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DOE OSTI2026

First results from the search for muon neutrino disappearance with ICARUS

After successful operation at LNGS and a major upgrade at CERN, the 760-ton ICARUS T600 detector has been running at Fermilab since 2020, collecting neutrino interactions from the BNB and NuMI beams. In late 2025, ICARUS reached five years of continuous data taking, demonstrating the maturity of large-scale LAr-TPC technology and its relevance for future experiments such as DUNE. This contribution presents the first ICARUS search for muon-neutrino disappearance in the BNB. Charged-current 1μNp events selected from 2022–2023 data are compared to simulations and interpreted, for the first time, within a two-neutrino approximation of the 3+1 sterile-neutrino model, including systematic uncertainties from flux, interaction, and detector effects. Although currently limited by systematic uncertainties, this first oscillation analysis probes the parameter space suggested by existing νμ-disappearance results and lays the groundwork for future SBN combined analyses with SBND, which will significantly improve sensitivity to sterile-neutrino scenarios.

Artero Pons, Maria [Padua U.; INFN, Padua]↗

DOE OSTI2026

Towards Spatial Control of Reaction Selectivity on Photocatalysts using Area Selective Atomic Layer Deposition on Model Dual Site Electrocatalyst Platform

Photocatalytic water splitting is a promising route to low-cost H2; however, this approach is currently limited by solar-to-hydrogen (STH) conversion efficiencies in the sub-10% range. Z-scheme water splitting, in which H2 and O2 evolving particles are operated in separate compartments and electronically coupled by a soluble redox mediator, offers improvements in STH efficiency but introduces high rates of undesired side and back reactions. Nanoscopic oxide coatings (e.g., CrOx, and SiOx) have previously been used to selectively block undesired reactants from reaching active sites; however, a coating encapsulating the entire photocatalyst particle limits activity as the particle can no longer facilitate both half reactions. In contrast to photodeposition, which may produce non-uniform overlayers due to the difficulty of controlling local electrochemical reactivity on the surface, area-selective atomic layer deposition (AS-ALD) can be used to deposit conformal ultrathin oxide coatings while preserving access to non-growth areas of a substrate surface. To develop this technique for Z-scheme photocatalysts, we performed AS-ALD of TiO2 on a dual site planar electrocatalyst based on interdigitated arrays of Pt and Au. Self-assembled monolayers of 1-octadecanethiol (ODT) were used to block growth on the Au array, resulting in a patterned surface in which only the Pt sites were encapsulated with TiO2. These electrocatalysts demonstrated localized reaction selectivity for hydrogen evolution reaction (HER) over the TiO2/Pt sites, while the uncoated Au sites retained activity towards Fe(II)/Fe(III) redox (FeRR). Under independent potential control, these microelectrodes showed that selectively deposited TiO2 coatings can suppress the rate of back reactions on neighboring active sites by an order of magnitude compared to uncoated control samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Demonstration of Grid Services Using Mixed Grid-Forming and Grid-Following Technologies at the Wheatridge Renewable Energy Facility (Final Technical Report)

This Final Technical Report summarizes the analytical, modeling, and engineering work performed to evaluate grid-forming (GFM) inverter capabilities within a large hybrid renewable energy facility. The project focused on assessing the ability of advanced inverter-based resources to provide essential reliability services through coordinated operation of grid-forming (GFM) and grid-following (GFL) technologies. During Budget Period 1, the project developed a comprehensive framework of GFM performance metrics, including angle support, voltage regulation, frequency response, damping behavior, and current-limiting performance. Extensive electromagnetic transient (EMT) studies and hardware-in-the-loop (HIL) testing were conducted to validate GFM behavior under a range of operating conditions, including weak-grid scenarios, voltage disturbances, and multi-resource interactions. The project also established validated modeling approaches, plant-level control integration strategies, commissioning frameworks, and high-speed measurement infrastructure to support future field demonstration. Although the project concluded prior to field demonstration, the results provide a utility-scale foundation for evaluating, modeling, and deploying grid-forming technologies. The methodologies and tools developed contribute to industry understanding of inverter-based resource behavior and support future power system reliability under increasing renewable penetration.

14 SOLAR ENERGY↗

DOE OSTI2026

Quench Propagation On Rare-Earth Barium Copper Oxide (REBCO) Tape

Rare-earth barium copper oxide (REBCO) high-temperature superconductors can carry high currents with zero electrical resistance, enabling applications in high-field magnets, energy systems, and fusion devices. However, localized losses of superconductivity, known as quenches, pose a severe risk due to REBCO’s mechanical brittleness and slow quench propagation, complicating early detection. This work investigates quench propagation and thermal response through controlled experiments. A segmented REBCO tape soldered onto a printed circuit board (PCB) with multiple voltage taps and temperature sensors was submerged in liquid nitrogen at 77 K. In the first test, current ramping produced a quench near 360 A, consistent with theoretical current limits, but resulted in local burnout. In the second test, a heater-induced quench at 300 A propagated bidirectionally with velocities ranging from 164–226 mm/s. These results provide critical parameters for improving REBCO quench detection and protection system design while accounting for REBCO’s limited bendability.

