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DOE OSTI2021

Measurement of the bulk radioactive contamination of detector-grade silicon with DAMIC at SNOLAB

We present measurements of bulk radiocontaminants in the high-resistivity silicon CCDs from the DAMIC experiment at SNOLAB. We utilize the exquisite spatial resolution of CCDs to discriminate between α and β decays, and to search with high efficiency for the spatially-correlated decays of various radioisotope sequences. Using spatially-correlated β decays, we measure a bulk radioactive contamination of 32 Si in the CCDs of 140 ± 30 μBq/kg, and place an upper limit on bulk 210 Pb of < 160 μBq/kg. Using similar analyses of spatially-correlated α and β decays, we set upper limits of < 11 μBq/kg (0.9 ppt) on 238 U and < 7.3 μBq/kg (1.8 ppt) on 232 Th in the bulk silicon. The ability of DAMIC CCDs to identify and reject spatially-coincident backgrounds, particularly from 32 Si, has significant implications for the next generation of silicon-based dark matter experiments, where β's from 32 Si decay will likely be a dominant background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Neutron tagging following atmospheric neutrino events in a water Cherenkov detector

We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218±9 μs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Eos: conceptual design for a demonstrator of hybrid optical detector technology

Eos is a technology demonstrator, designed to explore the capabilities of hybrid event detection technology, leveraging both Cherenkov and scintillation light simultaneously. With a fiducial mass of four tons, Eos is designed to operate in a high-precision regime, with sufficient size to utilize time-of-flight information for full event reconstruction, flexibility to demonstrate a range of cutting edge technologies, and simplicity of design to facilitate potential future deployment at alternative sites. Results from Eos can inform the design of future neutrino detectors for both fundamental physics and nonproliferation applications. This paper describes the conceptual design and potential applications of the Eos

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Twelve-crystal prototype of Li 2 MoO 4 scintillating bolometers for CUPID and CROSS experiments

An array of twelve 0.28 kg lithium molybdate (LMO) low-temperature bolometers equipped with 16 bolometric Ge light detectors, aiming at optimization of detector structure for CROSS and CUPID double-beta decay experiments, was constructed and tested in a low-background pulse-tube-based cryostat at the Canfranc underground laboratory in Spain. Performance of the scintillating bolometers was studied depending on the size of phonon NTD-Ge sensors glued to both LMO and Ge absorbers, shape of the Ge light detectors (circular vs. square, from two suppliers), in different light collection conditions (with and without reflector, with aluminum coated LMO crystal surface). The scintillating bolometer array was operated over 8 months in the low-background conditions that allowed to probe a very low, μBq/kg, level of the LMO crystals radioactive contamination by 228 Th and 226 Ra.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

A new hybrid gadolinium nanoparticles-loaded polymeric material for neutron detection in rare event searches

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

Dark Matter detectors (WIMPs, axions, etc.)↗

DOE OSTI2025

Configuration, Performance, and Commissioning of the ATLAS b-jet Triggers for the 2022 and 2023 LHC data-taking periods

In 2022 and 2023, the Large Hadron Collider produced approximately two billion hadronic interactions each second from bunches of protons that collide at a rate of 40 MHz. The ATLAS trigger system is used to reduce this rate to a few kHz for recording. Selections based on hadronic jets, their energy, and event topology reduce the rate to 𝒪(10) kHz while maintaining high efficiencies for important signatures resulting in b-quarks, but to reach the desired recording rate of hundreds of Hz, additional real-time selections based on the identification of jets containing b-hadrons (b-jets) are employed to achieve low thresholds on the jet transverse momentum at the High-Level Trigger. The configuration, commissioning, and performance of the real-time ATLAS b-jet identification algorithms for the early LHC Run 3 collision data are presented. These recent developments provide substantial gains in signal efficiency for critical signatures; for the Standard Model production of Higgs boson pairs, a 50% improvement in selection efficiency is observed in final states with four b-quarks or two b-quarks and two hadronically decaying τ-leptons.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

High-level hadronic tau lepton triggers of the CMS experiment in proton-proton collisions at √(s) = 13.6 TeV

The trigger system of the CMS detector is pivotal in the acquisition of data for physics measurements and searches. Studies of final states characterized by hadronic decays of tau leptons require the reconstruction and the identification of genuine tau leptons against quark- and gluon-initiated jets at the trigger level. This is a difficult task, particularly as improvements to the LHC have resulted in an increased number of interactions per bunch crossing in recent years. To address this challenge, a series of machine-learning algorithms with high identification efficiency and low computational cost have been incorporated into the high-level trigger for hadronically decaying tau leptons. In this paper, these developments and the trigger performance are summarized using data collected by the CMS experiment in proton-proton collisions at √(s) = 13.6 TeV in 2022–2023, corresponding to an integrated luminosity of 62 fb -1 .

