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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 181 records · Page 10

Single-pixel reconstructive mid-infrared micro-spectrometer

Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO 2 ). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF 2 ) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications.

47 OTHER INSTRUMENTATION↗

Temperature-dependent characterization of large-area superconducting microwire array with single-photon sensitivity in the near-infrared

Superconducting nanowire single photon detectors (SNSPDs) are a leading detector technology for time-resolved single-photon counting from the ultraviolet to the near-infrared regime. The recent advancement in single-photon sensitivity in micrometer-scale superconducting wires opens up promising opportunities to develop large area SNSPDs with applications in low background dark matter detection experiments. Here, we present the first detailed temperature-dependent study of a 4-channel 1×1 mm 2 WSi superconducting microwire single photon detector (SMSPD) array, including the internal detection efficiency, dark count rate, and importantly the coincident dark counts across pixels. The detector shows saturated internal detection efficiency for photon wavelengths ranging from 635 nm to 1650 nm, time jitter of about 160 ps for 1060 nm photons, and a low dark count rate of about 10 -2 Hz. Additionally, the coincidences of dark count rate across pixels are studied for the first time in detail, where we observed an excess of correlated dark counts, which has important implications for low background dark matter experiments. The results presented is the first step towards characterizing and developing SMSPD array systems and associated background for low background dark matter detection experiments.

47 OTHER INSTRUMENTATION↗

VISSTPX2DRECTG16V4MINNIS (c1)

Satellite-based retrievals of cloud and radiation properties are available in this value-added product provided by Bill Smith’s group at NASA/Langley using the VISST (Visible Infrared Solar-Infrared Split Window Technique) algorithm. This product contains VISST-derived pixel-level products from the GOES-16 satellite, rectilinear projection 2-D array.

broadband LW flux↗

Deuteron Evaporation from N = Z Compound Nuclei

Deuteron evaporation was observed from the N = Z compound nuclei 52 Fe ⋆ , 56 Ni ⋆ , and 64 Ge ⋆ in an experiment conducted at Argonne National Laboratory, USA. The experiment included a novel combination of two highly pixelated double-sided Si-strip detectors inside the Microball chargedparticle detection array, allowing for unequivocal discrimination of evaporated deuterons from protons and α particles. In conjunction with the Gammasphere array, Neutron Shell, and additional ancillary detectors, decay paths into various residual nuclei were investigated. The study provides insights into the competition of deuteron vs. proton-neutron evaporation as a function of available excitation energy and populated angular momentum. Results are interpreted using a statistical evaporation formalism for multiple subsequent particle emissions. The decisive factor in the comparison appears to be the available excitation energy in the residual system, with single nucleon evaporation preferred over deuteron evaporation for higher excitation energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Detection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning

Detecting concealed chemicals and explosives remains a critical challenge in global security. Terahertz time-domain spectroscopy (THz-TDS) offers a promising non-invasive and stand-off detection technique owing to its ability to penetrate optically opaque materials without causing ionization damage. While many chemicals exhibit distinct spectral features in the terahertz range, conventional terahertz-based detection methods often struggle in real-world environments, where variations in sample geometry, thickness, and packaging can lead to inconsistent spectral responses. In this study, we present a chemical imaging system that integrates THz-TDS with deep learning to enable accurate pixel-level identification and classification of different explosives. Operating in reflection mode and enhanced with plasmonic nanoantenna arrays, our THz-TDS system achieves a peak dynamic range of 96 dB and a detection bandwidth of 4.5 THz, supporting practical, stand-off operation. By analyzing individual time-domain pulses with deep neural networks, the system exhibits strong resilience to environmental variations and sample inconsistencies. Blind testing across eight chemicals—including pharmaceutical excipients and explosive compounds—resulted in an average classification accuracy of 99.42% at the pixel level. Notably, the system maintained an average accuracy of 88.83% when detecting explosives concealed under opaque paper coverings, demonstrating its robust generalization capability. These results highlight the potential of combining advanced terahertz spectroscopy with neural networks for highly sensitive and specific chemical and explosive detection in diverse and operationally relevant scenarios.

Imaging and sensing↗

Enhancing the signal-to-noise ratio for laser ranging by adjusting the photon equivalent threshold of a multi-pixel photon counter

A photon equivalent (PE) threshold-adjusting regime for laser ranging is proposed based on a multi-pixel photon counter (MPPC), and the mechanism of PE threshold influence on the signal-to-noise ratio (SNR) is demonstrated and analysed. The unique PE threshold adjustability of an MPPC leads to interesting results for laser ranging. Experimental results show that the SNR of the laser ranging system is significantly improved by optimising the MPPC PE threshold, which is beneficial for detection and false alarm probabilities. Submillimeter laser ranging resolution is obtained with noncooperative targets placed several meters away. Nanosecond dead time single photon laser ranging without gating is obtained due to an MPPC with a small pixel area. Multiple target ranging is implemented with a single MPPC rather than an array. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

