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At least 703 records · Page 39

Size scaling of acceleration phase energetics and its effects on direct-drive DT-layered implosions

A fundamental question in inertial confinement fusion is how implosion performance, and therefore ignition thresholds and fusion gain, evolve with target size. In laser-driven direct drive fusion, the scaling of laser-drive performance with size is critical to this evolution and to extrapolating results from the 30-kJ OMEGA laser-fusion experiments to ignition-class facilities such as the National Ignition Facility. Beyond the well-known adverse effects of cross-beam energy transfer (CBET) on drive performance, here we demonstrate that effects related to the non-scaling physics of thermal conduction and electron–ion energy equilibration exert an influence on drive behavior with scale that equals or surpasses that of CBET. We find that a significant portion of the lost implosion performance with increasing scale is due to the loss of shell implosion velocity. Here, we show that while modest modifications to hydro-scaled designs can recover most of the lost implosion velocity, a full hydro-equivalent performance extrapolation is difficult to achieve without CBET mitigation or subcooling below the triple point of DT.

Patel, D. [University of Rochester, NY (United Sta↗

Advancements in Yttrium Hydride Moderator Development

As microreactors evolve to become a more affordable and efficient worldwide energy source, the development of moderator material within the system to decrease the required mass of low-enriched uranium fuel is important. The use of low- instead of high-enriched uranium in small nuclear reactors stems from recent national policies associated with nonproliferation. New designs are being developed for a range of applications and nuclear space systems in particular. Using system geometries such as those described in this paper, the next step is to advance the technology readiness level of moderator material such as delta-yttrium hydride (YH x,x = 1.6–2.0 ) so that it can be qualified for use in a microreactor system. Although characterization of unirradiated material has been documented previously, to fully understand the performance of this material, behavior in relevant irradiation environments must occur. This paper describes the fabrication of yttrium hydride samples through innovative techniques and how these samples were tested in two relevant neutron environments. These two experiments include (1) a critical experiment performed at the National Criticality Experiments Research Center (NCERC) to evaluate reactivity changes in a neutron-critical environment and (2) irradiation in the Advanced Test Reactor (ATR) to assess structural integrity/material form, thermophysical data, hydrogen permeability, and other features post irradiation. For this purpose, hundreds of samples were fabricated for the NCERC and ATR experiments and are described within this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

On the Limits of EM Based Detection of Control Logic Injection Attacks In Noisy Environments

The difficulty in applying traditional security mechanisms in Industrial Control System (ICS) environments makes a large portion of these mission-critical assets vulnerable to cyber attacks. Therefore, there is a dire need for the development of novel security mechanisms specifically designed to protect such critical systems. Recently a lot of attention has been given to mechanisms that exploit the EM emanations of devices for defense purposes. Such practices may lead to the development of robust external and non-intrusive anomaly detection systems. Nevertheless, the majority of current work in the area neglects to consider the implications of real-life environments, particularly environmental noise. In this work, we explore the limits of EM-based anomaly detection towards identifying injection attacks in control logic software in noisy environments. Our study conducted upon both synthetically generated and real signals identified that indeed environmental noise might significantly degrade the accuracy of the anomaly detection process. Experiments done upon synthetic data indicated that assuming that signals are captured with high sampling rates, even minor code injections can be detected with above-90% accuracy in noisy environments where SNR is up to -2dB. This is true even if naive detection methods are considered. Moreover, experiments done using a real-life testbed attest that even single-instruction injections can be detected with near-perfect accuracy in relatively clean environments. Finally, noise-elimination techniques can drastically improve the reliability of the detection mechanism even in noisy environments.

97 MATHEMATICS AND COMPUTING↗

Engineering high-coherence superconducting qubits

Advances in materials science and engineering have played a central role in the development of classical computers and will undoubtedly be critical in propelling the maturation of quantum information technologies. In approaches to quantum computation based on superconducting circuits, as one goes from bulk materials to functional devices, amorphous films and non-equilibrium excitations — electronic and phononic — are introduced, leading to dissipation and fluctuations that limit the computational power of state-of-the-art qubits and processors. In this Review, the major sources of decoherence in superconducting qubits are identified through an exploration of seminal qubit and resonator experiments. The proposed microscopic mechanisms associated with these imperfections are summarized, and directions for future research are discussed. The trade-offs between simple qubit primitives based on a single Josephson tunnel junction and more complex designs that use additional circuit elements, or new junction modalities, to reduce sensitivity to local noise sources are discussed, particularly in the context of materials optimization strategies for each architecture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Effect of Luminance Pattern on Nighttime Discomfort Glare Response - CRADA 653 (Abstract)

