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DOE OSTI2025

Finding Nuclear Clusters in the Short-Baseline Near Detector

Production of nuclear clusters such as deuterons, tritons, helions and alpha particles has only recently been simulated for neutrino-nucleus interactions, and has not yet been measured in neutrino experiments. The Short-Baseline Near Detector (SBND) is the first Liquid Argon Time Projection Chamber (LArTPC) with high enough resolution and a large enough neutrino flux to accurately measure the cross-section for the production of heavier-than-proton fragments in neutrino interactions. SBND is a 112-ton LArTPC, and lies 110 m downstream from the Booster Neutrino Beam target, where it has already collected the world's largest dataset of neutrino-argon interactions. In these processes, the intranuclear cascade and nuclear de-excitation stages can both produce nuclear clusters. With LArTPC technology's excellent reconstruction capabilities and SBND's unprecedented neutrino statistics, a measurement of these nuclear clusters could distinguish between nuclear models and improve neutrino energy reconstruction. This poster presents the status of simulation, reconstruction, and prospects for a measurement of nuclear clusters in SBND.

Beever, Anna [Sheffield U.] (ORCID:000900069339924↗

DOE OSTI2025

A New Route to Improve the Material Quality of Nb3Sn with Zr Inclusion

Nb3Sn superconducting material promises significant potential to exceed the performance of niobium based superconducting radio frequency (SRF) accelerator cavities. With the aim of advancing the ongoing R&D efforts in improving the material quality of Nb3Sn SRF cavities, we studied how the inclusion of Zr in Nb3Sn matrix via co-sputtering process effects the microscopic structure and superconducting properties. Our results suggest co-sputtered Nb3SnZr alloy as a new prospective material platform to further advance the performance limits of SRF cavities.

Tripathi, Malvika [Fermilab]↗

DOE OSTI2026

A Dedicated Muon EDM Experiment in the `g-2 Storage Ring

Spin precession experiments offer exciting motivations to search for new physics. We propose here an idea of using a modified version of the Muon g-2 storage ring for a potential new scientific program to search for a non-zero muon electric dipole moment (EDM). Using both electric and magnetic dipole fields to produce a "frozen spin" condition for the MDM (all the while enhancing the EDM spin precession), the storage ring would operate at a lower central muon momentum than for the present Muon g-2 measurement. The incident proton beam on target for the muon production can be obtained from the PIP-II high intensity proton beam. Preliminary calculations and simulation results of muon production at 800 MeV PoT, along with the determination of the closed orbit inside the hybrid 'g-2' storage ring configuration, shall be presented. Possibilities of using the 'g-2' storage ring as a test bench to demonstrate the freezing of the MDM spin precession shall be discussed. The operational range of the muon's momentum and energy, and their respective window of electric and magnetic field values to establish the frozen spin condition, shall be presented. We shall also briefly discuss the physics prospects and improvements in muon EDM bounds upon using Fermilab's PIP-II beam.

Narayanan, Aakaash [Fermilab] (ORCID:0000000157944↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

The Short-Baseline Near Detector (SBND) is one of the Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and is the near detector in the Short-Baseline Neutrino (SBN) Program. The detector has completed Run 1, successfully recording approximately 3 million neutrino interactions, and started Run 2 in the autumn of 2025. SBND is characterized by superb imaging capabilities and will record around 3 million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will soon carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). As the near detector, it will enable the full potential of the SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate and constraining the BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

Del Tutto, Marco [Fermilab]↗

DOE OSTI2026

Overview of NLR Automated Mobility District Implementation Research - Phases I, II, and III. The Convergence of Automation, Electrification, and On-Demand Services: Enabling Resilient Automated Mobility Districts

A research program by the National Renewable Energy Laboratory has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings, referred to as Automated Mobility Districts (AMDs). An AMD emphasizes the deployment of automated vehicles (AV) passenger transport services within a dense urban setting and other major activity centers with intense passenger origin-destination demand patterns, such as those found in large business districts, airports, and university and medical campuses. Phase I and II surveyed 10 early deployment sites and subsequently collected and evaluated the lessons learned from these early deployment sites, with particular attention to fleet operations, impacts of service reliability, and vehicle technology evolution as the field of companies was being progressively winnowed by the challenges of full automation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

A Dedicated Muon EDM Experiment in the `g-2 Storage Ring

Narayanan, Aakaash [Fermilab] (ORCID:0000000157944↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

Del Tutto, Marco [Fermilab]↗

DOE OSTI2022

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Needs Assessment Framework for Storage Complexes Contributed to EDX (Work Product 2.1.c)

