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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Gaseous Argon-Based Near Detector to Enhance the Physics Capabilities of DUNE

This document presents the concept and physics case for a magnetized gaseous argon-based detector system (ND-GAr) for the Deep Underground Neutrino Experiment (DUNE) Near Detector. This detector system is required in order for DUNE to reach its full physics potential in the measurement of CP violation and in delivering precision measurements of oscillation parameters. In addition to its critical role in the long-baseline oscillation program, ND-GAr will extend the overall physics program of DUNE. The LBNF high-intensity proton beam will provide a large flux of neutrinos that is sampled by ND-GAr, enabling DUNE to discover new particles and search for new interactions and symmetries beyond those predicted in the Standard Model.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A Gaseous Argon-Based Near Detector for DUNE [Slides]

DUNE is the Deep Underground Neutrino Experiment. It is a comprehensive physics program whose focus is to search for the leptonic CP violation, determine mass ordering, precise measurements of neutrino mixing parameters, BSM searches, baryon number violation, and supernova neutrino observation. This presentation focus is on the argon-based near detector complex at DUNE.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Measurement of Argon-37 Background Concentrations in the Atmosphere

Radioisotopes of noble gases, primarily xenon and argon, are important indicators of underground nuclear explosions. The Comprehensive Nuclear-Test-Ban Treaty (CTBT) includes monitoring capabilities to identify potential nuclear explosions conducted in violation of the CTBT. This monitoring currently focuses on measurement of the xenon isotopes 133 Xe, 135 Xe, 131 mXe and 133 mXe. However, it is predicted that within 100 days of an underground nuclear explosion (UNE) 37 Ar would be released to the atmosphere at higher concentrations than xenon isotopes (Haas et al. 2010). Therefore, inclusion of 37 Ar measurement capabilities at atmospheric International Monitoring System (IMS) stations could improve the capability to detect a nuclear explosion. At an IMS station, it could be difficult to determine what constitutes an elevated concentration as a result of an UNE without first understanding the expected range of background concentrations. This work describes our analysis of atmospheric samples for 37 Ar to evaluate the range of background concentrations. The range of 37 Ar concentrations measured in atmospheric air samples was relatively narrow ranging between less than 1 mBq/m 3 to greater than 2 mBq/m 3 . The average atmospheric concentration of all samples was 0.98 mBq/m 3 , with a standard deviation of 0.5 mBq/m 3 . This is consistent with previous published results. The results presented here demonstrate the capability to detect background concentrations of 37 Ar in atmospheric air.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Report on Initial Tribological Studies of Graphite in Dry Argon and Molten Salt Environment

This report documents completion of the Advanced Reactor Technologies (ART) Level 2 Milestone M2TG-24OR0501081: “Complete report on initial tribological studies within molten salt environment”, due January 31, 2024. This milestone is a carryover milestone from FY23 M2TG-23OR0501091. The report summarizes the initial studies on tribological characterization of the graphite–graphite sliding interface in a dry argon and molten FLiNaK salt environment. The experiments were conducted on a high-temperature multifunctional tribometer placed in a glovebox. This configuration enables probing the wear and friction properties at high temperatures in an inert environment. The worn surfaces were analyzed using high-resolution microscopy and white-light profilometry to determine the wear modes and wear rates. This report discusses the previous wear and friction studies on 316H stainless steel (SS) sliding against graphite in molten salt for different temperatures, sliding speeds, and salt amount. Moreover, key tribological parameters of pebble-on-pebble interaction in gas-cooled and molten salt reactors (MSRs) are analyzed and used to design an experimental test matrix for future studies. The outcomes of this project could provide key information about the tribological behavior of graphite pebbles in gas-cooled and MSRs, thereby contributing to safer operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Experimental Neutrino Physics Research with Liquid Argon TPCs (Final Technical Report)

In this report, we present the accomplishments, products, impact, and outcomes of the project funded by the DOE award DE-SC0024095. The research accomplishments are making important contributions to achieving the physics goals, demonstrating the robustness and potential of software-level event reconstruction algorithms, and ensuring high-quality detector operation for relevant US accelerator neutrino experiments using liquid argon time projection chamber technology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First Demonstration of a Liquid Argon Time Projection Chamber Based Search for Intranuclear Neutron-Antineutron Transitions and Annihilation in $^{40}$Ar using the MicroBooNE Detector

