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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of a Printable Prill Formulation Technique and Demonstration of Monomodal Prill Size on Compaction Density and Compressive Strength

Polymer-bonded explosive molding powder, or “prills,” are relied on for the fabrication of pressed high explosives since the 1950's. The wet granulation technique, also known as “slurry coating,” that is used to formulate prills, is a complex process that results in polydisperse and variable yields. This makes it difficult to study the mesoscale effect that prills have on the microstructure of a pressed article. The following study introduces a novel approach to energetic granulation that leverages techniques used in the additive manufacturing of paste-like energetic materials. This extrusion granulation, or prill printing technique, makes it possible to tailor the sizes and shapes of prills, allowing for their morphological influences to be studied in a controlled manner. The following work details the fabrication and characterization of four monomodal size lots of prills using an inert formulation (95 wt.% melamine, 5 wt.% polymer binder). Prills from each size lot were die-pressed using a fixed recipe to investigate how prill size impacts compaction density and therefore compressive strength. It was found that larger prills influence the pressing density by creating larger defects within the microstructure of a pressed article, resulting in a decrease in compressive strength.

direct ink write↗
DOE OSTI2025

Supercritical preparation of doped (111) facetted nickel oxide for the oxygen evolution reaction

Green hydrogen is of great interest as a replacement for traditional fossil fuels in a variety of energy applications. However, due to the poor kinetics present in the oxygen evolution reaction (OER) half-reaction, nanostructured catalysts are needed to reduce the reaction overpotential. Nickel oxide has previously been shown to be a promising alternative to expensive Pt-group based catalysts for the OER in alkaline media. Herein, facetted NiO nanosheets have been doped with Fe, Mn, or Co to reduce its catalytic overpotential for the OER. A supercritical synthesis process was used to promote the mass transport of the reactants while preserving catalytic surface area. Microscopy, diffraction, spectroscopy, and adsorption techniques were used to understand the morphological changes resulting from the inclusion of each dopant, as well as characterize the surface chemistry presented by the doped (111) facet. The pH was found to affect the properties of mixing due to difference in hydrolysis rates and catalysis of the hydrolysis/condensation. The dopants exhibited distinct effects on OER activity: Mn increased the overpotential to 742 mV vs. RHE, while Co and Fe reduced it to 502 mV and 457 mV, respectively. In summary, a straightforward and novel synthesis method is presented to prepare doped NiO(111) nanosheets, and their surface characteristics are explored to understand their varied electrochemical performances.

08 HYDROGEN↗
DOE OSTI2025

Low viscosity of solid MgO at high pressures and strain rates measured using the laser-driven Richtmyer-Meshkov instability

Solids are often assumed to behave as viscous fluids under high-strain rates. This behavior has been studied experimentally in metals but largely unexplored in brittle ceramic materials. Here, in this study, we present a technique for measuring the viscosity of MgO using time-resolved velocimetry to track the growth rate of a perturbation caused by the Richtmyer-Meshkov instability at the OMEGA EP laser facility. To interpret the results, we use an in-house Eulerian hydrocode to simulate our experiments and model the plastic deformation of solid MgO as a viscous fluid. Results indicate that MgO has a surprisingly low upper bound to its effective viscosity of ∼10 2 ⁢ Pa s at 175 ± 15⁢ GPa, ∼3500⁢K, and 10 6 −10 7 s −1 strain rate.

Perez, Tyler M. [Johns Hopkins Univ., Baltimore, M↗
DOE OSTI2025

Understanding (La,Sr)(Co,Fe)O$_{3-δ}$ Phase Instability within SOECs Using a Combined Experimental and Atomistic Modeling Approach

Understanding the onset of degradation in the air electrode within solid oxide electrolysis cells (SOECs), and the subsequent impact on cell performance, is a critical step in mitigating the performance losses and stability issues of SOECs. In an effort to identify early onset degradation phenomena, SOECs were characterized as fabricated and after testing potentiostatically at 1.3 V for 1000 h at 750 °C. SOEC air electrodes composed of a 1:1 composite of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (6428-LSCF) and Gd 0.1 Ce 0.9 O 1.95 (GDC) were studied using synchrotron X-ray diffraction (XRD), scanning transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (STEM-EDS), and X-ray absorption near-edge spectroscopy (XANES) to evaluate the changes in the air electrode structurally and chemically. These techniques show the migration of Sr species from the air electrode through pores in the GDC barrier layer, progressing to the electrolyte boundary, where it accumulates and reacts with (Zr 0.84 Y 0.16 )O 2–δ (YSZ) to form SrZrO 3 . Microscopy results are paired with atomistic simulations to better understand the relationship between the thermodynamic instability of 6428-LSCF and cell fabrication/testing conditions. First-principles calculations reveal that LSCF-6428 is not stable during cell manufacturing and testing conditions, which supports the experimental identification of secondary phases in both as-fabricated and tested cells. Together, these results demonstrate that the challenging environments encountered by SOECs during cell manufacturing and operation lead to instabilities of the target 6428-LSCF anode material and underscore the need for more durable, high-performing SOEC components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Power Electronics Manufacturing Improvements for Heavy-Duty Fuel Cell Vehicles

