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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Dark photons and axion-like particles at the electron-ion collider in China

The Electron-Ion Collider in China (EicC), a proposed high-luminosity facility with advanced charged particle and photon detection capabilities, provides unique opportunities to uncover new physics beyond the Standard Model. We analyze its sensitivity to dark photons produced through electron bremsstrahlung in coherent scattering. Thanks to its beam energy settings, it has the potential to comprehensively probe the previously unexplored parameter space between the constraints from meson decays and beam dumps below $\mathcal{O}(1)$ GeV with displaced-vertex search. Additionally, the EicC has the potential to probe axion-like particles (ALPs) in the mass range 0.1 GeV ≲ m a ≲ 5 GeV, with a coupling reach of Λ ≲ 10 6 GeV, by combining the prompt-decay and displaced-vertex searches. The projected sensitivities to ALPs exceed the current bounds.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

PIXE – State of the Art, Systems, Challenges

Particle-induced X-ray emission (PIXE) is an analytical technique for elemental analysis in which a charged-particle beam (most commonly protons, but also alpha particles or heavier ions) ionizes inner-shell electrons in target atoms. When these vacancies are filled by outer-shell electrons, the atom emits characteristic X-rays (e.g., Kα, Kβ, L-series) whose energies are unique to each element. Measuring the X-ray spectrum therefore enables identification of the elements present and, with appropriate calibration and modeling, their concentration. PIXE provides rapid, simultaneous, quantitative multi-element detection with trace-level sensitivity for many mid- to high-Z elements, often with minimal sample preparation. It is widely used across materials science (thin films, alloys, corrosion), geology (mineral chemistry, provenance) and environmental monitoring (aerosols, particulates, soils); semiconductor contamination analysis (wafer surface/trace metals), cultural heritage (pigments, inks, archaeological artifacts) and forensics (gunshot residue, glass/pain), and biological/medical studies (tissue/biomaterial trace-element mapping).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Status of CHIP-TRAP: The Central Michigan University High-Precision Penning Trap

Precise and accurate atomic mass data provide crucial information for applications in a wide range of fields in physics and beyond, including astrophysics, nuclear structure, particle and neutrino physics, fundamental symmetries, chemistry, and metrology. The most precise atomic mass measurements are performed on charged particles confined in a Penning trap. Here, we describe the development, status, and outlook of CHIP-TRAP: the Central Michigan University high-precision Penning trap. CHIP-TRAP aims to perform ultra-high precision (~1 part in 10 11 fractional precision) mass measurements on stable and long-lived isotopes produced with external ion sources and transported to the Penning traps. Along the way, ions of a particular m/q are selected with a multi-reflection time-of-flight mass separator (MR-TOF-MS), with further filtering performed in a cylindrical capture trap before the ions are transported to a pair of hyperbolic measurement traps. In this paper, we report on the design and status of CHIP-TRAP and present results from the commissioning of the ion sources, MR-TOF-MS, and capture trap. We also provide an outlook on the continued development and commissioning of CHIP-TRAP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development of thin-gap GEM- μ RWELL hybrid detectors

Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A meshless stochastic method for Poisson–Nernst–Planck equations

A plethora of biological, physical, and chemical phenomena involve transport of charged particles (ions). Its continuum-scale description relies on the Poisson–Nernst–Planck (PNP) system, which encapsulates the conservation of mass and charge. The numerical solution of these coupled partial differential equations is challenging and suffers from both the curse of dimensionality and difficulty in efficiently parallelizing. We present a novel particle-based framework to solve the full PNP system by simulating a drift–diffusion process with time- and space-varying drift. We leverage Green’s functions, kernel-independent fast multipole methods, and kernel density estimation to solve the PNP system in a meshless manner, capable of handling discontinuous initial states. The method is embarrassingly parallel, and the computational cost scales linearly with the number of particles and dimension. We use a series of numerical experiments to demonstrate both the method’s convergence with respect to the number of particles and computational cost vis-à-vis a traditional partial differential equation solver.

