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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Super-Resolution Ptychography with Small Segmented Detectors

To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. Further, we demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe 2 /WSe 2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors.

2D materials↗
DOE OSTI2022

NuSD: A Geant4 based simulation framework for segmented anti-neutrino detectors

NuSD: Neutrino Segmented Detector is a Geant4-based user application that simulates inverse beta decay event in a variety of segmented scintillation detectors developed by different international collaborations. This simulation framework uses a combination of cross-programs and libraries including Geant4, ROOT and CLHEP developed and used by high energy physics community. It will enable the neutrino physics community to simulate and study neutrino interactions within different detector concepts using a single program. In addition to neutrino simulations in segmented detectors, this program can also be used for various research projects that use of scintillation detectors for different physics purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Reconstruction of fast neutron direction in segmented organic detectors using deep learning

A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. Here, the model is based on recurrent neural network, which can be trained by a sequence of data obtained from an event recorded in the detector and suitably pre-processed. The performance of deep learning-based model is compared with the conventional double-scatter detection algorithm in reconstructing the direction of a fast neutron source. With the deep learning model, the uncertainty in source direction of 0.301 rad is achieved with 100 neutron detection events in a segmented cubic organic scintillator detector with a side length of 46 mm. To reconstruct the source direction with the same angular resolution as the double-scatter algorithm, the deep learning method requires 75% fewer events. Application of this method could augment the operation of segmented detectors operated in the neutron scatter camera configuration for applications such as special nuclear material detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

SANDD: A directional antineutrino detector with segmented 6 Li-doped pulse-shape-sensitive plastic scintillator

We present a characterization of a small (9-liter) and mobile 0.1% 6 Li-doped pulse-shape-sensitive plastic scintillator antineutrino detector called SANDD (Segmented AntiNeutrino Directional Detector), constructed for the purpose of near-field reactor monitoring with sensitivity to antineutrino direction. SANDD comprises three different types of module. A detailed Monte Carlo simulation code was developed to match and validate the performance of each of the three modules. The combined model was then used to produce a prediction of the performance of the entire detector. Analysis cuts were established to isolate antineutrino inverse beta decay events while rejecting large fraction of backgrounds. The neutron and positron detection efficiencies are estimated to be 34.8% and 80.2%, respectively, while the coincidence detection efficiency is estimated to be 71.7%, resulting in inverse beta decay detection efficiency of 20.0% ± 0.2%(stat.) ± 2.1%(syst.). Finally, the predicted directional sensitivity of SANDD produces an uncertainty of 20° in the azimuthal direction per 100 detected antineutrino events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning (SPECTRE-ML) v0.8.0

SPECTRE-ML (Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning) is a machine learning based program for finding optimal clusters of radiation detector segments (i.e., pixels or voxels) in order to improve spectral performance. It provides facilities for pre-processing and analyzing training datasets, running ML algorithms, and evaluating and visualizing outputs. SPECTRE-ML outperforms simpler ad-hoc segmentation methods such as uniform depth clusters, learning detector performance trends such as dead layers, edge effects, and gain shifts. Although extensible to arbitrary highly-segmented spectroscopic radiation detectors, SPECTRE-ML currently focuses on improving spectral performance in highly-segmented CdZnTe (CZT) detectors for International Atomic Energy Agency (IAEA) non-destructive assay (NDA) safeguards tasks.

Vavrek, Jayson↗
DOE OSTI2026

Ionization-based search for magnetic monopoles using the NOvA Far Detector

We report a search for highly ionizing magnetic monopoles in the cosmic-ray flux using a 2713-day dataset collected during 2015–2025 with the NOvA Far Detector, a 14-kt segmented detector located on Earth’s surface in Minnesota, United States. The search is sensitive to monopoles across a wide range of speeds, 7 × 10 −4 < 𝛽 < 0.995, and is sensitive to masses as low as 2 × 10 5 GeV for the fastest monopoles. No signal was observed. With the detector’s large surface area and minimal overburden, we achieve the strongest flux limits reported to date in several regions of speed and mass. For heavy monopoles with masses above 10 13 GeV that are able to reach the detector from above or—crossing Earth—from below, we find a flux limit 𝜙 90% < 2 × 10 −16 cm −2 s −1 sr −1 (90% confidence level) for monopoles with 0.005 < 𝛽 < 0.8. Across the same range of speeds, we report a limit 𝜙 90% < 8 × 10 −16 cm −2 s −1 sr −1 for light monopoles with masses above 10 8 GeV that can reach the detector from above.

