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DOE OSTI2022

Slag Degassing for Electroslag Remelting Using Cold Start

The effect of slag degassing prior to cold start electroslag remelting (ESR) was investigated using various heat treatments of a commercial 40CaF2 – 30CaO – 30Al2O3 slag. The slag was either degassed in a vacuum heat treatment furnace or in a box furnace in air. Vacuum heat treatment included partial pressure of Ar gas. Several temperatures, ramp rates and/or holding times were investigated for each condition and the pressure was monitored for the heat treatment in the furnace with controlled atmosphere. A research scale 200 kg capacity ESR furnace was used for the experiments along with 1018 steel and 316 stainless steel electrodes. Significant differences in ingot quality were related to the sidewall and the presence of pores which were primarily located near the bottom of the ingot. Adjustments in the heat treatment temperature for heat treatment in air eventually led to an ingot quality near that obtained using slag degassed under vacuum and/or in a controlled atmosphere.

Detrois, Martin↗

DOE OSTI2022

Search for NuMI $\mu$DAR Electron Neutrinos in MicroBooNE

Muon Decay-at-Rest ($\mu$DAR) produces electron-neutrinos ($\nu_e$) in the $0$ to $53$ MeV energy range. The given range is especially interesting for its similarity to Supernovae-produced $\nu_e$. The Deep Underground Neutrino Experiment (DUNE) has as one of its main goals to measure Supernovae neutrinos on the occasion of a Galactic Supernova burst. To optimize the chances of detection, a low-energy neutrino-LAr cross-section (XS) measurement is a piece of important information to have at hand. MicroBooNE presents a good opportunity to explore the low-energy $\nu$-LAr detection and XS using the $\mu$DAR neutrinos and therefore develop the tools necessary for DUNE to in is a LArTPC that has been collecting neutrino data since October 2015 from the Booster Neutrino Beam (BNB) and off-axis to the Neutrinos at the Main Injector (NuMI) beam, both copious sources of $\mu$DAR neutrinos. esis, we present a first attempt to measure MeV-scale neutrinos in a LArTPC. To do that, we use specifi c MeV-scale reconstruction tools combined with other traditional reconstruction tools used in MicroBooNE. We discuss the tool's performance, limitations, and provide suggestions on how to improve them. zes looks for $\mu$DAR neutrino- argon charged current interactions in the NuMI Run1 data, that contains $2\times 10^{20}$ POT. We observed $9,176$ signal candidates. The number of expected background events is $8,776$, the majority from cosmic rays. We establish a XS upper limit of $<\sigma> = 1.99\times10^{-37} \textrm{cm}^2 / \textrm{Ar}$, which corresponds to $551.9$ times the nominal prediction from MARLEY, the neutrino generator used in this work. Despite the lack of sensitivity, this work is the first of its kind and sets the foundation for future similar analysis in the future. In the conclusions, we discuss how this results can be further improved in MicroBooNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Electroweak interactions in Nucleons and Nuclei