Chemistry↗
DOE OSTI2022

Nuclear Data for High Energy Ion Interactions and Secondary Particle Production

Understanding the harmful effects of galactic cosmic rays (GCRs) on space exploration requires a substantial amount of nuclear data. Specifically, the interaction of energetic GCR charged particles with spacecraft materials generates secondary radiations that, through energy deposition, can harm astronauts and electronic systems. By identifying the gaps in our knowledge of the relevant nuclear data – interaction cross sections – and identifying ways to fill those gaps – with measurements, compilations, evaluations, disseminations, reaction modeling, sensitivity studies, and uncertainty quantification – the safety and viability of space exploration can be improved. This work surveys the state of the art in this interdisciplinary field and identifies promising collaborative research topics that have significant potential to advance our understanding of the effects of the space radiation environment on space exploration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Time Projection Chambers instrumented with resistive MicroMegas for the SAND near detector of DUNE

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino accelerator experiment aiming for precise measurements of the neutrino oscillation parameters. DUNE will include a near detector complex regrouping three different detectors among which SAND (System for on-Axis Neutrino Detection) that will be the only one permanently on the neutrino beam axis in charge of monitoring in detail the emitted neutrino beam and its stability through time, a crucial characteristic to realize accurate oscillation measurements at the percent level. SAND will reuse the superconducting magnet and the electromagnetic calorimeter of the KLOE experiment. We will describe in the following the proposal of using, as inner tracker of SAND, a large 3D matrix of 1.5cm side scintillator cubes (3DST) surrounded by 3 gaseous Time Projection Chambers. This setup allows to realize accurate beam monitoring combining the 3DST unprecedented capability of neutron detection and energy measurement with the high precision momentum resolution for charged particles offered by the TPCs. The proposed TPC design allows to reach spatial resolutions of a few hundreds of micrometers using 1 cm pads by deploying the resistive MicroMegas technology for the charge readout.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Melting LHC detectors: a novel search for stopped long-lived particles

Particles at the TeV scale with lifetimes of a year or longer could have been abundantly produced at the LHC yet escaped detection because of backgrounds, and could still be trapped within detector materials. With gluinos in split-supersymmetry as a working example, we show that these trapped particles can be recovered from detector materials once prepared in liquid form, for example, by melting silicon detectors, extracting liquid argon from the electromagnetic calorimeter, or constructing a large water pool near ATLAS or CMS. These liquid samples can then be processed using iterative centrifugation followed by mass spectrometry, enabling single-particle sensitivity in macroscopic samples. This method can potentially discover gluinos up to 3 TeV in mass at the HL-LHC. It can also improve upon existing limits for other long-lived particles. For example, it can discover the stop up to 2 TeV, and will also be sensitive to integer-charged particles in the TeV range.

Gonski, Julia L. [SLAC]↗
DOE OSTI2023

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm 0.6$% and 84.1$\pm 0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

TinyTPC: A Test Stand for LAr Doping

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) featuring a pixelated readout system (LArPix) designed to improve the detection of charged particles. To enhance energy measurements at MeV scales, TinyTPC will study the impact of isobutylene, a photosensitive dopant that converts light to charge, and xenon, a wavelength shifter. This presentation will detail TinyTPC's commissioning, operation, data collection methodologies, noise levels, and upcoming tests involving isobutylene, xenon, and radioactive sources.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Two-particle azimuthal correlations in γp interactions using pPb collisions at s NN = 8.16 TeV

The first measurements of the Fourier coefficients ( V n Δ ) of the azimuthal distributions of charged hadrons emitted from photon-proton (γp) interactions are presented. The data are extracted from 68.8 nb −1 of ultra-peripheral proton-lead (pPb) collisions at s NN = 8.16 TeV using the CMS detector. The high energy lead ions produce a flux of photons that can interact with the oncoming proton. This γp system provides a set of unique initial conditions with multiplicity lower than in photon-lead collisions but comparable to recent electron-positron and electron-proton data. The V n Δ coefficients are presented in ranges of event multiplicity and transverse momentum ( p T ) and are compared to corresponding hadronic minimum bias pPb results. For a given multiplicity range, the mean p T of charged particles is smaller in γp than in pPb collisions. For both the γp and pPb samples, V 1 Δ is negative, V 2 Δ is positive, and V 3 Δ consistent with 0. For each multiplicity and p T range, V 2 Δ is larger for γp events. The γp data are consistent with model predictions that have no collective effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Clustering of electromagnetic showers and particle interactions with graph neural networks in liquid argon time projection chambers

