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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Search for Heavy Neutral Leptons Decaying to Electron-Positron Pairs and Neutral Pions in the MicroBooNE Detector

This thesis presents a search for heavy neutral leptons (HNLs) decaying inside the MicroBooNE detector. The MicroBooNE detector is a liquid-argon time projection chamber located at Fermilab that receives flux from two neutrino beams; the booster neutrino beam (BNB) and the neutrinos at the main injector (NuMI) beam. The search uses data taken when the NuMI beam was on, with a total exposure of $7.01\times10^{20}$ protons on target. HNLs would be produced in kaon decays, and the source of HNLs targeted in this search is kaons decaying at rest in the NuMI hadron absorber. The kinematics of the HNLs produced in this way allow their decays to be distinguished from the majority of beam-neutrino interactions and cosmic-ray activity that constitute the background. Two HNL decay channels are studied, $\nu$\ee and \vpi. Boosted decision trees (BDTs) are trained to separate the simulated HNL decays from the expected background events. The BDT score distributions are used to calculate upper limits on the mixing angle \umusq in the mass range $10\le m_{\rm HNL}\le 245$~MeV. This is the first direct search for HNL decays to the \vpi channel, and the limits provide the most stringent constraints on \umusq in the mass range $35<\mhnl<175$~MeV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

A laser inverse Compton scattering diagnostic to study runaway electron dynamics during tokamak disruptions

Both technical and simulation progress has been made toward implementing a laser inverse Compton scattering diagnostic on the DIII-D tokamak. This is a novel diagnostic which uses a short (sub-ns) pulse laser together with a fast (sub-ns) gated x-ray detector to measure relativistic electrons inside a tokamak plasma. The study of these relativistic electrons is important to make sure they can be removed from any tokamak-based power reactor, as they could damage vessel walls and cooling lines. This diagnostic is completely new for magnetic fusion research and has never been implemented before on a tokamak. It is found that good signals and radial profiles could be obtained with an optimized high-energy (7 Joule) laser. Using a standard off-the-shelf Nd:YAG (0.7 Joule) laser would give some signals above the noise but no ability to measure the relativistic electron radial profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The AMACStar ASIC for the HL-LHC ATLAS ITk Strip detector: design, verification, testing, and quality assurance

For the high-luminosity upgrade to the LHC (HL-LHC), the ATLAS detector at CERN requires an all-new inner detector, the Inner Tracker (ITk). The ITk Strip subdetector is made up of silicon modules, which include three types of radiation-hard ASICs. One of these is the Autonomous Monitor and Control (AMAC). The AMAC is manufactured by Global Foundries using 130 nm CMOS8RF DM technology and is approximately 3 by 5 mm in size. This ASIC autonomously monitors the temperatures, voltages, and currents in the module components while controlling critical values in order to prevent these quantities from reaching dangerous levels. The final design, AMACStar, was verified, tested, and ensured to perform all necessary functions. A quality control procedure using an in-house probe station set-up was developed in order to ensure that every individual chip on each wafer of AMACStars required by the ITk Strip project met performance requirements. The average per wafer yield of usable AMACStars is 92.33%, exceeding the design-specific 90% yield estimated for project costing. This estimate was based on actual yields for similar designs in this process.

Analogue electronic circuits↗
DOE OSTI2023

Heavy neutral leptons at beam dump experiments of future lepton colliders

A new beam dump experiment that utilizes the beam of future high energy electron-positron colliders could be an excellent avenue to search for dark sector particles due to its unprecedented high energy and intensity. We consider heavy neutral leptons (HNLs) as a specific example to demonstrate the sensitivity of searches for dark sector particles at future electron-positron collider beam dump experiments. This includes the study of the reach at the International Linear Collider (ILC), the Cool Copper Collider (C 3 ), and the Compact Linear Collider (CLIC). We comprehensively examine the HNL production and detector acceptance at these electron beam dump experiments. We show that these experiments will probe regions of HNL parameter space, not yet probed by past experiments, as well as by future approved experiments. Our study also motivates a more detailed analysis of heavy meson productions in high-energy electron-nucleon collisions in thick targets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Large scale SiPM testing for the Cosmic Muon Veto detector

A Cosmic Muon Veto (CMV) detector using extruded plastic scintillators is being built around the mini-Iron Calorimeter (mini-ICAL) detector at the transit campus of the India based Neutrino Observatory, Madurai. The extruded plastic scintillators will be embedded with wavelength shifting (WLS) fibres to absorb scintillating photons and propgate the re-emitted photons to the silicon-photomultipliers for the electronic signals. The CMV detector will require 760 extruded plastic scintillators to shield the mini-ICAL detector, and will require 3040 SiPMs for the readout. The design goal for the cosmic muon veto efficiency of the CMV is $>$99.99\% and fake veto rate less than 10$^{-5}$. Hence, every SiPM used in the detector needs to be characterised to satisfy the design goal of the CMV. For this, a large-scale testing system was developed, using an LED driver, to measure the gain and noise rate of each SiPM, and thus determine it's breakdown voltage ($V_{br}$) and optimum operating overvoltage ($V_{ov}$).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Observables for recoil identification in high-definition Gas Time Projection Chambers