Ju, Han [Northern Illinois U.]↗

DOE OSTI2026

Quench Propagation on Rare-Earth Barium Copper Oxide (REBCO) Tape

Rare-earth barium copper oxide (REBCO) high-temperature superconductors can carry high currents with zero electrical resistance, enabling applications in high-field magnets, energy systems, and fusion devices. However, the localized losses of superconductivity called a quench pose a severe risk due to REBCO’s mechanical brittleness and slow quench propagation, hence complicating early detection. This work investigates quench propagation and thermal response through controlled experiments. A segmented REBCO tape soldered on a PCB with multiple voltage taps and temperature sensors was submerged in liquid nitrogen at 77 K. In the first test, current ramping produced a quench near 360 A, consistent with theoretical current limits but resulted in a local burn. In the second test, a heater-induced quench at 300 A propagated bidirectionally with measured velocities ranging from 164–226 mm/s. These measurements provide critical parameters for improving REBCO quench detection and protection system design with accounts for REBCO's limited bendability.

Ju, Han [NIU, DeKalb]↗

DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗

DOE OSTI2025

LDRD for a high-current polarized-beam photogun

The electron accelerator driving the Ce+BAF conversion target requires a spin-polarized photogun capable of delivering a CW beam current of at least 1 mA. As the high beam current limits the useful operating time of the gun between photocathode reactivations due to ion back-bombardment, it is critical to increase the charge lifetime. A Jefferson Lab LDRD project aims to calibrate the simulation models needed to predict photocathode lifetime as a function of electrostatic optics and drive laser parameters in order to design a gun providing at least 1000 C charge lifetime. A prototype gun demonstrating the validity of the scaling predictions will be built and tested at the Gun Test Stand. I will describe the background and progress of this project and give an outlook on the expected performance.

Bruker, Max [Thomas Jefferson National Accelerator↗

DOE OSTI2026

DetSuM: Detector Surrogate Model for LArTPC

In large neutrino experiments such as the Deep Underground Neutrino Experiment (DUNE), estimating detector response uncertainties typically requires simulation samples that consume substantial computing resources and time. To mitigate this challenge, we present DetSuM, an uncertainty-aware surrogate model designed to capture the detector response variations with reduced computing load compared to full simulations. This poster describes the construction and evaluation of DetSuM using simulation and reconstruction datasets in a rare-event search at DUNE. We assess DetSuM's ability to predict key detector-response variations and their associated uncertainties, discuss current limitations, and outline improvements to extend its validity in systematics studies of DUNE physics.

Li, Aobo [UC, San Diego]↗

DOE OSTI2026

Development and Implementation of a New AI-Based Tool to Support Fast Reactor Software Model Generation and Validation

This report summarizes FY26 work to develop Maggie, an artificial intelligence-based assistant designed to support software model generation and validation activities for fast reactor analysis codes. The project established a modular, code-agnostic software architecture that separates reusable agent capabilities from code-specific knowledge and tools, with initial implementation focused on the FRP-supported fast reactor safety analysis code SAS4A/SASSYS1 (SAS). A curated SAS-specific knowledge base was assembled from the code manual, training materials, historical analysis reports, and representative input files, and was integrated through retrieval-augmented generation to ground Maggie’s responses in authoritative sources. Maggie was deployed on the internal Argonne network, where it demonstrated practical user-facing capability as a chatbot for answering natural language questions about SAS and retrieving relevant technical information. Demonstration cases also showed that Maggie can generate useful snippets of SAS input for selected modeling tasks, while highlighting current limitations in reliability and consistency for more complex input generation tasks. Overall, the FY26 effort established the technical foundation for an AI-assisted capability intended to improve the efficiency, consistency, and accessibility of fast reactor software model development at Argonne and, with further improvements, to support eventual use by the broader fast reactor community, including industry users of FRP-supported analysis tools.