We present a novel methodology to search for intranuclear neutron-antineutron transition ($n\rightarrow\bar{n}$) followed by $\bar{n}$-nucleon annihilation within an $^{40}$Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of $n\rightarrow\bar{n}$ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select $n\rightarrow\bar{n}$ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22$\pm$6.04)\% and (0.0020$\pm$0.0003)\%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of $3.32 \times10^{26}\,$neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the $n\rightarrow\bar{n}$ lifetime in $^{40}$Ar of $\tau_{\textrm{m}} \gtrsim 1.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Methodology of the Extraction of Multi-Differential Cross Sections of Charged-Current $\nu_\mu$-Argon Interactions in MicroBooNE Using Wire-Cell $\nu_\mu$CC Selection

Neutrino physics experiments rely on accurate nuclear-interaction models that are in part guided by experimental observations. Multi-differential cross section measurements are particularly valuable for exploring the underlying physics described in these models, making them a significant step forward in the field. This note presents methodology in preparation to unfold neutrino flux-averaged double and triple-differential cross sections of the inclusive muon neutrino charged-current interaction on Argon. This work builds upon the existing framework and methodology presented in recent energy dependent cross section measurements at MicroBooNE using the Wire-Cell tomographic event reconstruction. The signal definition, choice of binning, and handling of estimated detector uncertainties are discussed, and the MicroBooNE simulation model is validated over the multi-dimensional phase space of muon momentum, muon polar angle, and visible hadronic energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Progress Toward the First Search for Bound Neutron Oscillation into Antineutron in a Liquid Argon TPC

This note presents current progress for a neutron-antineutron oscillation ($n–\overline{n}$) search in MicroBooNE paving the way for the first search analysis of such process in a Liquid Argon Time Projection Chamber (LArTPC). Convolutional Neural Network (CNN) and Boosted Decision Tree (BDT) algorithms were used to select signal $n–\overline{n}$ events over cosmogenic backgrounds. The CNN-only, BDT-only, and the combined (CNN+BDT) methods were demonstrated on the Monte-Carlo signal and background events. Validation of the CNNonly and the BDT-only methods was carried out on a small dataset of MicroBooNE Run1 off-beam data, setting the starting point toward further improvement of the analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Reconstructing 3D Charge Depositions in the MicroBooNE Liquid Argon Time Projection Chamber using Convolutional Neural Networks

We have developed a convolutional neural network (CNN) that reconstructs the three dimensional location of ionization produced by charge particles traversing a wire-readout liquid argon time projection chamber (LArTPC) at MicroBooNE. This method is the first CNN application to reconstruct 3D space points directly from two dimensional images of the different wire plane views. I.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A First Search for Argon-Bound Neutron-Antineutron Oscillation using the MicroBooNE LArTPC

The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n ₋ n̄) oscillation. The n ₋ n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n ₋ n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n ₋ n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A first search for argon-bound neutron-antineutron oscillation using the MicroBooNE LArTPC

The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n – n̄) oscillation. The n – n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n – n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n – n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Neutron Detection in the DUNE liquid argon near Detector

DUNE is a next-generation long baseline neutrino experiment [1] to perform precision measurements of neutrino oscillations. The Liquid Argon Time Projection Chamber (LArTPC) of the DUNE near detector (ND-LAr) characterizes the beam before oscillations occur and is essential to constrain the systematic uncertainties of most DUNE measurements. ND-LAr will be a modular LArTPC with pixelated charge and high-coverage light readout system

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Intelligent Triggers for Rare Event Detection in Liquid Argon Detectors

Next-generation neutrino experiments like SBND and DUNE rely on Liquid Argon Time Projection Chambers (LArTPCs), which produce exceptionally detailed data at high volume. Capturing rare or unexpected events in real-time is a major challenge. Our project explores the use of machine learning, specifically autoencoder-based anomaly detection, to identify unusual activity directly from raw detector signals. Inspired by successes at the CMS experiment, we demonstrate that such methods can be adapted to LArTPCs and show promising results in both simulated studies and early steps toward real-time hardware deployment. This approach could open new avenues for detecting signals from physics beyond the Standard Model.