Light Emitting Diode (LED) adoption is critical for widespread energy savings from commercial outdoor lighting systems. A complaint from the public, concerns glare from LED light fixtures especially those with exposed LED arrays. This human factor study will examine luminance uniformity of the fixture aperture to identify parameters related to this response. The outcome will inform optical design by lighting manufacturers, retaining LED energy efficiency while mitigating glare. The results may also lead to improved industry standard glare metrics for lighting. Pacific Northwest National Laboratory’s (PNNL) Lighting Science and Technology Lab in Portland OR has a purpose-built apparatus with exposed LED arrays that have been used for prior work. It can easily be adapted for use in this experiment. Interchangeable templates will allow changing patterns for the stimulus. Glare ratings from the recruited subjects will be analyzed and reported in a peer-reviewed journal for application by luminaire manufacturers for improved products. The McClung Foundation’s interest is to better understand human perception of lighting, leading to more comfortable and effective visual environments. Members of the Foundation’s Technical Review Committee will be instrumental in reviewing the experimental design, analysis, and the final report. They will also help disseminate information about the results within the lighting community.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Novel, Middle and Long Wave Infrared Laser Sources For Accelerator Applications

The main accomplishment during Years 2020-2024 of the DOE Accelerator Stewardship Program is proof-of-principle demonstration of amplification of an ultrashort 10 µm seed pulse in a multiatmosphere CO 2 laser optically pumped by nanosecond pulses of either a ~4.3 µm Fe:ZnSe laser or a 2.8 µm electro-optically (EO) Q-switched Er: Laser. This has been accomplished at the UCLA Neptune Laboratory by using about 100 mJ, ~100 ns long pulses generated by the pump laser built for this purpose by the UAB team. Implementation of EO Q-switching regime in the solid-state Er:laser system made possible nanosecond synchronization between the pump pulse and the 0.5 ps seed pulse produced by a commercial Ti:sapphire laser based mid-IR OPA/DFG. The injection mode-locking regime realized in a compact Mult atmosphere 3 Hz CO 2 -He regenerative amplifier enabled generation of a train of ultrashort pulses separated by the cavity round-trip time of ~3.2 ns. The measured gain lifetime of ~1 µs at a total pressure of ~12-15 atm indicates that lifetime of the upper laser level is a critical limiting factor in designing high-pressure CO 2 amplifiers. A single picosecond 10 mm pulse with an energy 0.1-0.2 mJ was extracted from the amplifier’s cavity using an ultrafast Ge semiconductor switch whose reflectivity was photo-induced by a femtosecond 800 nm pulse. For direct amplification regime, nonlinear absorption in Ge at 10 mm at GW/cm 2 intensities limited the extracted energy. Therefore, the generated energy could be further increased by minimizing losses in the switch and optimizing the cavity mode size. Based on the obtained data in collaboration with BNL colleagues, we have designed a high-pressure CO 2 amplifier to be used as a preamplifier for the future experiments at the ATF BNL. The latter work is the subject of funding availability.

60 APPLIED LIFE SCIENCES↗

Project Update for “Designing Nuclear-data Measurements that Resolve Discrepancies in Existing Data” [Slides]

AIACHNE has made key progress this past year and will contribute to the larger scientific community. We recovered input data for the current 252 Cf(sf) PFNS evaluation that was previously lost. We render a standard to the best of our ability reproducible. We critically reviewed past data as input for ML & new standard evaluation that will impact PFNS of all major actinides. We developed a unique AI/ ML code that highlights which measurement features are related to bias and are working towards open-sourcing it for the community. Features that were identified as related to bias follow physics’ intuition and bring new understanding of exp effects and might help us for other reactions and isotopes. The results highlight that EXFOR is a goldmine of features that could help us understand experiment bias (if they are easy to parse).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The intrinsic mechanical properties of hydromagnesite, Mg 5 (CO 3 ) 4 (OH) 2 ·4H 2 O, a key phase of reactive MgO carbonate cement

To potentially enable CO 2 sequestration, reactive MgO carbonate cement is emerging as an alternative binder to Portland cement. Understanding the mechanical properties of its binding phase is critical for understanding the strength development and performing materials design for reactive MgO cement systems; however, the intrinsic mechanical properties of hydromagnesite (Mg 5 (CO 3 ) 4 (OH) 2 ·4H 2 O), a key binding phase, remain unexplored. Here the present study utilized synchrotron-based high-pressure X-ray diffraction to determine the unit cell-scale, intrinsic mechanical properties of hydromagnesite for the first time. Up to hydrostatic loading of 7.7 GPa, the bulk modulus of hydromagnesite was determined as 59 GPa or 71 GPa fitted using the second-order or third-order Birch-Murnaghan equation of state, which we contextualize with binding phases in various cement systems. The experiment results are applicable in materials design of low-carbon concrete and valuable for the validation and calibration of atomistic models.