The Marel Power Solutions project, funded by the U.S. Department of Energy under Award DE-SC0023801, focused on advancing manufacturing techniques for power electronics in heavy-duty fuel cell vehicles. The research aimed to enhance system efficiency, reduce costs, and support broader adoption of hydrogen fuel cell technology. Key areas of investigation included power topology, thermal modeling, system architecture, and accessibility through software tools. Key Accomplishments: 1. Power Topology: - Developed an interleaved boost converter with optimized phase count, leveraging Marel’s proprietary Power Stacks. - Achieved reduced parasitic inductance and resistance, enabling high efficiency in DC-DC converters. 2. Thermal Modeling: - Integrated innovative cooling systems into compact Silicon Carbide (SiC) modules. - Simulations demonstrated the ability to dissipate significant heat (up to 7.5 kW), ensuring device reliability under heavy loads. 3. System Architecture: - Utilized simulation tools to analyze the impact of various fuel cell and vehicle parameters on efficiency. - Highlighted the role of smaller, modular improvements, such as enhanced DC-DC converters, in achieving system-wide gains. 4. Accessibility: - Evaluated and implemented MATLAB/Simulink code generation tools for real-world hardware applications. - Demonstrated the potential for rapid prototyping of custom power systems with reduced development costs. Impact and Benefits: - Efficiency and Cost Reduction: Marel’s cooling technology enhances SiC die performance, reducing the number of dies required and overall system size. - Scalability and Flexibility: The innovations support tailored solutions for diverse applications, from mass transit to mining vehicles. - Sustainability: The research promotes the integration of electrification technologies, helping meet rising energy demands sustainably. Conclusion: The project’s outcomes advance the state of power electronics for hydrogen fuel cell vehicles, enabling more efficient, compact, and cost-effective solutions. These developments lay a foundation for future innovation, contributing to the broader adoption of clean energy technologies in transportation and other industries.

08 HYDROGEN↗
DOE OSTI2025

Porous carbon from lignocellulosic biomass with emphasis on corn plant waste residue for energy storage

The rising global demand for sustainable energy storage materials has driven the search for environmentally friendly and cost-effective electrode options. Hydrothermal conversion of lignocellulosic biomass has gained attention due to its low energy requirements and operation at relatively low temperatures, presenting a green alternative to traditional thermochemical methods. The resulting solid product, hydrochar, has been used as an adsorbent and soil amendment; however, chemical/thermal treatment significantly enhances its physical properties. These structural modifications transform hydrochar into an effective porous carbon electrode, offering abundant sites for electrolyte ion transport, critical for high-performance devices like supercapacitors and batteries. This review first discusses various waste biomass and sustainable feedstocks available globally. It compares two primary thermochemical conversion techniques, pyrolysis and hydrothermal carbonization/liquefaction, and examines their respective solid products, biochar and hydrochar, analyzing differences in their physical and chemical characteristics. The focus is placed on hydrochar, summarizing activation methods to produce porous carbon suitable for energy storage applications. Additionally, this review will include a dedicated section on the application of porous carbon derived from corn plant waste residue, considering that corn is one of the most abundant crops grown worldwide, which makes it an important and promising source for sustainable porous carbon production. The role of machine learning models in optimizing hydrothermal processes to produce high-quality hydrochar is also discussed, emphasizing how data-driven approaches can streamline process development. Finally, the review identifies the current challenges and prospects for lignocellulosic biomass-derived porous carbon as a sustainable electrode material in next-generation energy storage technologies.

25 ENERGY STORAGE↗
DOE OSTI2025

Evaluating Short-warning Mitigation via Intentional Robust Disruption of a Hypothetical Impact of Asteroid 2023 NT1

We investigate various short-warning mitigation scenarios via fragmentation for a hypothetical impact of asteroid 2023 NT1, a near-Earth object (NEO) that was discovered on 2023 July 15, two days after its closest approach to Earth on July 13. The asteroid passed by Earth within ∼0.25 lunar distances, with a closest approach of ∼1 × 10 5 km and a velocity of 11.27 km s −1 . Its size remains largely uncertain, with an estimated diameter range of 26–58 m and a most probable estimate of 34 m (JPL Sentry, 2023 September 15; weighted by the NEO size frequency distribution). If 2023 NT1 had collided with Earth, it could have caused significant local damage. Assuming a spherical asteroid with a diameter of 34 m, uniform density of 2.6 g cm −3 , and impact velocity of 15.59 km s −1 , a collision would have yielded an estimated impact energy of ∼1.5 Mt, approximately 3 times the energy of the Chelyabinsk airburst in 2013. We analyze the effectiveness of mitigation via intentional robust disruption for objects similar to 2023 NT1. We utilize Pulverize It (PI), a NASA Innovative Advanced Concepts study of planetary defense via fragmentation, to model potential mitigation scenarios through simulations of hypervelocity asteroid disruption and atmospheric ground effects in the case of a terminal defense mode. Simulations suggest that PI is an effective multimodal approach for planetary defense that can operate in extremely short interdiction modes, in addition to long interdiction timescales with extended warning. Our simulations support the proposition that threats like 2023 NT1 can be effectively mitigated with intercepts of 1 day (or less) prior to impact, yielding minimal to no ground damage.