Directional detection of nuclear recoils is broadly desirable in nuclear and particle physics. At low recoil energies, this capability may be used to confirm the cosmological origin of a dark matter signal, to penetrate the so-called neutrino floor, or to distinguish between different neutrino sources. Gas Time Projection Chambers (TPCs) can enable directional recoil detection if the readout granularity is sufficiently high, as is the case when micro-pattern gaseous detectors (MPGDs) are utilized. A key challenge in such detectors is identifying and rejecting background electron recoil events caused by gamma rays from radioactive contaminants in the detector materials and the environment. We define new observables that can distinguish electron and nuclear recoils, even at keV-scale energies, based on the simulated ionization's topology. Here we perform a simulation study that shows these observables outperform the traditionally used discriminant, dE/dx, by up to three orders of magnitude. Furthermore, these new observables work well even at ionization energies well below 10keV and remain robust even in the regime where directionality fails.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The Majorana Demonstrator readout electronics system

The M AJORANA D EMONSTRATOR comprises two arrays of high-purity germanium detectors constructed to search for neutrinoless double-beta decay in 76 Ge and other physics beyond the Standard Model. Its readout electronics were designed to have low electronic noise, and radioactive backgrounds were minimized by using low-mass components and low-radioactivity materials near the detectors. This paper provides a description of all components of the M AJORANA D EMONSTRATOR readout electronics, spanning the front-end electronics and internal cabling, back-end electronics, digitizer, and power supplies, along with the grounding scheme. The spectroscopic performance achieved with these readout electronics is also demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

SENSEI at SNOLAB: Single-Electron Event Rate and Implications for Dark Matter

We present results from data acquired by the SENSEI experiment at SNOLAB after a major upgrade in May 2023, which includes deploying 16 new sensors and replacing the copper trays that house the CCDs with a new light-tight design. We observe a single-electron event rate of (1.39±0.11)×10^{-5} e^{-}/pix/day, corresponding to (39.8±3.1) e^{-}/gram/day. This is an order-of-magnitude improvement compared to the previous lowest single-electron rate in a silicon detector and the lowest for any photon detector in the wavelength range between near-infrared and ultraviolet. We use these data to obtain a 90% confidence level upper bound of 1.53×10^{-5} e^{-}/pix/day and to set constraints on sub-GeV dark matter candidates that produce single-electron events. We hypothesize that the data taken at SNOLAB in the previous run, with an older tray design for the sensors, contained a larger rate of single-electron events due to light leaks. We test this hypothesis using data from the SENSEI detector located in the MINOS cavern at Fermilab.

dark matter↗
DOE OSTI2022

Artificial Intelligence for imaging Cherenkov detectors at the EIC

Abstract Imaging Cherenkov detectors form the backbone of particle identification (PID) at the future Electron Ion Collider (EIC). Currently all the designs for the first EIC detector proposal use a dual Ring Imaging CHerenkov (dRICH) detector in the hadron endcap, a Detector for Internally Reflected Cherenkov (DIRC) light in the barrel, and a modular RICH (mRICH) in the electron endcap. These detectors involve optical processes with many photons that need to be tracked through complex surfaces at the simulation level, while for reconstruction they rely on pattern recognition of ring images. This proceeding summarizes ongoing efforts and possible applications of AI for imaging Cherenkov detectors at EIC. In particular we will provide the example of the dRICH for the AI-assisted design and of the DIRC for simulation and particle identification from complex patterns and discuss possible advantages of using AI.

Instruments & Instrumentation↗
DOE OSTI2021

Cepstral scanning transmission electron microscopy imaging of severe lattice distortions

The development of four-dimensional (4D) scanning transmission electron microscopy (STEM) using fast detectors has opened-up new avenues for addressing some of longstanding challenges in electron imaging. One of these challenges is how to image severely distorted crystal lattices, such as at a dislocation core. Here we develop a new 4D-STEM technique, called Cepstral STEM, for imaging disordered crystals using electron diffuse scattering. In contrast to analysis based on Bragg diffraction, which measures the average and periodic scattering potential, electron diffuse scattering can detect fluctuations caused by crystal disorder. Local fluctuations of diffuse scattering are captured by scanning electron nanodiffraction (SEND) using a coherent probe. The harmonic signals in electron diffuse scattering are detected through Cepstral analysis and used for imaging. By integrating Cepstral analysis with 4D-STEM, we demonstrate that information about the distortive part of electron scattering potential can be separated and imaged at nm spatial resolution. Here, we apply the technique to the analysis of a dislocation core in SiGe and lattice distortions in a high entropy alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

