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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies

Tropical leaf phenology-particularly its variability at the tree-crown scale-dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red-green-blue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. Here, we first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Effect of threshold parameters on infrared segmentation methods for porosity detection in electron beam powder bed fusion

In-situ process monitoring has seen significant interest in additive manufacturing to address qualification and certification goals. This is especially prevalent in metal powder bed fusion processes such as electron beam powder bed fusion (PBF-EB), with layer-wise infrared imaging being commonly used to detect defects. Here, this work compares two different segmentation methods (static thresholding and statistical thresholding) used for detecting porosity from in-situ infrared imaging data for PBF-EB. Samples were manufactured at a variety of focus offset values to induce porosity. Then, the segmented infrared images were compared to ex-situ X-ray computed tomography scans, which served as a ground-truth reference for objective evaluation. Through this analysis framework, the influential parameters, static threshold and N-value (number of standard deviations above the mean pixel value), respectively, for both image segmentation methods were analyzed and compared for their effects on porosity detection. With optimal parameter settings, the two methods had similar porosity detection performance, but the statistical method performed better under a larger variety of parameter settings.

Infrared imaging↗
DOE OSTI2022

Simple through-plane spatial filter for 2D MRI projections

A simple spatial filter for 2D projection MR imaging is introduced. It works in the third (unresolved) direction to eliminate uniform or slowly varying interfering background signals. A constant amplitude gradient pulse in the unresolved direction is applied at the same time as the usual phase encode gradient during 2D acquisition. The filter is demonstrated for root imaging in soil, where background soil water signals can be troublesome. The filter suppresses the soil water signal while preserving the desired signal of plant roots. Fundamental to the operation of the filter is that the roots are sparse in the image domain, meaning there are relatively few pixels with multiple roots present. Here, the performance of the through-plane filter is demonstrated and compares favorably to more conventional in-plane spatial filtering.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Montage electron tomography of vitrified specimens

Cryo-electron tomography provides detailed views of macromolecules in situ. However, imaging a large field of view to provide more cellular context requires reducing magnification during data collection, which in turn restricts the resolution. To circumvent this trade-off between field of view and resolution, we have developed a montage data collection scheme that uniformly distributes the dose throughout the specimen. In this approach, sets of slightly overlapping circular tiles are collected at high magnification and stitched to form a composite projection image at each tilt angle. These montage tilt-series are then reconstructed into massive tomograms with a small pixel size but a large field of view. For proof-of-principle, we applied this method to the thin edge of HeLa cells. Thon rings to better than 10 Å were detected in the montaged tilt-series, and diverse cellular features were observed in the resulting tomograms. These results indicate that the additional dose required by this technique is not prohibitive to performing structural analysis to intermediate resolution across a large field of view. We anticipate that montage tomography will prove particularly useful for lamellae, increase the likelihood of imaging rare cellular events, and facilitate visual proteomics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗
DOE OSTI2026

The incommensurate modulation of tetragonal tungsten bronze quantified by high resolution 4D STEM

Many members of the tetragonal tungsten bronze (TTB) family of oxides display an incommensurate periodic lattice distortion, the nature of which has been the subject of some controversy. Here we present a study of this structural modulation in the relaxor ferroelectric Ba 5 SmSn 3 Nb 7 O 30 (BSSN) by quantitative scanning transmission electron microscopy (STEM). Additionally, we characterize the modulation in BSSN by employing a fast, pixelated direct electron detector to perform high resolution phase contrast STEM imaging of the crystalline lattice. By quantitatively analyzing the images, we visualize the atomic structural correlations present in the material on both the cation and anion sublattices. This analysis reveals the incommensurate structure to have an octahedral tilting pattern and cooperative A2 site cation displacements, analogous to an Ama2 commensurate cell. Finally, we show that the modulation is composed of a structural motif with a period of 3 x $d_{1\bar{1}0}$ and modified by discommensurations, likely arise from frustrated octahedral tilting in the odd-valued periodicity.

Differential phase contrast↗
DOE OSTI2021

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
DOE OSTI2020

Study of CMOS strip sensor for future silicon tracker

Monolithic silicon sensors developed with High-Voltage CMOS (HV-CMOS) processes have become highly attractive for charged particle tracking. Compared with the standard CMOS sensors, HV-CMOS sensors can provide larger and deeper depletion regions that lead to larger signals and faster charge collection. They can provide high position resolution, low material budget, high radiation hardness and low cost that are desirable for high performance tracking in harsh collision environment. Various studies have been conducted to explore the technology feasibility for the large-area tracking systems at future collider experiments. CHESS (CMOS HV/HR Evaluation for Strip Sensor) sensor series have been developed as an alternative solution to the conventional silicon micro-strip detectors for the ATLAS inner tracker upgrade. The first prototype (named CHESS1) was to evaluate the diode geometry and the in-pixel analog electronics. Obtained test results were used to optimize the second prototype (named CHESS2). CHESS2 was implemented with a full digital readout architecture and realized as a full reticle sized monolithic sensor. Here, the basic characteristics of the CHESS2 prototype sensors and their performance in response to different input signals are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Measurements of D–D fusion neutrons generated in nanowire array laser plasma using Timepix3 detector