Thomas, Rachel [Argonne National Laboratory (ANL),↗

DOE OSTI2026

First Results from the Search for Muon-Neutrino Disappearance with the ICARUS Detector

After successful operation at LNGS and a major upgrade at CERN, the 760-ton ICARUS T600 detector has been running at Fermilab since 2020, collecting neutrino interactions from the BNB and NuMI beams. In late 2025, ICARUS reached five years of continuous data taking, demonstrating the maturity of large-scale LAr-TPC technology and its relevance for future experiments such as DUNE. This contribution presents the first ICARUS search for muon-neutrino disappearance in the BNB. Charged-current 1$\mu$Np events selected from 2022–2023 data are compared to simulations and interpreted, for the first time, within a two-neutrino approximation of the 3+1 sterile-neutrino model, including systematic uncertainties from flux, interaction, and detector effects. Although currently limited by systematic uncertainties, this first oscillation analysis probes the parameter space suggested by existing $\nu_\mu$ disappearance results and lays the groundwork for future SBN combined analyses with SBND, which will significantly improve sensitivity to sterile-neutrino scenarios.

Steklain, Andre [Parana Tech. Fed. U., Toledo] (OR↗

DOE OSTI2026

Rational Design of Lanmodulin Variants for Size-Based Selectivity of Individual Rare Earth Elements

Rare earth elements (REEs) are essential to modern technologies, yet their high physical and chemical similarity makes separation of individual REEs difficult and environmentally taxing. Metalloproteins offer a promising alternative for selective REE binding, as they tend to have high metal ion affinity and specificity. Lanmodulin (LanM), in particular, has arisen as a potential candidate for REE separation as it exhibits picomolar affinity for elements in the REE family. Prior work has shown that the single point mutation D9N can shift LanM’s preference away from lanthanides toward actinides, motivating efforts to tune selectivity of LanM through targeted mutagenesis. Here, we tested the hypothesis that introducing selective aspartic acid to glutamic acid substitutions in the metal coordinating EF hands of LanM would impose steric constraints that would drive LanM affinity away from larger ions, such as La3+, to smaller ions, such as Y3+. To test this hypothesis, a combination of computational and experimental approaches were employed to evaluate the signal mutations LanM D5E and LanM D3E and the double mutants LanM D1ED5E and LanM D3ED9E. Surprisingly, increasing the number of mutations within the metal center did not enhance affinity for smaller REEs, or decrease affinity for larger ions. Only the single point mutation LanM D5E weakened La3+ binding by one order of magnitude relative to LanM wild type (WT), and pairing it with a second mutation to produce LanM D1ED5E drove La3+ affinity to be stronger than that seen for LanM WT. The D3E mutation alone prevented proper expression and folding, but paring it with D9E to produce LanM D3ED9E rescued expression and yielded La3+ affinities comparable to LanM WT. All variants that expressed (LanM D5E, LanM D1ED5E, LanM D3ED9E) displayed Y3+ affinities comparable to LanM WT. Overall, these results highlight the tunability of LanM’s metal-binding environment but also expose current limitations in predicting structural responses to point mutations within a protein sequence. This work establishes a foundation that can be used for refining computational and experimental strategies to engineer metalloproteins with tailored REE selectivity.

Close, Emily [Pacific Northwest National Laborator↗

DOE OSTI2025

SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions

Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation functions on the edges of the computational graph followed by summation on nodes. The learnable edge activation functions in the original implementation are basis spline functions (B-Spline). Here, we present a model in which learnable grids of B-Spline activation functions are replaced by grids of re-weighted sine functions (SineKAN). We evaluate numerical performance of our model on a benchmark vision task. We show that our model can perform better than or comparable to B-Spline KAN models and an alternative KAN implementation based on periodic cosine and sine functions representing a Fourier Series. Further, we show that SineKAN has numerical accuracy that could scale comparably to dense neural networks (DNNs). Compared to the two baseline KAN models, SineKAN achieves a substantial speed increase at all hidden layer sizes, batch sizes, and depths. Current advantage of DNNs due to hardware and software optimizations are discussed along with theoretical scaling. Additionally, properties of SineKAN compared to other KAN implementations and current limitations are also discussed.

Reinhardt, Eric↗

DOE OSTI2026

Augmented Reality Technologies for Radiation Safety Training: A Systematic Review of Sensor Integration and Visualization Approaches