The neutrino oscillation experiments are being performed using detectors having moderate to heavy nuclear targets like $^{12}{C}$, $^{16}{O}$, $^{40}{Ar}$, $^{56}{Fe}$, $^{208}{Pb}$, etc. to get a reasonably good number of events. Many present-day neutrino experiments are taking data in the few GeV (1 $\leq$ E$_{\nu}$ $\leq$ 10 GeV) energy region of neutrinos and antineutrinos to which some of the neutrino oscillation parameters are sensitive and required to understand CP violation in the lepton sector. This is the energy region which is most intriguing as it receives the contribution from the Quasielastic Scattering~(QE), Inelastic Scattering(IE), Shallow Inelastic Scattering (SIS) and the Deep Inelastic Scattering~(DIS) processes. This thesis details three different studies: \begin{itemize} \item First, a DIS study was performed with the MINERvA experiment at the Fermilab. MINERvA is a dedicated neutrino and antineutrino cross-section measurement experiment and uses (anti)neutrino beams in the two energy runs {\it viz.} the low energy run~(the peak of which lies $\sim$ 3 GeV) and the medium energy run(the peak lies at $\sim$ 6 GeV). The MINERvA experiment is using several nuclear targets like $^{4}$He, $^{12}$C, $^{16}$O, $^{56}$Fe and $^{208}$Pb and the aim is to perform EMC~(European Muon Collaboration experiment using charged lepton beam on several nuclear targets) kind of measurements to understand the nuclear medium effects in both the neutrino and antineutrino modes in the wide region of Bjorken scaling variable $x$, and the four-momentum transfer squared $Q^2$, covering the quasielastic, inelastic, and the deep inelastic scattering regions. In the medium energy region, it is expected that more than 30\% of the events would arise due to DIS processes. \item Second part of the thesis includes the analysis of the proposed India-based Neutrino Observatory(INO) atmospheric neutrino experiment. This work is dedicated to studying atmospheric neutrino and ant ineutrino oscillation parameters in the INO experiment. We present the ICAL sensitivity to confirm a non-zero value of the difference in atmospheric mass squared of neutrinos and anti-neutrinos i.e. ($|\Delta m^{2}_{32}|$-$|\Delta\overline{m^{2}}_{32}|$). \item Third, the theoretical work that was performed at the Aligarh Muslim University. This work has been performed keeping in mind the theoretical development of a model that will describe the associated particle production induced by photons, electrons, neutrinos, and antineutrinos. We have studied the associated particle production induced by photons which receive the contributions from the non-resonant terms and from the nucleon, hyperon, and kaon resonances. \end{itemize}

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Polyaromatic electrolytes for alkaline membrane fuel cells

A polyaromatic electrolyte for a fuel cell electrode includes a structure represented by Formula 1, wherein in Formula 1, Ar is a neutral unit represented by one of Formula 2A and Formula 2B: The fuel cell electrode may include a catalyst suspended in the polyaromatic electrolyte.

Park, Eun Joo↗

DOE OSTI2023

The Future of Visualization Technology Vis in Practice

Two decades ago, we witnessed an inflection point as graphics programming became commoditized. A comparable inflection point may be on the horizon, this time driven by the commoditization of immersive display technology with Augmented Reality (AR), Virtual Reality (VR), and Extended Reality (XR) technologies poised to redefine our interaction with data, environments, and collaboration. To drive the technology and its application, we should consider the lessons learned from successful large-scale immersive installations. Where these installations have thrived is by enhancing traditional workflows rather than entirely replacing them, supporting improved judgments of complex spaces, direct interaction in 3D, and embedding high-dimensional data.

AR/VR↗

DOE OSTI2024

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗

DOE OSTI2024

Non-LWR Regulatory Framework Modernization

This report provides an end-of-year summary that reflects the progress and status of Idaho National Laboratory’s (INL) activities concerning the development of advanced reactor (AR) regulatory framework and its implementation in the United States (U.S.). The report also provides recommendations for work to be performed in Fiscal Year 2025 (FY-25) and beyond. This work was completed in Fiscal Year 2024 (FY-24) and was supported by the U.S. Department of Energy (DOE) Regulatory Development sub-program. These activities are managed by INL on behalf of DOE.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Situated Visualization of Photovoltaic Module Performance for Workforce Development: Preprint

The rapid growth of the solar energy industry requires advanced educational tools to train the next generation of engineers and technicians. We present a novel system for situated visualization of photovoltaic (PV) module performance, leveraging a combination of PV simulation, sun-sky position, and head-mounted augmented reality (AR). Our system is guided by four principles of development: simplicity, adaptability, collaboration, and maintainability, realized in six components. Users interactively manipulate a physical module's orientation and shading referents with immediate feedback on the module's performance.