On September 30, 2021, a Needs Assessment Framework for Storage Complexes was completed for the SECARB-USA region by the Southern States Energy Board (SSEB) and The University of Texas at Austin Bureau of Economic Geology (UT-BEG). The Needs Assessment Framework for Storage Complexes documented a region-wide assessment to identify data needed to advance storage projects at sites of relevance to industrial, academic, and government stakeholders. The region-wide assessment addresses the needs of CO2 source, storage, and utilization stakeholders, finance and insurance institutions, state and local government agencies, local stakeholders at prospective storage complexes, environmental non-governmental organizations (NGOs), and others as identified by the Partners. This assessment was tested against various potential storage sites and modified to include site-specific issues, such as surface or pore space rights. The framework was provided to stakeholders for review and then used in other tasks, such as the ML initiative (Subtask 3.4) and storage complex readiness evaluation (Subtask 4.2). In accordance with the SOPO, this assessment satisfied completion of Work Product 2.1.b. The OSTI ID is 3015803, and the DOI link is https://doi.org/10.2172/3015803. On February 28, 2022, SSEB uploaded Work Product 2.1.b to NETL’s Energy Data eXchange (EDX). As such, Work Product 2.1.c is completed as documented below.

42 ENGINEERING↗

DOE OSTI2026

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Physics model enhancements in MARLEY version 2

Large next-generation neutrino detectors, such as those designed for accelerator-based oscillation experiments, are expected to have impressive sensitivity to MeV astrophysical neutrinos generated by the Sun and by supernovae. There are also numerous related prospects to search for MeV-scale phenomena beyond the Standard Model. In contrast to detectors constructed with water and hydrocarbon targets, which will be primarily sensitive to electron antineutrinos via inverse beta decay, the upcoming Deep Underground Neutrino Experiment (DUNE) will provide unparalleled capabilities to measure low-energy electron neutrinos from cosmic sources. Interpreting such future measurements in DUNE will require a high-quality simulation of MeV interaction physics in the argon nucleus. The MARLEY (Model of Argon Reaction Low Energy Yields) neutrino event generator has been designed with the goal of delivering the needed simulation capabilities for DUNE and other argon-based neutrino detectors. In this poster, I will present recent improvements to MARLEY's suite of interaction models, which will be released for general use by the neutrino community in version 2 of the software.

Gardiner, Steven James [Fermilab] (ORCID:000000028↗

DOE OSTI2026

CRADA Number NFE-24-10110 with Qubit Engineering Inc. (CRADA Final Report)

Over the past year, the Qubit Engineering team has pushed the frontiers of power‑grid optimization, working in close collaboration with Oak Ridge National Laboratory (ORNL) and the Tennessee Valley Authority (TVA). Their progress is reflected in three newly submitted conference papers, “Unified Relational GNN Architecture for AC Optimal Power Flow Calculations in Electric Grids,” “Graph‑Based Attention Mechanisms for Solving the AC Optimal Power Flow Problem in Electrical‑Power Networks,” and “Enhanced Power‑Grid Maintenance Planning and Quantum‑Inspired Combinatorial Prospects.” These publications showcase state‑of‑the‑art graph‑neural‑network methods for AC‑OPF and novel quantum‑inspired heuristics for maintenance scheduling. Beyond the academic results, the Qubit team has converted the research into two production‑grade tools built on TVA data: Neuro‑Grid, an AI‑driven power‑flow simulator that provides instant, interactive full‑grid load‑flow visualizations, and Quanta‑Grid, a quantum‑inspired maintenance‑scheduling engine to support logistics optimization for power utilities. Together, these advances demonstrate how Qubit’s partnership with ORNL and TVA is delivering practical, physics‑grounded analytics for next‑generation grid management.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Neutron-Antineutron Transition Search at DUNE

Neutron-antineutron transition is a baryon number violating process with ΔB=2, providing a unique insight into potential explanations of the baryon asymmetry in our universe, especially in the context of post-sphaleron baryogenesis. Studies have been conducted across various neutron-rich environments, including free neutron sources, neutron stars, and bound neutrons in large underground neutrino detectors, among which large neutrino experiments have historically obtained the most stringent constraints. The forthcoming Deep Underground Neutrino Experiment (DUNE) will offer especially strong prospects for this search, enabled by the high spatial resolution of its liquid argon time projection chamber. This poster presents a recent study on neutron-antineutron transition at DUNE using machine-learning based event classification.

Yu, Kaiwen [UC, Irvine (main)]↗

DOE OSTI2026

Fermilab complex upgrades and CLFV

I review the current status and future prospects of charged lepton flavor violation (CLFV) searches at Fermilab, with emphasis on their sensitivity to physics beyond the Standard Model and their complementarity to the mission-critical LBNF/DUNE neutrino program. In this context, strategic considerations for the evolution of the complex in the Linac-II era will be discussed, including synergies between CLFV initiatives and mission-critical commitments such as reliable high-power beam delivery to LBNF/DUNE.