Particle identification methods↗

NASA NTRS1973

Differential energy spectra of low energy (less than 8.5 MeV per nucleon) heavy cosmic rays during solar quiet times

Explorer 47 satellite observations of carbon, oxygen, and heavier nuclei differential energy spectra below 8.5 MeV/nucleon are presented for solar quiet time periods. A dE/dx vs E method for particle identification and energy determination was used. The instrumentation telescope included an isobutane proportional counter, a surface barrier Si detector, and a cylindrical plastic scintillator anticoincidence shield. The observations were performed outside the bow-shock and in the ecliptic plane. Results show an anisotropy of about 25% at 22 degrees west of the sun with a C/O ratio of 0.5 supporting a solar origin. The low energy portions of the C and O spectra have steep negative slopes, and the corresponding power law is given. Peculiarities in the O spectrum are discussed.

Hovestadt, D.↗

DOE OSTI2024

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

25 ENERGY STORAGE↗

DOE OSTI2026

A 24-channel ultra-low-noise preamplifier for dN/dx measurements with drift tube detectors

Cluster counting $(dN/dx)$ is a promising method to enhance particle identification for gaseous detectors, especially in next-generation collider experiments like the FCC-ee, where good $π/K$ separation over a broad momentum range is essential. However, its implementation in large-scale systems has been limited by the challenging requirements for high-resolution signal amplification and readout. This paper presents a 24-channel ultra-low-noise preamplifier board designed for drift tube detectors to enable $dN/dx$ measurements. The three-stage amplification topology employs SiGe transistors and integrates dedicated noise-minimization techniques, achieving a charge gain of 21.11 mV/fC from 0.3 fC to 50 fC, a bandwidth of 542 MHz, and a voltage gain of 47.8 dB. The measured voltage noise density is 0.35 nV/$\sqrt{\textrm{Hz}}$ , surpassing most of the state-of-the-art preamplifiers for gaseous and silicon detectors. Validation tests conducted on the sMDT chambers at the CERN Proton Synchrotron test beam facility demonstrate that the proposed design meets the stringent preamplifier requirements for implementing the $dN/dx$ method in drift-tube detector systems, achieving an equivalent noise charge of 0.14 fC and a signal-to-noise ratio of 73 when operated with a He:iC 4 H 10 (90:10) gas mixture. The design also shows promise for broader application in other gaseous or semiconductor detectors.

Drift tube detector↗

NASA NTRS2015

Particle Capture Devices and Methods of Use Thereof

The present invention provides a device and methods of use thereof in microscale particle capturing and particle pairing. This invention provides particle patterning device, which mechanically traps individual particles within first chambers of capture units, transfer the particles to second chambers of opposing capture units, and traps a second type of particle in the same second chamber. The device and methods allow for high yield assaying of trapped cells, high yield fusion of trapped, paired cells, for controlled binding of particles to cells and for specific chemical reactions between particle interfaces and particle contents. The device and method provide means of identification of the particle population and a facile route to particle collection.

Voldman, Joel↗

DOE OSTI2025

Particle hit clustering and identification using point set transformers in liquid argon time projection chambers

Liquid argon time projection chambers are often used in neutrino physics and dark-matter searches because of their high spatial resolution. The images generated by these detectors are extremely sparse, as the energy values detected by most of the detector are equal to 0, meaning that despite their high resolution, most of the detector is unused in a particular interaction. Instead of representing all of the empty detections, the interaction is usually stored as a sparse matrix, a list of detection locations paired with their energy values. Traditional machine learning methods that have been applied to particle reconstruction such as convolutional neural networks (CNNs), however, cannot operate over data stored in this way and therefore must have the matrix fully instantiated as a dense matrix. Operating on dense matrices requires a lot of memory and computation time, in contrast to directly operating on the sparse matrix. We propose a machine learning model using a point set neural network that operates over a sparse matrix, greatly improving both processing speed and accuracy over methods that instantiate the dense matrix, as well as over other methods that operate over sparse matrices. Compared to competing state-of-the-art methods, our method improves classification performance by 14%, segmentation performance by more than 22%, while taking 80% less time and using 66% less memory. Compared to state-of-the-art CNN methods, our method improves classification performance by more than 86%, segmentation performance by more than 71%, while reducing runtime by 91% and reducing memory usage by 61%.

calibration and fitting methods↗

DOE OSTI2021

Alpha Shape Analysis (ASA) Framework for Post- Clustering Property Determination in Atom Probe Tomographic Data