Liquid argon time projection chambers (LArTPCs) are a class of detectors that produce high resolution images of charged particles within their sensitive volume. In these images, the clustering of distinct particles into superstructures is of central importance to the current and future neutrino physics program. Electromagnetic (EM) activity typically exhibits spatially detached fragments of varying morphology and orientation that are challenging to efficiently assemble using traditional algorithms. Similarly, particles that are spatially removed from each other in the detector may originate from a common interaction. Graph neural networks (GNNs) were developed in recent years to find correlations between objects embedded in an arbitrary space. The graph particle aggregator (GrapPA) first leverages GNNs to predict the adjacency matrix of EM shower fragments and to identify the origin of showers, i.e., primary fragments. On the PILArNet public LArTPC simulation dataset, the algorithm achieves a shower clustering accuracy characterized by a mean purity of 99.4%, a mean efficiency of 99.6% and a primary identification accuracy of 99.8%. It yields a relative shower energy uncertainty of (4.1 + 1.4 / $\sqrt{\text{E(GeV)})}$% and a shower direction uncertainty of (2.1/ $\sqrt{\text{E(GeV)})}$°. Finally, the optimized algorithm is then applied to the related task of clustering particle instances into interactions and yields a mean purity of 99.8% and a mean efficiency of 99.5% for an interaction density of $\mathcal{O}(1)$ m –3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Perpendicular magnetofluid theory for magnetically confined plasmas in the collisionless limit

Note that the magnetically confined plasmas in thermonuclear fusion turn to be collisionless. Some particles are trapped by the inhomogeneous equilibrium field or by the waves, while some others keep circulating. One cannot expect the charged particles to be collectively localized in space by collisions along the magnetic field lines. Consequently, the fluid parameters relating to the parallel motion, such as parallel fluid velocity, become inadequate. In this paper, the perpendic- ular magnetofluid theory for magnetically confined plasmas in the collisionless limit is developed. It revises Braginskii’s transport theory by releasing the collisional dominance assumption. In the perpendicular direction, the particle spatial localization is solo resulted from the strong magnetic field, while the finite Larmor radius (FLR) effects are taken into account in the next order. In the parallel direction, the particle mobility feature is fully retained by constructing only the per- pendicular moments. Therefore, besides the FLR effects till order O($k$ $^{2}_{⊥}$ $ρ$ $^{2}_{i}$ ), the Landau damping, the trapped particle effects, and other parallel kinetic effects are all kept in the current formalism. Here, k ⊥ is the perpendicular wave number and ρ i is the ion Larmor radius. Here, the theory can be used both for the analytical and numerical studies of magnetically confined plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Signal Processing in SBND with Calibrated and Validated Electronics and Field Responses

SBND is a liquid argon time projection chamber in Fermilab’s Short-Baseline Neutrino Program, located 110 m from the neutrino source and operating in a high-rate environment with unprecedented statistics. Charged particles from neutrino interactions ionize the argon, and the resulting electrons drift to the anode wires, inducing current signals recorded as raw waveforms. These waveforms are a convolution of deposited charge with the electronics and TPC field responses, making accurate signal processing essential for recovering the true charge distribution. Signal processing forms the starting point for SBND reconstruction, directly impacting hit finding, charge calibration, clustering, and the reconstruction of tracks and showers, and therefore playing a key role in energy reconstruction and particle identification. In this poster, we present an overview of the SBND signal processing chain, including noise removal, channel-by-channel electronics correction, signal identification, and deconvolution using measured electronics and TPC field responses. We demonstrate that the two kernel functions—electronics and field responses—achieve high precision when compared to data, ensuring that the SBND signal processing chain provides a robust and accurate foundation for event reconstruction and precision physics measurements.

Singh, Prabhjot [Louisiana State U.] (ORCID:000000↗
DOE OSTI2021

Initial evaluation of a multimodal diamond sensor for simultaneous temperature and radiation measurements

Several experimental disciplines require simultaneous neutron flux and temperature monitoring. This paper provides the groundwork on a diamond sensor concept that could be used in harsh environments where the limits of current technologies are exceeded. Here, we present initial results on the functionality of a multimodal diamond sensor, which can simultaneously sense the presence of alpha particles at a few counts per second at temperatures up to 494 K. Such a sensor may also have applications where both charged particles or neutron detection and temperature measurement are simultaneously desired.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Apparent temperatures of neutron-poor and neutron-rich compound nuclei

The possibility of the dependence of the nuclear caloric curve on neutron excess sets a limit on the accuracy of our knowledge of the nuclear equation of state, and thus impacts predictive capabilities of nuclear reaction and nuclear astrophysics models. To date, theoretical models have not reached consensus on the magnitude or sign on the asymmetry dependence. To provide constraints, we have measured evaporated particles and heavy residues for complete and incomplete fusion-evaporation reactions in inverse kinematics. The temperatures extracted from the observed light charged particles tend to favor higher temperatures for the neutron-rich fused systems, though they are near the limits of the systematic uncertainty. The present measurement may be used as an upper limit to constrain the asymmetry dependence of the nuclear caloric curve.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