Recent advances in detectors for imaging and spectroscopy have afforded in situ, rapid acquisition of hyperspectral data. While electron energy loss spectroscopy (EELS) data acquisition speeds with electron counting are regularly reaching 400 frames per second with near-zero read noise, signal to noise ratio (SNR) remains a challenge owing to fundamental counting statistics. In order to advance understanding of transient materials phenomena during rapid acquisition EELS, trustworthy analysis of noisy spectra must be demonstrated. In this study, we applied machine learning techniques to denoise high frame rate spectra, benchmarking with slower frame rate “ground truths”. The results provide a foundation for reliable use of low SNR data acquired in rapid, in-situ spectroscopy experiments. Such a tool-set is a first step toward both automation in microscopy as well as use of these methods to interrogate otherwise poorly understood transformations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Embedded FPGA developments in 130 nm and 28 nm CMOS for machine learning in particle detector readout

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Electromagnetic shower reconstruction and energy validation with Michel electrons and π 0 samples for the deep-learning-based analyses in MicroBooNE

This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two v μ -sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Finally, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

An electron paramagnetic resonance study of the electron transport in heavily Si-doped high Al content AlxGa1−xN

High Al mole fraction AlGaN is an ultrawide bandgap semiconductor with potential applications in power electronics and deep UV detectors. Although n-type material is achievable with Si-doping, the role of Si is controversial, particularly for AlxGa1−xN with x > 0.8. For this paper, AlGaN films were grown by plasma-assisted molecular beam epitaxy onto bulk AlN substrates and doped with 1018–1020 cm−3 Si. We examine electron transport in heavily Si-doped AlxGa1−xN with x ≥ 0.65 using magnetic resonance, which allows us to probe the neutral donors directly rather than the free carriers and avoids complications due to electrical contacts. Transport was studied through the temperature-dependent linewidth of the electron paramagnetic resonance (EPR) signature for the neutral donor. Analysis shows evidence of hopping conductivity in the most lightly doped samples and impurity band formation in the most heavily doped ones. The EPR results, which are consistent with Hall measurements performed on the same samples, are promising for the development of highly conducting high Al content AlGaN.

Materials Science↗
DOE OSTI2025

Search for light neutral particles decaying promptly into collimated pairs of electrons or muons in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for a dark photon, a new light neutral particle, which decays promptly into collimated pairs of electrons or muons is presented. The search targets dark photons resulting from the exotic decay of the Standard Model Higgs boson, assuming its production via the dominant gluon-gluon fusion mode. The analysis is based on 140 fb -1 of data collected with the ATLAS detector at the Large Hadron Collider from proton-proton collisions at a center-of-mass energy of 13 TeV. Events with collimated pairs of electrons or muons are analysed and background contributions are estimated using data-driven techniques. No significant excess in the data above the Standard Model background is observed. Upper limits are set at 95% confidence level on the branching ratio of the Higgs boson decay into dark photons between 0.001% and 5%, depending on the assumed dark photon mass and signal model.

Aad, G. [Aix-Marseille Université] (ORCID:00000002↗
DOE OSTI2020

RD53A: A large-scale prototype chip for the phase II upgrade in the serially powered HL-LHC pixel detectors

The phase II upgrade of the HL-LHC experiments within the LHC intends to deepen the studies of the Higgs boson and to allow the discovery of further particles by adding an integrated luminosity of about 4000 fb -1 over 10 years of operation. This upgrade would overwhelm the installed pixel detector readout chips with higher hit rates and radiation levels than ever before. To match these extreme requirements the RD53 collaboration, a joint effort between ATLAS and CMS, developed RD53A, a new generation pixel detector readout chip prototype manufactured in a 65 nm CMOS technology. It is half the size of the final pixel chips and designed to meet requirements in the face of 3 GHz/cm 2 hit rate after irradiation to 500 Mrad. The detector is able to use 50×50 μm 2 or 25×100 μm 2 pixels with high readout speed of up to 4 links per chip with 1.28 Gbit/s each. Shunt–LDO regulators integrated on the bottom of the chip provide the required voltages to the two power domains, analog and digital. These regulators enable serial powering of the pixel modules, which is the only feasible, radiation hard scheme to ensure acceptable power cable losses and to stay within the material budget for the future pixel detectors. Finally, an overview of the status and challenges of serial powering and the Shunt–LDO regulator development will be given.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Muon tagging with flash ADC waveform baselines

Here, this manuscript describes an innovative method to tag muons using the baseline information of the Flash ADC (FADC) waveform of PMTs in the JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) experiment. The experiment is designed to search for evidence of sterile neutrinos, and a reliable method for muon tagging is an essential component for background rejection because the detector is located above ground, on the 3rd floor of the J-PARC Material and Life Science Experimental Facility (MLF). Cosmogenic muons that stop within the detector volume and produce a Michel electron are a particularly important background that must be rejected for our sterile neutrino search. Utilizing this innovative method, more than 99.8 % of Michel electrons can be rejected even without using information from the detector’s veto region PMTs. This technique can be employed by any experiments which uses a similar detector configuration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