magnetic monopoles↗
DOE OSTI2026

Gaia: segmented germanium detector for high-energy X-ray fluorescence and spectroscopic imaging

We present Gaia, a monolithic array of 96 high-purity germanium pixel detectors integrated with a custom low-noise application-specific integrated circuit (ASIC) and a field-programmable gate array (FPGA)-based data acquisition system. The sensor operates at ∼100 K using a commercial closed-cycle cryocooler, with the in-vacuum electronics thermally isolated from the cold finger to ensure thermal stability. The system demonstrates an average energy resolution of 711 eV at 122 keV, measured using a 57 Co source, and 253 eV at 5.89 keV, measured with 55 Fe across all channels. The readout architecture incorporates a high-performance FPGA paired with a dual-core ARM processor, forming a complete embedded Linux-based computing platform. Communication between the processor and FPGA is handled via memory-mapped I/O, and data are streamed over high-speed gigabit Ethernet. A full-scale 384-pixel Gaia detector, based on this 96-element module, is currently under fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Directional Recoil Detection

Searches for dark matter–induced recoils have made impressive advances in the last few years. Yet the field is confronted by several outstanding problems. First, the inevitable background of solar neutrinos will soon inhibit the conclusive identification of many dark matter models. Second, and more fundamentally, current experiments have no practical way of confirming a detected signal's Galactic origin. The concept of directional detection addresses both of these issues while offering opportunities to study novel dark matter– and neutrino-related physics. The concept remains experimentally challenging, but gas time projection chambers are an increasingly attractive option and, when properly configured, would allow directional measurements of both nuclear and electron recoils. In this review, we reassess the required detector performance and survey relevant technologies. Fortuitously, the highly segmented detectors required to achieve good directionality also enable several fundamental and applied physics measurements. As a result, we comment on near-term challenges and how the field could be advanced.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Highly Segmented Silicon Strip Detectors for Radiation Detection (LDRD Final Report)

Large area highly segmented silicon strip detectors were investigated for use in applied radiation detection applications. Two ASIC-based readout electronics solutions were tested for compatibility. During the analysis, it was determined that significant computational resources and highly specialized firmware are required to reconstruct the data into a meaningful data stream for generalized spectroscopic performance. Future investment in the technology and careful choice of readout ASIC is expected to demonstrate relevance in measuring high activity samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Flavor Classification in ICARUS Using Convolutional Visual Networks

In this work, we adapt the Convolutional Visual Network (CVN) approach [1] to the ICARUS detector by incorporating TPC stitching methods inspired by NuGraph[8]. The stitching technique used here is unique to ICARUS, designed specifically to handle its distinct detector segmentations. We then retrain the network using ICARUS-specific data. This study underscores the flexibility of deep learning models in high-energy physics and the importance of accounting for detector-specific features when transferring machine learning techniques between experiments. This poster presents the methods, classification performance, and insights gained from applying CVN to ICARUS data.

Wieler, Felipe [Tech. Fed. Parana U.]↗
DOE OSTI2025

High-energy X-ray imaging with a Germanium MM-PAD hybrid pixel detector

Germanium is a high-Z sensor material with excellent energy resolution and attractive properties for high-energy photon detection. Despite its advantages, the need for cryogenic operation and challenges in the fabrication of pixelated high-purity germanium have hindered the development of segmented detectors. We report on the fabrication and performance of a germanium imaging detector with 150 μm pixel pitch hybridized to the MM-PAD ASIC. The detector was capable of high-resolution radiographic imaging and has a fast temporal response. Additionally, we describe the detector's upper operating temperature limits using both the MM-PAD and MARS ASICs, achieving stable operation up to 130 K and 190 K, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Neutrino Flavor Classification in ICARUS Experiment Using Convolutional Visual Networks