Here, we present results of the neutron detection in laser plasma experiment with CD2 nanowire target. A hybrid semiconductor pixel detector Timepix3 covered with neutron converters was using for the detection neutrons. D-D fusion neutrons were detected in a plastic converter through recoiled protons. Both the energy of recoiled protons and time-of-flight of neutrons (and thus their energy) were determined. We report (2.4±1.8) × 10 7 neutrons generated for 1 J of incoming laser energy. Furthermore, we proved that Timepix3 is suitable for difficult operational conditions in laser experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

First 3D vector tracking of helium recoils for fast neutron measurements at Super$\mathrm{KEKB}$

Here we present results from the first deployment of novel, high definition, compact gas Time Projection Chambers (TPCs) with pixel chip readout as part of the BEAST II beam background measurement project at SuperKEKB. The TPCs provide detailed 3D imaging of ionization from neutron-induced nuclear recoils in a helium and carbon dioxide target gas mixture at standard temperature and pressure. We present the TPC performance and the neutron backgrounds observed during the initial stage of collider commissioning. We find excellent electron background rejection, leading to background-free nuclear recoil measurements above 50 keV ee , despite the extreme high-background environment. We measure an angular resolution better than 20° for recoil tracks longer than 1.7 mm, corresponding to an average ionization energy of approximately 100 keV ee . We also obtain the full 3D vector direction of helium recoils by utilizing charge profile measurements along the recoil axis, with a correct head/tail assignment efficiency of approximately 80%. With this performance, we present comparisons between measured and simulated event rates, recoil energy spectra, and directional distributions originating from beam–gas and Touschek beam losses at SuperKEKB. We utilize head/tail recognition to distinguish neutron components traveling with positive radial velocity in the Belle II coordinate system from those traveling in the opposite direction. Finally, we present a novel method of discriminating beam–gas interactions from Touschek beam losses that can eliminate the need for dedicated accelerator runs for background measurements. This method is still statistics-limited. However, future studies should be able to verify this method, which in turn could lead to neutron background analysis runs symbiotic with normal Belle II operation. The capabilities demonstrated here also suggest that high definition recoil imaging in gas TPCs is applicable to low energy, low-background experiments, such as directional dark matter searches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Convolution-based frequency domain multiplexing of SiPM readouts using the $\mathrm{DRS4}$ digitizer

Here we present 4:1 multiplexing of organic scintillators, each coupled to a silicon photomultiplier (SiPM), to reduce the need for a large number of digitizer input channels to readout highly pixelated radiation detection systems. Frequency domain multiplexing (FDM) encodes a detector pulse by assigning it a unique frequency via convolution before combining the encoded signal into a single channel. The combined signal is then read through a digitizer input channel. We have designed an FDM system to multiplex four SiPMs using DRS4 digitizer evaluation board from Paul Scherrer Institute (PSI). We demonstrate 4:1 multiplexing of the SiPM fast output signals and pulse recovery from the digitized multiplexed signal using deconvolution. The noise in the recovered pulse introduces a bias and uncertainty in the estimate of energy and timing that changes with pulse height. The relative uncertainty in the estimated energy from the recovered pulse decreases with pulse height with a maximum uncertainty of 3.1% for the low energy pulses (corresponding to 100 keV); the uncertainty in the estimated time pick-off also decreases with pulse height with a maximum uncertainty of 110 ps for the low energy pulses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Multiplicity trigger detector for the S π RIT experiment

A multiplicity trigger detector (MTD) was developed for the SπRIT experiment that aims to probe the high- density symmetry energy via heavy-ion collisions (HICs). The MTD is designed to measure the charged-particle multiplicity in HICs to provide a trigger signal that can be used to select high-multiplicity events induced by central collisions. The MTD consists of two side-walls segmented into 30 plastic scintillation paddles, each equipped with a multi-pixel photon counter. A custom board with EASIROC front-end ASIC is used as readout electronics. A multiplicity logic signal is generated by an on-board FPGA that processes the discriminated signals from EASIROCs. The overall latency of the whole detector system for outputting the trigger is less than 100 ns, including 52 ns of electronics latency for processing the signals. During the measurement of 112 Sn + 124 Sn reactions at an incident energy of 270 MeV/nucleon, the minimum multiplicity threshold of the MTD was set to 4, where the overall trigger efficiency was obtained to be about 39 % for inclusive nuclear reactions. Furthermore, a simulation study with a numerical calculation of HICs found that the central collisions of impact parameters of less than 4 fm can be triggered with a high efficiency of more than 95 % by the experimental trigger condition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Application of recoil-imaging time projection chambers to directional neutron background measurements in the SuperKEKB accelerator tunnel