36 MATERIALS SCIENCE↗

In situ catalyst activation and regeneration enable energy-efficient high-current CO 2 reduction to ethanol-rich C 2+ mixtures

Electrochemical conversion of dissolved CO 2 in bicarbonate electrolytes, i.e., bicarbonate electrolysis, offers distinct advantages over gas diffusion electrode systems by enabling direct utilization of the CO 2 capture electrolyte while bypassing the energy-intensive CO 2 release step. However, bicarbonate electrolysis faces challenges such as CO 2 mass-transfer limitation, local pH-driven CO 2 depletion, and high cathodic potentials. The higher potential often causes catalyst surface reorganization, leading to a gradual loss of active sites and variations in selectivity during CO 2 reduction. Here, we report a directed, in situ activation and regeneration method that allows precatalysts to equilibrate under dynamic (pulsed) electrolysis conditions. We demonstrate in situ activation of a scalable Cu 2 O/Cu mesh that, under short-width (t = 4 s) pulsed electrolysis, provides stable mixed oxidation states of Cu, favoring the formation of an ethanol-rich crude mixture. The pulsed electrolysis waveform, consisting of six distinct segments, is tuned to form Cu + oxides, which are then reduced to generate local alkaline conditions favoring C–C coupling. This synergistic effect results in FEs of 73% for C2+ products and 39% for ethanol at an applied current density of −150 mA cm −2 and a cathodic potential of −1.45 V (vs. RHE). The overall half-cell energy efficiency is ∼30% for C 2+ products. The in situ Raman experiments confirm the role of pCO 2 R in dynamically regenerating Cu+-containing surface species during pulsed operation, thereby steering selectivity towards C 2+ products. A comprehensive multiscale, multiphysics model is developed to investigate the dynamic behavior of copper surface species (Cu, Cu + , and Cu 2+ ) and local microenvironmental conditions during the pCO 2 R. The results reveal that the coexistence of different copper oxidation states, especially the Cu+ intermediate, is critical in steering selectivity towards multicarbon (C 2+ ) products. The dynamic modulation of surface redox states via tailored pulsing strategies favors C–C coupling pathways by inducing localized alkaline conditions and stabilizing reactive intermediates. This work establishes a predictive modeling platform that links pulse waveform design with mechanistic insights into catalyst state evolution and product selectivity. Overall, this study provides valuable insights into the synergistic effect of in situ activation of pre-catalysts and pulsed electrolysis for higher selectivity towards C 2+ products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

LLM Generation of Online Courses from a Curated Set of Documents in the Nuclear Safeguards Domain

A multidisciplinary team at Argonne National Laboratory explores the application of advanced technologies to enhance knowledge transfer and retention within the nuclear safeguards domain. Specifically, it examines the feasibility of leveraging secure large language models (LLMs) to streamline the creation of e-learning modules for the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Safeguards (NA-241). The initiative addresses the critical need for preserving institutional memory and accelerating skill development amidst the imminent retirement of senior professionals in the field in addition to supporting good knowledge management practices. The project integrates instructional design theory with cutting-edge AI technologies to transform curated document sets from the Safeguards Knowledge Repository (SKR) into modular online courses. By automating the generation of learning objectives and instructional content, the effort aims to reduce manual effort while maintaining high-quality educational outcomes. A limited measure of human supervision, however, ensures accuracy, relevance, and alignment with NNSA’s strategic priorities. Key findings highlight the potential of AI-assisted course generation to support safeguards professionals by creating structured, interactive learning experiences. The report underscores the importance of SME validation to address limitations in AI-generated content, such as terminology errors and gaps in coverage. Recommendations include adopting a structured workflow combining LLM acceleration with expert oversight to ensure accuracy, usability, and alignment with learner needs. This work demonstrates Argonne’s commitment to advancing national security and scientific excellence through innovative knowledge management solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Recognizing Institutions that Prepare Students for 21st Century Building Careers

