temperatures Using Satellite Infrared Data from 1979 Through 1995

The large scale spatial and temporal variations of surface ice temperature over the Antarctic region are studied using infrared data derived from the Nimbus-7 Temperature Humidity Infrared Radiometer (THIR) from 1979 through 1985 and from the NOAA Advanced Very High Resolution Radiometer (AVHRR) from 1984 through 1995. Enhanced techniques suitable for the polar regions for cloud masking and atmospheric correction were used before converting radiances to surface temperatures. The observed spatial distribution of surface temperature is highly correlated with surface ice sheet topography and agrees well with ice station temperatures with 2K to 4K standard deviations. The average surface ice temperature over the entire continent fluctuates by about 30K from summer to winter while that over the Antarctic Plateau varies by about 45K. Interannual fluctuations of the coldest interannual variations in surface temperature are highest at the Antarctic Plateau and the ice shelves (e.g., Ross and Ronne) with a periodic cycle of about 5 years and standard deviations of about 11K and 9K, respectively. Despite large temporal variability, however, especially in some regions, a regression analysis that includes removal of the seasonal cycle shows no apparent trend in temperature during the period 1979 through 1995.

Comiso, Josefino C.↗

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗

Adaptive methods of generating complex light arrays

Structured light arrays of various shapes have been a cornerstone in optical science, driven by the complexities of precise and adaptable generation. This study introduces an approach using a spatial light modulator (SLM) as a generator for these arrays. By projecting a holographic mask onto the SLM, it functions simultaneously as an optical convolution device, focusing mechanism, and structured light beam mask. Our approach offers unmatched versatility, allowing for the experimental fabrication of traditional beam arrays like azimuthal Laguerre–Gaussian (LG), Bessel–Gaussian (BG), and Hermite–Gauss (HG) in the far-field. Notably, it has enabled a method of generating Ince–Gauss (IG) and LG radial mode beam arrays using a convolution solution. Our system provides exceptional control over array periodicity and intensity distribution, bypassing the Talbot self-imaging phenomenon seen in traditional setups. We provide an in-depth theoretical discussion, supported by empirical evidence, of our far-field results. This method has vast potential for applications in optical communication, data processing, and multi-particle manipulation. It paves the way for rapid generation of structured light with high spatial frequencies and complex shapes, promising transformative advances in these domains.

Optics↗

Water4Energy Tier-1 Raw Observations for TVA Seasonal Prediction, Version 1

Tier-1 (Step-1) raw observation staging collection for the Water4Energy Genesis Task-1 project on weeks-to-years prediction of Tennessee Valley temperature and precipitation. This data-only deposit includes CPC/PSL teleconnection indices, NOAA OISST monthly and ERSST sea-surface temperature, ERA5-derived daily 1° fields (t2m, tp, msl for 1980–2024), CFSv2 NMME ensemble-mean seasonal baselines, and a TVA boundary mask. The product supports seasonal teleconnection diagnostics and construction of AI ready-to-train packs published separately. Multi-terabyte hourly archives are excluded from this version.

54 ENVIRONMENTAL SCIENCES↗

Real-time X-ray phase-contrast imaging using SPINNet—a speckle-based phase-contrast imaging neural network

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.

36 MATERIALS SCIENCE↗