augmented reality↗

DOE OSTI2024

Situated Visualization of Photovoltaic Module Performance for Workforce Development

augmented reality↗

DOE OSTI2024

The NuMI Flux Prediction at ICARUS

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment seeking to probe fundamental symmetries within the structure of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix, and perform precision measurements its parameters including the neutrino mass ordering via the sign of $\Delta m^2_{31}$, and the charge-parity violating phase, $\delta_{CP}$. To make these measurements with high precision, DUNE will require external $\nu$-Ar scattering cross section data as a crucial input to the oscillation fit. Imaging Cosmic And Rare Underground Signals (ICARUS) is a 476 t liquid argon neutrino detector located at Fermi National Accelerator Laboratory (FNAL) where it is serving as the far detector for the Short-Baseline Neutrino (SBN) program along the Booster Neutrino Beam (BNB) axis. ICARUS additionally lies 795 m downstream and 100.1 mrad off-axis of the Neutrinos at the Main Injector (NuMI) neutrino beam. From this position, ICARUS is exposed to a large flux of NuMI (anti-)electron and (anti-)muon neutrinos, and poses a unique opportunity to provide high-statistics measurements of quasi-elastic and single pion-production cross sections for four neutrino flavors ($\nu_{\mu}$, $\nu_{e}$, $\bar{\nu}_{\mu}$, $\bar{\nu}_{e}$). This dissertation is centered around accurately characterizing the models and estimating their precision for use in making these measurements. This includes identifying major sources of uncertainty in the models such that they can be properly propagated to the cross section measurements. Specifically, this work focused on the model of the NuMI beamline and its impact on the neutrino fluxes, but also delved into the detector response model and its impact on reconstructed observables in the detector. Significant efforts were made to improve the characterization to enhance precision and thus reduce the level of propagated uncertainty. In particular, the NuMI flux was determined to be composed of 57% $\nu_{\mu}$, 38% $\bar{\nu}_{\mu}$, 3% $\nu_{e}$, and 2% $\bar{\nu}_{e}$ while the horns are operating in the positive-particle focusing configuration. The total uncertainty on the $\nu_{\mu} + \bar{\nu}_{\mu}$ ($\nu_{e} + \bar{\nu}_{e}$) flux while operating in the forward horn operating mode was determined to be 10.84% (9.04%). Compared to the on-axis flux, mesons that eventually decay to neutrinos more frequently reinteract within the NuMI structure, resulting in elevated uncertainty as these processes are not well-constrained by existing hadron interaction cross section measurements. Covariance matrices were calculated to propagate the flux uncertainty characterization to NuMI analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

The ICEBERG Test Stand for DUNE Cold Electronics Development

ICEBERG is a liquid argon time projection chamber at Fermilab for the purpose of testing detector components and software for the Deep Underground Neutrino Experiment (DUNE). The detector features a 1.15m x 1m anode plane following the specifications of the DUNE horizontal drift far detector and a newly installed X-ARAPUCA photodetector. The status of ICEBERG is reported along with analysis of noise, pulser, and cosmic ray data from the ninth run beginning May 2024 with the goal of advising the DUNE collaboration on the optimal wire readout electronics configuration. In addition, development of an absolute energy scale calibration method is currently underway using known sources such as cosmic ray muon Michel electrons at the ~10 MeV scale and $^{39}$Ar decay electrons at the ~100keV scale. Research into AI-based identification of such events at the data acquisition level is introduced.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Open Architecture for Cost Savings in Advanced Nuclear Reactors