This paper presents a comprehensive systematic review examining the application of augmented reality (AR) and sensor technologies for visualizing ionizing radiation in virtual training environments. The review methodology involved systematic identification and analysis of the relevant literature based on predetermined criteria including publication type, year of publication, application domain, and technological approach. The literature search encompassed publications from 2011 to 2021 across four major academic databases: Web of Science, Google Scholar, IEEE Xplore, and Scopus. Through rigorous screening following PRISMA 2020 guidelines, 23 research articles met the inclusion criteria for detailed analysis. From 404 initial database records, 360 were excluded during title/abstract screening (primarily for lacking AR components, radiation focus, or training applications) and 4 during full-text assessment (all for lacking sensor integration). The findings reveal that AR-based ionizing radiation visualization has been successfully implemented across diverse domains, including nuclear facility operations, medical procedures, CERN research activities, and educational and monitoring applications. The analysis identified multiple dimensions of impact, encompassing distinct benefits, emerging opportunities, and implementation challenges associated with AR deployment for ionizing radiation training. Each of these dimensions is comprehensively examined and documented within this review. Additionally, this study identifies critical research gaps that currently limit the full potential of AR technology in supporting ionizing radiation training programs. These gaps are systematically analyzed and discussed to establish clear directions for future research endeavors in this emerging field.

61 - RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Effects of Media Nutrient Variation on Microalgae Productivity and Economics During Semi-Continuous Cultivation

The development of large-scale microalgae growth for biofuel production is currently limited by the cost of biomass production. However, new approaches to infrastructure and cultivation practices are bringing the field closer to realization. Macronutrients in the cultivation media contribute significant costs, especially since their concentrations have not been optimized for specific strains and conditions. Environmental photobioreactors (ePBRs) were used to simulate cultivation under outdoor conditions, during which the nitrogen and phosphorus levels in the media were varied. The growth of two potential biofuel production strains, Picochlorum celeri and Tetraselmis striata, with varying nutrient inputs during summer and winter scripts, respectively, was studied. This study demonstrated that nitrogen and phosphorus in f/2 media could be reduced by more than 60% from the standard formulation, while maintaining growth rates in a semi-continuous harvesting approach. Experiments comparing the standard and reduced nutrient input concentrations were also conducted for both species in 820 L outdoor raceway ponds, in Mesa, AZ. P. celeri grown in these ponds in October had a growth rate of 10.6 ± 0.7 g/m 2 /day and 10.6 ± 0.3 g/m 2 /day for the standard and low-nutrient P. celeri ponds, respectively. T. striata grown in April–May had a growth rate of 16.6 ± 1.4 g/m 2 /day for the standard nutrient input ponds and 17.4 ± 1.1 g/m 2 /day for the low-nutrient input ponds, and in October 14.5 ± 0.6 g/m 2 /day for standard nutrient ponds and 14.4 ± 0.6 g/m 2 /day for low-nutrient ponds. These outdoor data therefore confirmed the indoor ePBR data. Techno-economic analysis shows that, if high growth rates can be attained at lower nutrient concentrations, a reduction of at least 60% in nutrient costs can be achieved. Such results highlight the importance of managing macronutrient media inputs, as these have a considerable contribution to biomass production costs in large-scale facilities. The analysis also points to the importance of maintaining high spent medium recycling rates in an industrial deployment, so as to minimize the losses of nitrogen and phosphorus compounds.

09 BIOMASS FUELS↗

DOE OSTI2026

Nickel Interlayer for Improved Silver Complex Inks Metallization in GaAs Photovoltaic Devices

Large areas of III-V photovoltaic panels are essential to supplying operational energy for a growing demand of satellites of strategic importance to the United States military, covering a range of applications. High fabrication costs and low manufacturing throughput are key barriers to meeting the necessary supply, which can in turn jeopardize mission success. At the device level, metallization based on printing of complex metal inks has attracted significant research interest due to its potential to substantially reduce processing costs and increase throughput while achieving electrical performance comparable to those of conventional metallization schemes. For GaAs photovoltaic devices, however, reliable electrical contacting remains challenging due to the formation of an interfacial oxide layer at the metal-semiconductor interface. This oxide barrier severely limits current extraction from the PV absorber, resulting in unacceptably high contact resistance. In this study, we report the introduction of a reactive nickel (Ni) interfacial layer between the silver metal fingers and the GaAs substrate to suppress oxide formation while maintaining a low-resistance electrical interface, and show performance data from fully fabricated GaAs devices incorporating the Ni interlayer. These results demonstrate the potential of reactive Ni ink as an effective interfacial layer for improved electrical contacting in low-cost PV metallization schemes.

14 SOLAR ENERGY↗

DOE OSTI2025

Adsorption of Rare Earth Elements to Kaolinite [dataset]

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7−8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH 5 but does not affect adsorption at pH 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH ∼6 and inner-sphere surface complexation to edge sites at pH ∼6. Equilibrium constants for surface complexation increase in the order of Yb Dy Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗

DOE OSTI2024

Towards a Circular Economy for PET Bottles in the U.S. - 4P Model

The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.

carbon↗

DOE OSTI2024

Towards a Circular Economy for PET Bottles in the U.S. - 4P Framework

circular economy↗