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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Performance of a Modular Ton-Scale Pixel-Readout Liquid Argon Time Projection Chamber

The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Low-energy Electron-track Imaging for a Liquid Argon Time-projection-chamber Telescope Concept Using Probabilistic Deep Learning

The GammaTPC is an MeV-scale single-phase liquid argon time-projection-chamber gamma-ray telescope concept with a novel dual-scale pixel-based charge-readout system. It promises to enable a significant improvement in sensitivity to MeV-scale gamma rays over previous telescopes. The novel pixel-based charge readout allows for imaging of the tracks of electrons scattered by Compton interactions of incident gamma rays. The two primary contributors to the accuracy of a Compton telescope in reconstructing an incident gamma-ray’s original direction are its energy and position resolution. In this work, we focus on using deep learning to optimize the reconstruction of the initial position and direction of electrons scattered in Compton interactions, including using probabilistic models to estimate predictive uncertainty. We show that the deep-learning models are able to predict locations of Compton scatters of MeV-scale gamma rays from simulated 500 μm pixel-based data to better than 1 mm rms error and are sensitive to the initial direction of the scattered electron. We compare and contrast different deep-learning uncertainty estimation algorithms for reconstruction applications. Additionally, we show that event-by-event estimates of the uncertainty of the locations of the Compton scatters can be used to select those events that were reconstructed most accurately, leading to improvement in locating the origin of gamma-ray sources on the sky.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Real-time Anomaly Detection for Liquid Argon Time Projection Chambers

We present a real-time anomaly detection framework for liquid argon time projection chambers (LArTPCs), targeting applications in particle physics experiments such as the Short Baseline Near Detector (SBND) or the future Deep Underground Neutrino Experiment (DUNE). These experiments employ detectors that generate and stream high-resolution but sparse images of neutrino and other particle interactions. Our approach utilizes anomaly detection with autoencoders, compressed through knowledge distillation (KD), to enable the detection of anomalous signals in the data through efficient inference on resource-constrained hardware. The framework is targeted for deployment on computing platforms equipped with field-programmable gate arrays (FPGAs), GPUs, or CPUs, allowing low-latency selection of relevant activity directly from the raw detector data stream. We demonstrate that our approach is suitable for the detection and localization of anomalously "high-multiplicity" activity, and outline promising applications for LArTPC online data filtering and triggering.

FOS: Physical sciences↗
DOE OSTI2024

Chamber studies of OH + dimethyl sulfoxide and dimethyl disulfide: insights into the dimethyl sulfide oxidation mechanism

Abstract. The oxidation of dimethyl sulfide (DMS) in the marine atmosphere represents an important natural source of non-sea-salt sulfate aerosol, but the chemical mechanisms underlying this process remain uncertain. While recent studies have focused on the role of the peroxy radical isomerization channel in DMS oxidation, this work revisits the impact of the other channels (OH addition and OH abstraction followed by bimolecular RO2 reaction) on aerosol formation from DMS. Due to the presence of common intermediate species, the oxidation of dimethyl sulfoxide (DMSO) and dimethyl disulfide (DMDS) can shed light on these two DMS reaction channels; they are also both atmospherically relevant species in their own right. This work examines the OH oxidation of DMSO and DMDS, using chamber experiments monitored by chemical ionization mass spectrometry and aerosol mass spectrometry to study the full range of sulfur-containing products across a range of NO concentrations. The oxidation of both compounds is found to lead to rapid aerosol formation (which does not involve the intermediate formation of SO2), with a substantial fraction (14 %–47 % S yield for DMSO and 5 %–21 % for DMDS) of reacted sulfur ending up in the particle phase and the highest yields observed under elevated NO conditions. Aerosol is observed to consist mainly of sulfate, methanesulfonic acid, and methanesulfinic acid. In the gas phase, the NOx dependence of several products, including SO2 and S2-containing organosulfur species, suggest reaction pathways not included in current mechanisms. Based on the commonalities with the DMS oxidation mechanism, DMSO and DMDS results are used to reconstruct DMS aerosol yields; these reconstructions roughly match DMS aerosol yield measurements from the literature but differ in composition, underscoring remaining uncertainties in sulfur chemistry. This work indicates that both the abstraction and addition channels contribute to rapid aerosol formation from DMS and highlights the need for more study into the fate of small sulfur radical intermediates (e.g., CH3S, CH3SO2, and CH3SO3) that are thought to play central roles in the DMS oxidation mechanism.