Recently, nuclear power plant build projects in the West have run over budget due to high capital costs and schedule overruns. Compared to other sources of energy, nuclear power plants have higher capital costs. Reactors are often different at every site, resulting in a lack of standardization. Nuclear is expected to compete with other low carbon sources of energy which have lower capital costs making it essential for nuclear to develop ways of reducing costs. Strategies such as standardization, learning rates, modularization, and schedule reduction in advanced reactors can reduce nuclear costs by about 40%. Standardization as a way of cutting capital costs has been explored even in large nuclear power plants. Standardization of certain plant components can result in lower component and installation costs and higher learning from experience. Standardization can be achieved by adopting a criterion of key performance indicators and general design principles for a specific system or component such as the balance of plant. Modularization allows the construction of certain components of SMRs in a factory, which saves time, increases productivity, and encourages higher learning rates. Production learning decreases the time and the cost related to an activity. The potential for modularized components of advanced reactors to be manufactured in factories makes it conducive to achieving higher learning rates. Developing large-capacity nuclear programs through sequential builds cultivates a higher learning rate, which in effect may reduce schedule overruns. Open architecture has been identified as a way to drive standardization among advanced reactor designs and result in cost savings. Open architecture (OA) is defined as a design enabling a diverse supply chain by defining and publishing requirements of systems or equipment in functional and/or interface terms, utilizing technical standards in widespread use. Currently, the nuclear industry’s approach is to use closed architecture, making most designs proprietary. However, collaboration between various advanced reactor vendors and suppliers utilizing the concept of open architecture can result in modular and standardized architecture of subsystems or subcomponents of a nuclear power plant. Completely standardizing nuclear power plants may be impossible, however, certain common subsystems amongst the various reactor designs could be standardized and/or access a wider supply chain and leverage existing learning from other sectors. Open architecture will save time and allocate resources to the parts of the plants that have the most unique features. A key advantage of open architecture is its ability to improve production learning across advanced reactors (AR) types in the industry, by providing and utilizing the same kind of component. Sodium fast reactor (SFR), High Temperature Gas Reactor (HTGR) and Molten Salt Reactor (MSR) are the advanced reactors considered for this project. This paper aims to determine the cost savings in advanced reactor programs due to open architecture learning rate. This work is an extension of work done on light water reactor small modular reactors; the cost methodology was utilized to investigate the impact of open architecture on advanced reactors with a particular focus on sodium fast reactors. The cost data on sodium fast reactors used in the model presented the most adequate information required for the analysis.

Advanced Nuclear Reactors↗

DOE OSTI2025

Muon momentum reconstruction in ICARUS-T600 LArTPC via Multiple Scattering

The SBN program at Fermilab investigates the possible existence of eV-scale sterile neutrinos. This work focuses on reconstructing muon momentum in $\nu$-Ar interactions within the ICARUS-T600 LArTPC detector using Multiple Coulomb Scattering (MCS), the only viable method for non-contained muons. Two algorithms are evaluated: the Gran Sasso algorithm (2D, Collection view) and the MicroBooNE algorithm (3D angles), applied to 2391 simulated and 2255 real stopping muon tracks (0.4-1 GeV/c). Performance is assessed via bias and resolution, using range-based momentum as a reference. Two enhanced versions of the Gran Sasso algorithm are also developed: one combining all three wire plane views, and one using 3D angles. Results show that the MicroBooNE algorithm performs slightly better, with resolution down to 14\% in simulation and 16\% in real data. These improvements significantly boost $\nu_\mu$ CC statistics, enhancing sensitivity to $\nu_\mu$ disappearance and 3+1 oscillation signals.

Chiello, Giovanni [Pisa U.] (ORCID:000900064571071↗

DOE OSTI2025

A Machine Learning Approach for Hourly Traffic Prediction Used in EV-Charging Sites

Reliable forecasting of hourly traffic volumes on highways is critical for planning and operating electric-vehicle charging infrastructure without overloading the grid. In this work, we develop and evaluate a station-specific machine-learning approach based on NeuralProphet, enhanced with conditional seasonality to better distinguish weekday, weekend, and holiday patterns. For each station, the model automatically retrieves the same calendar day from the prior years as an AR-Net initialization, fits trend and Fourier-based seasonality components, and then applies short-term auto-regressive corrections. We train and test on 2021 and 2022 TMAS data, respectively, and validate performance over the whole year. We chose to demonstrate how the model performs on a typical weekday (3/15/2022), weekend (3/27/2022), and a special holiday (12/25/2022). Our results yield MAPE of 7.4%, 23.6%, and 32.0%, respectively. Over the entire year 2022, the overall MAPE was 17%. This demonstrates that station-specific models with conditional seasonality can achieve accurate, scalable hourly forecasts for EV-charging load planning.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Standard Candles for Supernova Neutrino Detection at DUNE

The Deep Underground Neutrino Experiment (DUNE) far detector is sensitive to $\mathcal{O}(10)$ MeV electron neutrinos through $ν_e$ charged-current reaction with argon. This capability is a unique window into the $ν_e$ component of a Galactic core-collapse supernova flux. Extracting the properties of the supernova spectrum is, however, limited by the poorly-known $ν_e$-Ar cross section. We propose a data-driven strategy that leverages $^8$B solar neutrinos and muon-decay-at-rest neutrinos as standard candles for this process. These calibration samples constrain both the low-energy and high-energy components of the cross section relevant for supernova detection. Our method reduces the reliance on nuclear models, which can bias the extraction of the spectral parameters by as much as 300$\%$.