280 GHz Focal Plane Unit Design and Characterization for the Spider-2 Suborbital Polarimeter

We describe the construction and characterization of the 280 GHz bolometric focal plane units (FPUs) to be deployed on the second flight of the balloon-borne Spider instrument. These FPUs are vital to Spider’s primary science goal of detecting or placing an upper limit on the amplitude of the primordial gravitational wave signature in the cosmic microwave background (CMB) by constraining the B-mode contamination in the CMB from Galactic dust emission. Each 280 GHz focal plane contains a $16 \times 16$ grid of corrugated silicon feedhorns coupled to an array of aluminum–manganese transition-edge sensor (TES) bolometers fabricated on 150 mm diameter substrates. In total, the three 280 GHz FPUs contain 1530 polarization-sensitive bolometers (765 spatial pixels) optimized for the low loading environment in flight and read out by time-division SQUID multiplexing. In this paper, we describe the mechanical, thermal, and magnetic shielding architecture of the focal planes and present cryogenic measurements which characterize yield and the uniformity of several bolometer parameters. The assembled FPUs have high yields, with one array as high as 95% including defects from wiring and readout. We demonstrate high uniformity in device parameters, finding the median saturation power for each TES array to be $\sim $ 3 pW at 300 mK with a less than 6% variation across each array at $1\sigma $ . These focal planes will be deployed alongside the 95 and 150 GHz telescopes in the Spider-2 instrument, slated to fly from McMurdo Station in Antarctica in December 2018.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Neuro-Spark: A Submicrosecond Spiking Neural Networks Architecture for In-Sensor Filtering

Neuro-Spark, which is a new neuromorphic architecture with a field-programmable gate array (FPGA) implementation for ultrafast spiking neural network (SNN) inference at the edge, facilitates smart-pixel in-sensor filtering for high-energy physics experiments at the Large Hadron Collider (LHC). Utilizing the evolutionary optimization for neuromorphic systems (EONS) training method, we generate compact SNN models with 91% signal efficiency, akin to convolutional neural networks but with half the parameters. However, deploying near the detector poses a challenge because the SNN must handle a sustained input data rate exceeding 1013 GB/s. To overcome this, we propose a novel hardware architecture that uses high-level synthesis to construct a tuned architecture for the EONS-trained SNN. In addition to the analysis and validation with an AMD Xilinx Artix-A7 FPGA, our solution consumes only ç24% of FPGA LUT and flipflops. We also introduce an innovative quantization method that reduces FPGA resource utilization by ç15% without compromising accuracy. Our FPGA implementation achieves computing latency of ç10 ns for smart-pixel application inference on an edge FPGA.

Miniskar, Narasinga Rao↗

Results from the DUNE ND-LAr 2x2 Demonstrator Run 2

The Deep Underground Neutrino Experiment (DUNE) is a cutting-edge, long-baseline experiment under construction in the United States, based on large liquid-argon time projection chambers (LArTPCs). The DUNE Near Detector LArTPC (ND-LAr) will employ a novel modular architecture using a pixelated LArPix charge readout. To validate this design and characterize detector response, the 2×2 demonstrator—an array of eight optically isolated LArTPC modules—was deployed at Fermilab in 2024. During winter 2025, the 2x2 demonstrator was operated for a second data-taking campaign (Run 2) with the aim of studying the low-energy response of the detector. Run 2 focused on calibration and response studies using a suite of deployed radioactive sources. Gamma sources (²²Na, ⁶⁰Co, and ⁸⁸Y) were used to probe module-to-module performance variations, energy resolution, and calibrations. Neutron sources (AmBe and a pulsed neutron generator) enabled studies of neutron interactions in liquid argon, including inelastic scatters and neutron capture signals, relevant for low-energy backgrounds and detector modeling. In addition, the detector was doped with ²²⁰Rn, providing Bi–Po coincidence signals that allow precise calibration of the charge and scintillation response. This poster will present results from these calibration campaigns. These studies provide critical validation of the ND-LAr modular LArTPC concept and inform calibration and reconstruction strategies for the full DUNE near detector.

Mora-Lepin, Luis [Florida State U.] (ORCID:0000000↗

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↗

Deep learning for morphological identification of extended radio galaxies using weak labels

Abstract The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25–35 $\mu$ Jy beam $^{-1}$ . We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP $_{50}$ of 67.5% and 76.8% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM

Astronomy & Astrophysics↗

Hierarchical Phased-Array Antennas Coupled to Al KIDs: A Scalable Architecture for Multi-band Millimeter/Submillimeter Focal Planes

We present the optical characterization of two-scale hierarchical phased-array antenna kinetic inductance detectors (KIDs) for millimeter/submillimeter wavelengths. Our KIDs have a lumped-element architecture with parallel plate capacitors and aluminum inductors. The incoming light is received with a hierarchical phased array of slot dipole antennas, split into 4 frequency bands (between 125 GHz and 365 GHz) with on-chip lumped-element band-pass filters, and routed to different KIDs using microstriplines. Individual pixels detect light for the 3 higher-frequency bands (190–365 GHz), and the signals from four individual pixels are coherently summed to create a larger pixel detecting light for the lowest frequency band (125–175 GHz). The spectral response of the band-pass filters was measured using Fourier transform spectroscopy (FTS), the far-field beam pattern of the phased-array antennas was obtained using an infrared source mounted on a 2-axis translating stage, and the optical efficiency of the KIDs was characterized by observing loads at 294 K and 77 K. We report on the results of these three measurements.