Goss, Matthew B. (ORCID:0000000226885463)↗
DOE OSTI2025

Developing A Custom-Built Metal Aerosol Processing Chamber: Analysis of Aerosol Coagulation at Low Humidities

We have developed an intermediate size (906 L) aerosol processing chamber, and this work reports on the design and initial characterization of dry aerosol experiments. Specifically, we are determining wall-loss and coagulation correction factors using the observed size distribution measurements for surrogates of common aerosol classes: sodium chloride, sucrose, and biomass burning aerosol smoke. Results show that, on average, sodium chloride, sucrose, and smoke wall-loss rates converge to similar values on relatively short time scales (< 1 h). The fitted coagulation correction factor, W C -1 , for smoke particles (1.23 ± 0.312), indicates that on average they adhere to each other more than sodium chloride (0.969 ± 0.524) and sucrose (1.16 ± 1.38). The relative uncertainty is high for the coagulation correction, but it is consistent with our Monte Carlo error analysis. This study lays the foundation for future experiments at elevated humidity and supersaturation conditions to characterize the influence of particle shape on coagulation and cloud parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Teaching sterile neutrinos in an undergrad laboratory: a sterile-neutrino search using data from the MicroBooNE liquid-argon time projection chamber performed in an undergraduate teaching laboratory

Dataset associated with "A sterile-neutrino search using data from the MicroBooNE liquid-argon time projection chamber performed in an undergraduate teaching laboratory" an educational paper to teach data analisys within particle physics for 3-4 yr physics major undergrads. Data format are csv, h5 and pkl

Gramellini, Elena [Manchester U.] (ORCID:000000031↗
DOE OSTI2020

AEROICESTUDY Colorado State University Continuous Flow Diffusion Chamber (CFDC) version R0

This dataset comprises measurements of atmospheric ice nucleating particle (INP) number concentrations at ARM's Southern Great Plains (SGP) Site Guest Instrument Facility (GIF), in Lamont, Oklahoma, during the 2019 Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY). The results reported here are from the Colorado State University Continuous Flow Diffusion Chamber (CFDC-1H) and represent real-time measurements of ambient INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2019

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 21 June to 25 September, 2019 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 09:00 - 16:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Eriophorum angustifolium. Image files (.jpg) captured by Wingscapes TimelapseCams, compressed as zip files. Additional information in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2017

Time lapse photography (*.jpg) of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Barrow (now Utqiagvik), Alaska. Images were recorded from 21 June to 18 September, 2017 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 11:00-14:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Petasites frigidus. Also included multiple metadata files including reporting formats as *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2021

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 17 June to 19 September, 2021 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 09:00 - 16:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam Pro cameras. The target species was Carex aquatilis. Individual jpg images from each camera have been combined in zip format. The data package includes a metadata document with example fields of view from each camera (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2018

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 17 June to 24 September, 2018 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images are *.jpg files recorded daily at 30 minute intervals, from 11:00 - 14:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Arctagrostis latifolia. Additional information in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Measurement of the Total Hadronic $\pi^-$ on Argon Cross Section in the Kinetic Energy Range from 0.2-1 Giga-Electron Volts in a Liquid Argon Time Projection Chamber

The liquid argon time projection chamber (LArTPC) technology offers fine-grained tracking along with excellent calorimetric and particle identification capabilities, making it a powerful tool for experimental neutrino physics. Thus, the LArTPC has become the technology of choice for studying neutrino oscillations over short ( 1000 km) baselines by experiments such as MicroBooNE, SBND, ICARUS, and DUNE. The LArIAT (Liquid Argon in a Test-beam) experiment exposes a LArTPC to a controlled beam of charged particles at the Fermilab Test Beam Facility to perform calibration studies and measurements of charged hadron-argon cross sections, with the goal of helping to reduce systematic uncertainties in LArTPC-based neutrino experiments. This work presents a measurement of the total hadronic π⁻-Ar cross section in the kinetic energy range from 0.2 GeV to 1 GeV, using data from the LArIAT experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Searching for Clues for a Matter Dominated Universe in Liquid Argon Time Projection Chambers