Buildings play a significant role in reaching the White House's goal of a net-zero emissions economy by 2050, so it is critical that building professionals are prepared to design and construct high-efficiency, low-carbon buildings powered by renewables. The U.S. Department of Energy's Zero Energy Design Designation recognizes post-secondary academic programs that prepare students for 21st century building careers. ZEDD is a three-year designation, and as of 2023 almost 40 programs of study from more than 25 institutions have been recognized and supported by DOE for their great work. The University of Cincinnati received the ZEDD designation for the Net Zero Energy Design Track in Architectural Engineering Program. Tracks, majors, minors, and certificates are all eligible for ZEDD. In recent interviews with faculty from the University of Cincinnati and Appalachian State University about their experiences with ZEDD, many common topics came up. Both faculty members mentioned their students who graduate with ZEDD on their resume are often the only people in their future design firms who understand and can create net zero energy designs.

buildings↗

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗

Ultrafast Optical Nanoscopy of Carrier Dynamics in Silicon Nanowires

Carrier distribution and dynamics in semiconductor materials often govern their physical properties that are critical to functionalities and performance in industrial applications. The continued miniaturization of electronic and photonic devices calls for tools to probe carrier behavior in semiconductors simultaneously at the picosecond time and nanometer length scales. Here, in this paper, we report pump–probe optical nanoscopy in the visible-near-infrared spectral region to characterize the carrier dynamics in silicon nanostructures. By coupling experiments with the point-dipole model, we resolve the size-dependent photoexcited carrier lifetime in individual silicon nanowires. We further demonstrate local carrier decay time mapping in silicon nanostructures with a sub-50 nm spatial resolution. Our study enables the nanoimaging of ultrafast carrier kinetics, which will find promising applications in the future design of a broad range of electronic, photonic, and optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Factors Influencing Adoption of Pooled Rideshare An Explorative Study on User-Centered Design and Services

The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals ride alone or with people they know) initially dominated the market, the popularity of pooled ridesharing (individuals share rides with strangers) has grown globally. However, pooled rideshare remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. A national U.S. survey ( N = 5,385) used exploratory and confirmatory factor analyses to identify four key factors influencing riders’ willingness to consider pooled rideshare: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. Understanding and implementing these user-centered design principles and service-related factors may be critical for increasing the future use of pooled rideshare services

Gangadharaiah, Rakesh↗

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

Designing order–disorder transformation in high-entropy ferritic steels

Order–disorder transformations hold an essential place in chemically complex high-entropy ferritic steels (HEFSs) due to their critical technological application. The chemical inhomogeneity arising from mixing of multi-principal elements of varying chemistry can drive property altering changes at the atomic scale, in particular short-range order. Using density-functional theory-based linear-response theory, we predict the effect of compositional tuning on the order–disorder transformation in ferritic steels—focusing on Cr–Ni–Al–Ti–Fe HEFSs. We show that Ti content in Cr–Ni–Al–Ti–Fe solid solutions can be tuned to modify short-range order that changes the order–disorder path from BCC-B2 (Ti atomic-fraction = 0) to BCC-B2-L2 1 (Ti atomic-fraction > 0) consistent with existing experiments. Our study suggests that tuning degree of SRO through compositional variation can be used as an effective means to optimize phase selection in technologically useful alloys.

36 MATERIALS SCIENCE↗

Hadron-Argon Cross-Section Measurements at Protodune

The Deep Underground Neutrino Experiment (DUNE) is a next-generation experiment designed to measure neutrino oscillations with unprecedented precision, specifically seeking to identify CP violation in the lepton sector. DUNE utilizes the Liquid Argon Time Projection Chamber (LArTPC) as its core detecting technology, offering high-resolution imaging to reconstruct neutrino interactions on argon. A primary challenge in this reconstruction is the modeling of hadronic final-state interactions (FSI), where hadrons produced at the initial interaction vertex undergo further scattering before escaping the nucleus. In this thesis, I utilize the ProtoDUNE-SP detector and its 1~GeV/$c$ hadron beam at the CERN Neutrino Platform to present the first measurements of total inelastic $\pi^+$-argon and proton-argon cross sections in an energy regime critical to DUNE. I detail the development and validation of the ``slicing method'', which utilizes a kiloton-scale LArTPC to extract hadron-argon cross sections. These measurements provide an indispensable benchmark for informing DUNE's FSI modeling, and our results show no significant tension with current model predictions. Additionally, I study the impact of FSI modeling on DUNE’s sensitivity to oscillation parameters. This study demonstrates that variations in FSI models may be degenerate with oscillation features, highlighting the necessity of using direct experimental data to refine interaction models. Finally, I provide an outlook on related studies that will further contribute to this effort, supporting the ambitious physics goals of upcoming neutrino oscillation programs including DUNE.

Yin-Rui, Liu [U. Chicago (main)]↗