Gaseous time projection chambers (TPCs) with high readout segmentation are capable of reconstructing detailed 3D ionization distributions of nuclear recoils resulting from elastic neutron scattering. Here, using a system of six compact TPCs with pixel ASIC readout, filled with a 70:30 mixture of He:CO 2 gas, we analyze the first directional measurements of beam-induced neutron backgrounds in the tunnel regions surrounding the Belle II detector at the SuperKEKB e + e – collider. With the use of 3D recoil tracking, we show that these TPCs are capable of maintaining nearly 100% nuclear recoil purity to reconstructed ionization energies (E reco ) as low as 5 keV ee . Using a large sample of Monte-Carlo (MC)-simulated 4 He, 12 C, and 16 O recoil tracks, we find consistency between predicted and measured recoil energy spectra in five of the six TPCs, providing useful validation of the neutron production mechanisms modeled in simulation. Restricting this sample to 4 He recoil tracks with E reco > 40 keV ee , we further demonstrate axial angular resolutions within 8° and we introduce a procedure that under suitable conditions, correctly assigns the vector direction to 91% of these simulated 4 He recoils. Applying this procedure to assign vector directions to measured 4 He recoil tracks, we observe consistency between the angular distributions of observed and simulated recoils, providing first experimental evidence of localized neutron “hotspots” in the accelerator tunnel. Observed rates of nuclear recoils in these TPCs suggest that simulation overestimates the neutron flux from these hotspots. Despite this, we estimate these hotspots to produce the majority of neutron backgrounds in the accelerator tunnel at SuperKEKB’s target luminosity of 6.3 x 10 35 cm –2 s –1 , making them important regions to continue to monitor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Capability Demonstration of a 3D CdZnTe Detector on a High-Altitude Balloon Flight

In collaboration between the University of Michigan and Los Alamos National Laboratory, a 3D position-sensing CdZnTe (CZT) detector prototype was built and integrated into a high-altitude balloon platform to evaluate its performance in a space-like mixed-radiation environment. The detector prototype, Orion Eagle, was designed to operate in near-vacuum environments without any temperature regulation. Orion Eagle was hand-launched from NASA’s Columbia Scientific Balloon Facility (CSBF) at Fort Sumner, NM on September 26, 2021, and successfully operated throughout a 9-hour flight, which reached 38.5 km in altitude. The flight met its objectives, successfully detecting atmospheric gamma rays and galactic cosmic rays, and raising the Technical Readiness Level from 4 to 6 for large-volume 3D CZT detector technology for space applications. Ionization tracks produced by charged particles create spatial signatures in the detector that are distinguishable from discrete gamma-ray interactions. Therefore, the 3D position-sensing capabilities using pixelated electrodes on a CZT detector can help enable discrimination of background charged particles from gamma-ray events without an anticoincidence shield. The potential for background rejection capability, ambient-temperature operation, gamma-ray coded-aperture and Compton imaging, and near High Purity Germanium (HPGe) energy resolution motivate the use of large-volume 3D CZT imaging spectrometers in future space missions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Advanced silicon tracking detector developments for the future Electron-Ion Collider

The proposed Electron-Ion Collider (EIC) will operate high-luminosity high-energy electron+proton and electron+nucleus collisions at the collision energies from 20 GeV to 141 GeV to solve several fundamental questions in the high energy and nuclear physics fields. Its instantaneous luminosity can reach 10 33-34 cm -2 s -1 and the bunching crossing rate is around 10 ns. The EIC project has received CD1 approval from the US DOE in 2021 and moves toward the machine design and preparation for construction. To realize various particle measurements with high precision at the future EIC, a low material-budget and high-granularity silicon vertex and tracking detector with fine spatial and momentum resolutions and nearly 4π solid angle coverage is desired. The Monolithic Active Pixel Sensor (MAPS) and AC Coupled Low Gain Avalanche Diode (AC-LGAD) technologies stand out of several advanced technology options for the EIC silicon vertex and tracking detector subsystems. The MAPS technology has advanced features of low material budget, low power consumption, good radiation resistance and fine spatial resolution. The AC-LGAD technology can achieve fast timing resolution. Latest studies and progress of the EIC silicon vertex and tracking detector conceptual design, performance validations in simulation and ongoing MAPS and AC-LGAD R&D will be shown. Furthermore, schedule and plan of the EIC project detector development will be discussed as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