Liquid Argon Time Projection Chambers (LArTPCs) represent one of the most widely utilized neutrino detection techniques in neutrino experiments, for instance, in the Short Baseline Neutrino (SBN) program and the future large-scale LArTPC: Deep Underground Neutrino Experiment (DUNE). The high-end technique, facilitating excellent spatial and calorimetric reconstruction resolution, also enables testing exotic Beyond Standard Model (BSM) theories, such as baryon number violation (BNV) processes (e.g., proton-decay, neutron-antineutron oscillation). At the same time, Machine Learning (ML) techniques have demonstrated their ubiquitous use in recent decades; ML techniques have also become some of the most powerful tools in high-energy physics (HEP) analyses. Furthermore, the development of algorithms to cater to the needs of problems in HEP (i.e., triggering, reconstruction, improving sensitivity, etc.) has also become an active area of research. By developing a combined approach using Convolutional Neural Network (CNN) and Boosted Decision Tree (BDT) techniques, the sensitivity of neutron-antineutron oscillation in DUNE is evaluated for a projected exposure of 400kton&middot;years. Additionally, to meet the triggering requirement to select such rare events in DUNE, such a search is only supported with highly efficient self-triggering algorithms. An ML-based self-triggering scheme for large-scale LArTPCs, such as DUNE, is also developed with the intention of implementation on field-programmable gate arrays (FPGAs). The ML-based approach for searching for neutron-antineutron oscillation can be demonstrated and validated on the current LArTPC MicroBooNE. The analysis in MicroBooNE represents the first-ever search for neutron-antineutron oscillation in a LArTPC. DUNE's projected 90% C.L. sensitivity to the neutron antineutron oscillation lifetime is 6.45&times;10³² years, assuming 1.327&times;10³⁵ neutron&middot;years, equivalent to 10 years of DUNE far detector exposure (400kton&middot;years). For MicroBooNE, assuming 372 seconds of exposure (equivalent to 3.13&times;10³⁶ neutron&middot;years), the 90% C.L. lifetime sensitivity is found at 3.07&times;10²⁵ yrs, after accounting for Monte-Carlo statistical uncertainty and systematic uncertainty from detector effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Simulation and Development of the Radial Time Projection Chamber For the Bonus12 Experiment in CLAS12

Knowledge of the structure of nucleons (i.e. protons and neutrons) is a central topic of interest to nuclear/particle physicists. Much more is known about the structure of the proton than the neutron due to the lack of high-density free neutron targets. The Barely Off-shell Nucleon Structure experiment (BONuS12) at Jefferson Lab (JLab) is a second generation experiment upgraded/optimized to advance our knowledge of the neutron's structure using the deep-inelastic scattering of electrons off deuterium. Typically, since deuterium is a nuclear target, corrections for off-shell and nuclear binding effects must be taken into account in order to extract results on the neutron. These corrections are model-dependent and therefore have limited our success in extracting neutron information using deuterium targets. In the BONuS12 experiment, 10.6 GeV electrons are scattered off of a deuterium target. By detecting the low momentum spectator proton at backward angles, the uncertainty due to final state interactions is minimized. The goal of the experiment is to measure the ratio of the neutron to proton structure functions ($F^n_2/F^p_2$) as the Bjroken scaling variable x approaches 1. The newly designed Radial Time Projection Chamber (RTPC) for BONuS12 detects the spectator proton in coincidence with the scattered electron, which is detected in the CEBAF Large Acceptance Spectrometer (CLAS12). This work presents the simulation and development of the new BONuS12 RTPC. The design, construction, and testing of the Drift-gas Monitoring Sysytem (DMS) for the BONuS12 experiment is also described. The results of the DMS operation as well as the first preliminary data from the BONuS12 experimental run are given. Because the BONuS12 data analysis depends on CLAS12 working effectively, an effort to verify the CLAS12 operation with the extraction of the inclusive deep inelastic cross section from the first experiment in CLAS12 (Run Group A) will be presented.