Cheng, Ting [Fermilab]↗

DOE OSTI2026

First Measurement of Sub-GeV $ν_μ$ Charged-Current Coherent Pion Production on Argon in MicroBooNE

We report a measurement of the charged-current coherent pion production cross section on argon using the MicroBooNE liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. The measurement uses the MicroBooNE data set corresponding to $1.26 \times 10^{21}$ protons on target with a mean neutrino energy of $0.8$~GeV. The flux-averaged cross section is measured to be $(9.1 \pm 1.2_{\text{stat}} \pm 1.2_\text{syst}) \times 10^{-40}\,\text{cm}^2/\text{Ar}$. This result represents the first measurement of charged-current coherent pion production on argon at sub-GeV neutrino energies. Due to its clean two-body kinematics, where the neutrino interacts coherently with the entire nucleus producing a forward muon and pion with no nuclear breakup, this process provides a useful tool for constraining neutrino flux uncertainties in current and future oscillation experiments such as DUNE.

Abratenko, P. [Tufts U.] (ORCID:0000000169455941)↗

DOE OSTI2025

Large negative magnetoresistance in antiferromagnetic G⁡d 2 ⁢S⁢e 3

Rare earth chalcogenides provide a great platform to study exotic quantum phenomena such as superconductivity and charge density waves. Among various interesting properties, the coupling between magnetism and electronic transport has attracted significant attention. Here, we report the investigation of such coupling in α-G⁡d 2⁢ S⁢e 3 single crystals through magnetic, calorimetric, and transport property measurements. α-G⁡d 2 ⁢S⁢e 3 is found to display an antiferromagnetic ground state below 11 K with metamagnetic spin-flop transitions. The magnetic fluctuations remain strong above the transition temperature. Transport measurements reveal an overall metallic transport behavior with a large negative magnetoresistance of approximately 65% near the magnetic transition temperature, together with positive magnetoresistance near the field-induced spin-flop transitions, which can be understood in terms of the suppression of spin scattering by the magnetic field.

electrical properties↗

DOE OSTI2026

Strain Relaxation and Relative Defect Density with Thickness in MBE-Grown Ge 0.85 Sn 0.15 on Ge(001)

Germanium–tin (GeSn) alloys are emerging as promising materials for mid-infrared optoelectronics and silicon-compatible photonic devices, owing to their tunable direct bandgap. However, the growth of high-quality GeSn films with high Sn content remains challenging due to strain-induced defect formation. In this study, we investigate the role of film thickness on strain-induced relaxation, defect density, and Sn segregation. A series of five samples with varying thicknesses and ∼15% Sn-containing GeSn layers were grown, ranging from the critical thickness for strain relaxation to the onset of Sn segregation. All GeSn samples were analyzed using X-ray diffraction reciprocal space mapping (XRD-RSM) to explore the evolution of strain-induced relaxation as a function of thickness. Photoluminescence measurements reveal that increasing the GeSn thickness enhances strain relaxation while reducing defect-related emission, indicating a decrease in effective defect density prior to reaching the threshold thickness of GeSn layer. At a thickness of ∼150 nm, the GeSn layer shows the onset of Sn segregation, evident in the XRD-RSM spectrum, marking the threshold thickness for Sn segregation. This work defines an effective growth window in terms of thickness (35 to 150 nm) for fabricating relaxed, defect-suppressed GeSn layers with 15% Sn content. These findings emphasize the crucial role of thickness control in balancing strain relaxation and defect suppression, advancing the fabrication of high-quality, high Sn-content relaxed GeSn using molecular beam epitaxy.

Defects↗