Chung, Seokju [Columbia U. (main)]↗
DOE OSTI2025

Electromagnetic shower reconstruction in the ICARUS liquid argon time projection chamber detector

The ICARUS-T600 liquid argon time projection chamber (LArTPC) detector is taking data at shallow depth as the far detector of the Short Baseline Neutrino (SBN) program at Fermilab, to search for a possible sterile neutrino signal at $\Delta m^{2} \approx 1~\text{eV}^{2}$ with the Booster (BNB) and Main Injector (NuMI) neutrino beams at $\GeV{\sim 0.8}$ and $\GeV{\sim 2}$ average energies respectively. The LArTPC technology, developed by the ICARUS collaboration and now a standard in neutrino physics, offers impressive charged-particle imaging capabilities with $\sim1 \ \text{mm}$ spatial resolution, enabling efficient discrimination between track-like signatures (e.g., from muons, pions, and protons) and electromagnetic showers (from electrons and photons). Moreover, electron and photon signatures can be distinguished both with the calorimetric measurement of local energy depositions at the shower start and with the cm-scale conversion gap signature of photons. This contribution discusses event reconstruction at ICARUS focusing on Pandora, a multi-algorithm pattern recognition software widely used in LArTPC experiments. Over a hundred Pandora algorithms and tools are used to reconstruct cosmic rays and neutrino interactions in the ICARUS detector. Recent developments have focused on the reconstruction of electromagnetic shower signatures, crucial to ensure a robust and efficient reconstruction of charged-current $\nu_e$ interactions, which serve as a key signature of sterile neutrino oscillations at SBN. In this contribution, recent improvements to the reconstruction are discussed, focusing on the discrimination between tracks and electromagnetic showers using neutrino simulations and data.

Triozzi, Riccardo [Padua U.; INFN, Padua] (ORCID:0↗
DOE OSTI2025

Investigating One- and Two-Body Interference Terms in Neutrino Argon Interactions with ACHILLES at LArTPCs

Due to the complex nature of heavy nuclei, uncertainties in the prediction of neutrino-nucleus cross-sections contribute significantly to the systematic limitations of neutrino oscillation experiments. Current neutrino detectors are dedicating significant effort to measuring these cross-sections in order to improve the sensitivities of next-generation experiments. To extract translatable scattering parameters that can be applied between detector media and beam energies, these measurements must be supported by robust theoretical modelling. ACHILLES is a recent theory-driven lepton-nucleus scattering generator that aims to be easily extensible, while also providing modern accurate theory predictions. This talk will discuss the application of ACHILLES to derive experimental observables for the investigation of interference between one- and two-body scattering processes in neutrino-nucleus interactions. We will show studies primarily using the Booster Neutrino Beam (BNB) flux in the context of the SBND experiment, which is collecting world-leading statistics for neutrino argon scattering, utilising its PRISM capabilities.

Paton, Josephine L. [Fermilab]↗
DOE OSTI2025

Analysis of scintillation light dependence on liquid Argon purity

Previous studies have investigated the correlation between impurity concentrations in Liquid Argon (LAr) and the temporal evolution of either the slow scintillation decay time or the light yield. These impurities typically consist of various molecular species. Electronegative contaminants directly affect electron drift and photon production, while other molecules, such as nitrogen (N_2),can influence LAr scintillation properties without necessarily affecting electron lifetime. Many current and future neutrino and dark-matter experiments use LAr detectors. This study aims to evaluate the measured electron lifetimes in relation to the timing characteristics of the scintillation light signal in the SBN ICARUS detector at Fermi National Accelerator Laboratory. The ICARUS experiment consists of two cryostats that have shown some discrepancies in the measured electron lifetime over the years. In particular, this study addresses the use of data collected under varying purity conditions in the two cryostats.

Saia, Clara [Catania Astrophys. Observ.]↗
DOE OSTI2025

New Bismuth-Source Liquid Argon Purity Monitor and Its Operation in the ProtoDUNE Vertical Drift TPC

• LArTPCs offer excellent spatial and calorimetric resolution for neutrino physics, but require ultra-pure liquid argon to preserve ionization electrons. • Signal loss arises from recombination (∼ 1/3 at 500 V/cm) and capture by electronegative impurities; electron lifetime τe must be long (≳ 10 ms) to limit attenuation (∼ 6% per meter drift). • Continuous purity monitoring is vital for stable operation. • A 207Bi source provides mono-energetic IC electrons and a defined Compton edge, enabling precise, continuous, and non-intrusive τe measurements over a wide range.

Baibussinov, B. [INFN, Padua]↗