Dzbenski, Nathan↗
DOE OSTI2021

Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber

The transportation sector accounts for almost a third of the United States energy consumption. We are developing predictive simulations of the complex in-cylinder processes of internal combustion engines to improve performance and decrease pollutant emissions. Using volume rendering, we provide a first look at the jet impingement and ignition inside a piston-cylinder chamber. Through the visualization, we were able to construct a complete 3D picture of the jet impingement on the piston-bowl walls leading to the formation of pockets of auto-ignition of fuel-air mixture. These auto-ignition pockets subsequently lead to flame stabilization releasing the chemical energy for conversion to useful work. A detailed physical picture of flame stabilization as provided by the visualization techniques presented in this study help in the design next-generation internal combustion engines.

91 SC - Advanced Scientific Computing Reseach (ASC↗
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. 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.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Results on photon-mediated dark matter-nucleus interactions from the PICO-60 C$_{3}$F$_{8}$ bubble chamber

Many compelling models predict dark matter coupling to the electromagnetic current through higher multipole interactions, while remaining electrically neutral. Different multipole couplings have been studied, among them anapole moment, electric and magnetic dipole moments, and millicharge. This study sets limits on the couplings for these photon-mediated interactions using non-relativistic contact operators in an effective field theory framework. Using data from the PICO-60 bubble chamber leading limits for dark matter masses between 2.7 GeV/c$^2$ and 24 GeV/c$^2$ are reported for the coupling of these photon-mediated dark matter-nucleus interactions. The detector was filled with 52 kg of C$_3$F$_8$ operating at thermodynamic thresholds of 2.45 keV and 3.29 keV, reaching exposures of 1404 kg-day and 1167 kg-day, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Neutrino Hunting: Looking through a UV Lens Scintillation Photon Detection in a Large-Volume Liquid Argon Time Projection Chamber, Exposed to a Multi-GeV Charged Particle Beam

The Deep Underground Neutrino Experiment (DUNE) will be a world-class neutrino observatory and nucleon decay detector designed to answer fundamental questions about elementary particles and their role in the universe. The DUNE experiment will consist of a a Near Detector, located at Fermilab, and a Far Detector, approximately 1.5~km underground at the Sanford Underground Research Facility in South Dakota, located $\sim$1300~km away. The accelerator complex at Fermilab will host an intense beam of neutrinos directed toward the two detectors. My dissertation centers on the implementation of technologies used to detect scintillation photon signals in liquid argon in the context of the DUNE's Far Detector Single-Phase (SP) module design, and features direct contributions to the Photon Detection System (PDS) deployed in the ProtoDUNE-SP Large-Volume Liquid Argon Time Projection Chamber (LArTPC) prototype. The PDS is needed for non-beam event timing, such as atmospheric neutrinos, proton d ecay, and supernova detection. The PDS provides a prompt signal ($t_{0}$ information) for micro-second event time determination, which improves the TPC's spatial localization along drift direction, enables accurate ionization-signal-attenuation determination, and even provides calorimetry. My dissertation will discuss an overview of the DUNE and ProtoDUNE-SP experiment and how we detect neutrinos in LAr, via charge and scintillation light. It will discuss my core experimental and analysis work, in regards to the Photon Detection System; including my contributions in establishing procedures for the commissioning and integration for the Photon Detector System that will be valuable during the construction, installation, commissioning, and operations of the DUNE Far Detector. In addition, it will comprehensively discuss the capability of three different photon detection technologies, and their characteristics and responses to muon and electron beam particles over a range of beam momenta , from 0.3~GeV/$c$ - 7~GeV/$c$. Further, the overall progress detailed in this thesis will help pave the way toward understanding the physical properties of these detectors, which will contribute to the success of the sensitivity measurements required for determining the neutrino mass hierarchy and $\delta_{CP}$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