In this work, I adapt the Convolutional Visual Network (CVN) approach to the ICARUS detector by incorporating TPC stitching methods inspired by NuGraph. The stitching technique used here is unique to ICARUS, designed specifically to handle its distinct detector segmentation s. I then retrain the network using ICARUS-specific data. This study underscores the flexibility of deep learning models in high-energy physics and the importance of accounting for detector-specific features when transferring machine learning techniques between experiments. This dissertation presents the methods, classification performance, and insights gained from applying CVN to ICARUS data.

Wieler, Felipe Andre [Parana Tech. Fed. U., Toledo↗
DOE OSTI2020

Pixel Array Germanium Detectors for Nuclear Physics (Final Technical Report)

The Department of Energy (DOE) Office of Nuclear Physics supports the development and maintenance of germanium gamma-ray detector arrays at national laboratories and universities. Germanium gamma-ray detectors provide state-of-the-art gamma-ray energy resolution, making them critical for gamma-ray and x-ray spectroscopy in Nuclear Physics. Furthermore, detector segmentation and charge-signal waveform processing enables 3-dimensional (3D) measurement of gamma-ray interaction locations needed for the highest-fidelity Nuclear Physics experiments. Attaining and maintaining excellent gamma-ray energy resolution depends largely on the naturally excellent charge-collection properties of germanium crystals. However, the optimal method for achieving the best practical 3D spatial resolution within the detector volume at high counting rates is less clear.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Calibration strategy of the PROSPECT-II detector with external and intrinsic sources

This paper presents an energy calibration scheme for an upgraded reactor antineutrino detector for the Precision Reactor Oscillation and Spectrum Experiment (PROSPECT). The PROSPECT collaboration is preparing an upgraded detector, PROSPECT-II (P-II), to advance capabilities for the investigation of fundamental neutrino physics, fission processes and associated reactor neutrino flux, and nuclear security applications. P-II will expand the statistical power of the original PROSPECT (P-I) dataset by at least an order of magnitude. The new design builds upon previous P-I design and focuses on improving the detector robustness and long-term stability to enable multi-year operation at one or more sites. The new design optimizes the fiducial volume by elimination of dead space previously occupied by internal calibration channels, which in turn necessitates the external deployment. In this paper, we describe a calibration strategy for P-II. Here, the expected performance of externally deployed calibration sources is evaluated using P-I data and a well-benchmarked simulation package by varying detector segmentation configurations in the analysis. The proposed external calibration scheme delivers a compatible energy scale model and achieves comparable performance with the inclusion of an additional AmBe neutron source, in comparison to the previous internal arrangement. Most importantly, the estimated uncertainty contribution from the external energy scale calibration model meets the precision requirements of the P-II experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Low-dose high-resolution $\mathrm{TOF}$-$\mathrm{PET}$ using ionization-activated multi-state low-$\mathrm{Z}$ detector media

We propose PET scanners using low atomic number media that undergo a persistent local change of state along the paths of the Compton recoil electrons. Measurement of the individual scattering locations and angles, deposited energies, and recoil electron directions allows using the kinematical constraints of the 2-body Compton scattering process to perform a statistical time-ordering of the scatterings, with a high probability of precisely identifying where the gamma first interacted in the detector. In these cases the Line-of-Response is measured with high resolution, determined by the underlying physics processes and not the detector segmentation. There are multiple such media that act through different mechanisms. As an example in which the change of state is quantum-mechanical through a change in molecular configuration, rather than thermodynamic, as in a bubble chamber, we present simulations of a two-state photoswitchable organic dye, a ‘Switchillator’, that is activated to a fluorescent-capable state by the ionization of the recoil electrons. The activated state is persistent, and can be optically excited multiple times to image individual activated molecules. Energy resolution is provided by counting the activated molecules. Location along the LOR is implemented by large-area time-of-flight MCP-PMT photodetectors with single photon time resolution in the tens of ps and sub-mm spatial resolution. Simulations indicate a large reduction of dose.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