While application of clustering algorithms to atom probe tomography data have enabled quantification of solute clusters in terms of number density, size, and subcomposition there exist other properties (e.g., volume, surface area, and composition) that are better determined by defining an interface between the cluster and the surrounding matrix. The limitation in composition results from an ion selection step where the expected matrix ion types are omitted from the cluster search algorithm to enhance the contrast between the matrix and cluster and to reduce the complexity of the search. Previously, composition determination within solute clusters has utilized a secondary envelopment and erosion step on top of conventional methods such as maximum separation. In this work, we present a novel stochastic method that combines the particle identification fidelity of a conventional clustering algorithm with the analytical flexibility of mesh-based approaches through the generation of alpha shapes for each identified cluster. Furthermore, the corresponding mesh accounts for concave components of the clusters and determines the volume and surface area of the clusters; additionally, the mesh boundary is utilized to update the total composition according to the internal ions.

42 ENGINEERING↗

DOE OSTI2024

Fiber reinforced aerogel composites

Fiber reinforced aerogel composites, including a transparent composite material that contains an aerogel and fibers embedded into the aerogel and/or bonded to one or more surfaces of the aerogel, and composites that contain an aerogel tile and an assemblage of fibers embedded into the aerogel tile or bonded to the aerogel tile that are useful as Cherenkov radiators for the detection and identification of subatomic particles. Also, methods of making and using the composites.

Pegg, Ian Louis↗

NASA NTRS1984

Analysis of individual biological particles by mass spectrometry

A method is developed for the detection and identification of biological particles introduced in aerosol form into a quadrupole mass spectrometer. The bacterial aerosol is generated by nebulizing an ethanol suspension. The particles are introduced into the ion source of the mass spectrometer in the form of a beam, where they are individually volatilized on a V-type rhenium filament and ionized by electron impaction. It is shown that the average intensity of a mass peak is obtained from the pulse height distribution of about a thousand ion pulses from different particles. Pseudomonas putida, Bacillus subtilis, and Bacillus cereus are used in the studies. Differences between the relative intensities of mass peaks in the spectra from P. putida and B. subtilis are found and may provide a method for differentiation of microorganisms. The results for the two species agree reasonably well with those reported by Kistemaker et al. (1975) and Schulten et al. (1973). However, there exist some differences between the two spectra in the high mass range due to the difference in the pyrolysis conditions.

Sinha, M. P.↗

DOE OSTI2026

Searching for heavy charged relics in the Earth

We propose a method for detecting an ambient density of heavy, electrically-charged particles. Such particles would impact the Earth, lose energy in terrestrial matter, and become trapped. We study the accumulation of these rare particles in multiple target materials that provide large exposure, such as water and geological rocks. We discuss strategies for concentrating the particles by centrifugation or gravitational settling, along with particle identification using mass spectrometry. This method enables the discovery of charged relics with masses $1-10^{12}\,{\rm TeV}$ comprising a tiny fraction of the local dark matter density, reaching down to $f_X\sim 10^{-20}$ at the lowest masses. A pathfinder experiment using only a liter of water and one centrifuge (or $\sim \text{m}^3$ and no centrifuge) operating for a month can already reach $f_X\sim 10^{-10}$ and probe new parameter space.

Ebadi, Reza [Johns Hopkins U.; Delaware U.] (ORCID↗

DOE OSTI2024

Parallel-plate avalanche counters for heavy-ion beam tracking: History and mysteries

Despite being an old detector concept, position-sensitive parallel-plate avalanche counters (PPACs) remain widely used today for heavy-ion position and timing measurements. In modern rare isotope beam facilities and large-acceptance fragment separators, PPACs are used to characterize beam properties (diagnostics), facilitate beam delivery (tuning), and provide event-by-event beam tracking for particle identification (PID). Most popular particle localization methods in PPAC detectors are based on strip electrodes electrically connected to resistive-chain circuits or delay lines. More exotic systems include optical readouts based on recording electroluminescence light with high-granularity photodetector arrays or high-resolution resistive anode electrodes. PPACs with conventional resistive-chain or delay-line readouts achieve typical position and time resolutions of below 1 mm ( σ ) and around 150 ps ( σ ), respectively. In addition, delay-line systems are capable of counting rates above several hundred kHz for beam areas of a few millimeters square, and around 1 MHz for larger beam sizes. Resistive-chain readouts have limited rates of a few tens of kHz. A review of the operation principles and performance of PPAC detectors is presented in this paper. We will discuss decades-long experience building and operating PPACs developed at the National Superconducting Cyclotron Laboratory, and then refined at the Facility for Rare Isotope Beams (FRIB), mostly focusing on the delay-line readout technique (DLPPAC). We will also discuss problems that arise due to electric discharges at high rates and briefly describe ongoing developments at FRIB. Published by the American Physical Society 2024

Physics↗