47 OTHER INSTRUMENTATION↗

Optical and x-ray characterization of the Daedalus ultrafast x-ray imager

The Daedalus ultrafast x-ray imager is the latest generation in Sandia’s hybrid CMOS detector family. With three frames along an identical line of sight, 1 ns minimum integration time, a higher full well than Icarus, and added features, Daedalus brings exciting new capabilities to diagnostic applications in inertial confinement fusion and high energy density science. In this work, we present measurements of time response, dynamic range, spatial uniformity, pixel cross-talk, and absolute x-ray sensitivity using pulsed optical and x-ray sources. Here, we report a measured 1.5 Me — full well, pixel sensitivity at 9.58 × 10 —7 V/e — , and an estimate of spatial uniformity at ~5% across the sensor array.

47 OTHER INSTRUMENTATION↗

Design and Bolometer Characterization of the SPT-3G First-Year Focal Plane

During the austral summer of 2016-2017, the third-generation camera, SPT-3G, was installed on the South Pole Telescope, increasing the detector count in the focal plane by an order of magnitude relative to the previous generation. Designed to map the polarization of the cosmic microwave background, SPT-3G contains ten 6 ''-hexagonal modules of detectors, each with 269 trichroic and dual-polarization pixels, read out using 68x frequency-domain multiplexing. Here we discuss design, assembly, and layout of the modules, as well as early performance characterization of the first-year array, including yield and detector properties.

bolometer↗

Large active-area superconducting microwire detector array with single-photon sensitivity in the near-infrared

Superconducting nanowire single photon detectors (SNSPDs) are the highest-performing technology for time-resolved single-photon counting from the UV to the near-infrared. The recent discovery of single-photon sensitivity in micrometer-scale superconducting wires is a promising pathway to explore for large active area devices with application to dark matter searches and fundamental physics experiments. We present 8-pixel $1 mm^2$ superconducting microwire single photon detectors (SMSPDs) with $1\,\mathrm{\mu m}$-wide wires fabricated from WSi and MoSi films of various stoichiometries using electron-beam and optical lithography. Devices made from all materials and fabrication techniques show saturated internal detection efficiency at 1064 nm in at least one pixel, and the best performing device made from silicon-rich WSi shows single-photon sensitivity in all 8 pixels and saturated internal detection efficiency in 6/8 pixels. This detector is the largest reported active-area SMSPD or SNSPD with near-IR sensitivity published to date, and the first report of an SMSPD array. By further optimizing the photolithography techniques presented in this work, a viable pathway exists to realize larger devices with $cm^2$-scale active area and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a large array of Silicon Drift Detectors for high-rate synchrotron fluorescence spectroscopy

An array of small-area Silicon Drift Detectors (SDD), named Hera, has been developed at Brookhaven National Laboratory (BNL) in the past few years. Its primary application is high-rate spectroscopy at synchrotrons. Each SDD pixel is a 1 mm × 1 mm square to match the footprint of the original diode-based pixel detector called Maia, which was developed for the same application. The replacement of the diode with an SDD allows for better energy resolution at short shaping times and an increased stability of the detector. 32, 96, and 384-channel arrays were designed and fabricated and achieved a Full Width Half Maximum (FWHM) as low as 176 eV at 5.9 keV with peaking time of 1 μs at -13°C. The sensor design, simulation, fabrication, its readout system, and its spectroscopic performance are reported.

47 OTHER INSTRUMENTATION↗

Femtojoule optical nonlinearity for deep learning with incoherent illumination

Optical neural networks (ONNs) are a promising computational alternative for deep learning due to their inherent massive parallelism for linear operations. However, the development of energy-efficient and highly parallel optical nonlinearities, a critical component in ONNs, remains an outstanding challenge. Here, we introduce a nonlinear optical microdevice array (NOMA) compatible with incoherent illumination by integrating the liquid crystal cell with silicon photodiodes at the single-pixel level. We fabricate NOMA with more than half a million pixels, each functioning as an optical analog of the rectified linear unit at ultralow switching energy down to 100 femtojoules per pixel. With NOMA, we demonstrate an optical multilayer neural network. Our work holds promise for large-scale and low-power deep ONNs, computer vision, and real-time optical image processing.

36 MATERIALS SCIENCE↗