Hedges, Michael [Fermilab] (ORCID:0000000165041872↗

DOE OSTI2026

SBND Detector Status and First Results

The Short-Baseline Near Detector (SBND) is one of three liquid argon time projection chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and serves as the near detector in the Short-Baseline Neutrino (SBN) Program. The detector just completed its second year of running, collecting over 6.5e20 POT, equivalent to an unprecedented sample of over 5 million neutrino interactions. Initial data has demonstrated superb performance of the detector’s subsystems, enabling precise tracking and calorimetric reconstruction of events. With this large statistical data set, SBND is performing multi-dimensional cross section measurements of inclusive and exclusive topologies and precise searches for beyond the Standard Model (BSM) processes. As the near detector in the SBN Program, it will enable the full potential of the joint sterile neutrino measurements program by precisely characterizing the unoscillated neutrino beam, constraining BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the current status of the experiment, first results from SBND’s neutrino interaction program, as well as status and prospects for BSM and oscillation searches are discussed.

Paton, Josephine [Fermilab] (ORCID:000000032651489↗

DOE OSTI2026

Physics model enhancements in MARLEY version 2

Large next-generation neutrino detectors, such as those designed for accelerator-based oscillation experiments, are expected to have impressive sensitivity to MeV astrophysical neutrinos generated by the Sun and by supernovae. There are also numerous related prospects to search for MeV-scale phenomena beyond the Standard Model. In contrast to detectors constructed with water and hydrocarbon targets, which will be primarily sensitive to electron antineutrinos via inverse beta decay, the upcoming Deep Underground Neutrino Experiment (DUNE) will provide unparalleled capabilities to measure low-energy electron neutrinos from cosmic sources. Interpreting such future measurements in DUNE will require a high-quality simulation of MeV interaction physics in the argon nucleus. The MARLEY (Model of Argon Reaction Low Energy Yields) neutrino event generator has been designed with the goal of delivering the needed simulation capabilities for DUNE and other argon-based neutrino detectors. In this talk, I will present recent improvements to MARLEY's physics models, which will be released for general use by the neutrino community in version 2 of the software.

Gardiner, Steven James [Fermilab] (ORCID:000000028↗

DOE OSTI2020

Status and Plan of DUNE at Fermilab

The discovery and the solid confirmation of neutrino flavor oscillation have been made throughout late 1990 to 2000s. Such oscillation is the clear proof of non-zero neutrino mass since this is caused by the fact that the neutrino mass eigenstates differ from that of the flavor. The neutrinos in the Standard Model, however, are massless leptons, and thus the neutrino flavor oscillation necessitates either the Standard Model to be significantly modified or a new theoretical paradigm to describe the universe better. In order to provide experimental information, it is essential for the properties of the neutrino oscillation be well understood through precision measurements of oscillation parameters, including the mixing angles, determination of the mass hierarchy between the three mass eigenstates and determination of the CP phase (Delta_CP) between neutrino and anti-neutrino oscillations. Among the several next generation neutrino experiments, this presentation covers the Deep Underground Neutrino Experiment (DUNE) which, with the high intensity neutrino beam facility, will help accomplish these goals. In this report, I will discuss the current status and plan of the DUNE experiment, including the results of the detector performance studies from the large scale prototype detectors operating at CERN and the timeline for construction and data taking of the experiment, as well as its physics prospects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Accessing scattering amplitudes using quantum computers

Future quantum computers may serve as a tool to access non-perturbative real-time correlation functions. In this talk, we discuss the prospects of using these to study Compton scattering for arbitrary kinematics. The restriction to a finite-volume spacetime, unavoidable in foreseeable quantum-computer simulations, must be taken into account in the formalism for extracting scattering observables. One approach is to work with a non-zero iϵ-prescription in the Fourier transform to definite momentum and then to estimate an ordered double limit, in which the spacetime volume is sent to infinity before ϵ is sent to 0. For the amplitudes and parameters considered here, we find that significant volume effects arise, making the required limit very challenging. We present a practical solution to this challenge that may allow for future determinations of deeply virtual Compton scattering amplitudes, as well as many other reactions that are presently outside the scope of standard lattice QCD calculations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Small experiment, Big Data: the data production of the Muon $g-2$ Experiment

The Muon $g-2$ Experiment at Fermilab aims to measure the muon anomalous magnetic moment with the unprecedented precision of 140 parts per billion (ppb). In April 2021 the collaboration published the first measurement, based on the first year of data taking. The result confirmed the previous experiment at Brookhaven National Laboratory (BNL), and increased the long-standing tension with the Standard Model prediction to 4.2 $\sigma$. The experiment is now running the sixth year of data acquisition of positive muon data, having accumulated a total of $\sim$19 times the statistics of the BNL experiment. A collaboration-wide effort is now in place to help produce the multi-petabyte-sized data sets, a challenge typically faced by much bigger experiments. Having a quick production turnaround time is of critical importance in order to achieve a timely analysis and publication schedule. In this paper I will describe the production workflow, the former and current challenges, the resources, tools, and the future prospects of the Muon $g-2$ Experiment.

Girotti, Paolo↗