Asteroids↗
DOE OSTI2026

Designing the Platinum Catalyst Layer for Improved Performance and Durability in Anion Exchange Membrane Water Electrolysis

To lower the cost of hydrogen produced by anion exchange membrane water electrolysis (AEMWE), it is critical to reduce the use of platinum group metal (PGM) catalysts within the device. While iridium has been successfully replaced with PGM-free catalysts at the anode, platinum-based (Pt) cathode catalysts are still required to meet the activity and durability targets. This study investigates the impact of commercial Pt/C catalyst loading, ionomer type and content, and electrode fabrication method on the cathode catalyst layer properties and AEMWE performance with the aim of determining the feasibility of reduced Pt loadings. While increased Pt loading is found to improve beginning-of-life performance, the effects are minimal above 0.6 mg/cm 2 . Ink characterization shows that ionomer type and content affect the ink stability, particle size, and percent of unbound ionomer, which further impact the homogeneity of the sprayed catalyst layers. The 5% PiperION cathode exhibited the highest performance, which may be attributed to a balance between the small particle size and the low proportion of unbound ionomer, minimizing kinetic and transport losses. Theoretical calculations show that the ionomers interact differently with the Pt surface, causing different surface charges and water adsorption strength and activating different mechanisms for hydrogen evolution. Pt-PiperION lowered the enthalpy of water-splitting by 0.1 eV compared to Pt alone and allowed for equal site access between adsorbed H* and OH* (both adsorbed at circa −2.2 eV). Although catalyst-coated membrane (CCM) fabrication techniques are desirable for scale-up, no performance enhancement is observed compared with the catalyst-coated substrate approach. Durability, as measured by degradation rates, Pt loss, and catalyst layer restructuring, was found to improve with increased Pt loadings, higher ionomer content, and CCM architectures. These findings provide important insight into the significant role of the cathode in AEMWE and strategies for maintaining the performance with low Pt loading or PGM-free catalysts.

08 HYDROGEN↗
DOE OSTI2025

Structural characterization of highly alloyed (Al,Gd)N thin films

Highly alloyed (Al,Gd)N is of potential interest in a variety of applications, including neutron detection and in devices such as non-volatile memory. Gd has been shown to have very low equilibrium solubility in AlN at room temperature; however, non-equilibrium deposition techniques such as sputtering are able to deposit thin films, which incorporate large amounts of Gd. Here, we characterize a highly-alloyed (Al,Gd)N combinatorial thin film grown by RF sputtering on a GaN substrate, looking for any evidence of chemical or phase segregation or structural disorder in the films. Compositions with between 13% and 32% Gd (on a cation basis) were studied. No evidence was found for chemical or phase segregation in any studied composition. Higher degrees of Gd incorporation led to greater structural disorder in the film and a tendency toward amorphization; however, electron diffraction shows that the film does not become fully amorphous at any of the studied compositions, instead retaining textured local order even at 32% Gd. Electron energy loss spectra suggest that the material retains a locally wurtzite-like tetrahedral bonding environment at all studied compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Extrusion‐Spheronization of Mock Energetic Materials

The primary method for producing plastic bonded explosive (PBX) granules, or “prills”, has remained relatively unchanged for 70 years despite the complex nature of the process. In this work, we demonstrate the feasibility of using an extrusion‐spheronization technique to produce prills for PBX applications. We begin by detailing an inert formulation with similar properties of PBXs and then demonstrate the extrusion‐spheronization processing of these materials. A study is then performed where the spheronization process time of the extruded materials is varied and the resultant prills are morphologically characterized. Further, these prills are then pressed into high‐density articles and subject to compression testing to elucidate trends in process, properties, and performance. It was found that, for our formulation (95 wt.% melamine/5 wt.% polymer binder) and process, a spheronization time of 60 s yielded relatively uniform particles that exhibited improved poured, tapped, and pressed densities. Mechanical strength did not have a strong trend with process time as all spheronized materials had similar peak compression stress at failure. After further optimization, extrusion‐spheronization may be a promising path for future PBX formulation.

extrusion spheronization↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
DOE OSTI2025

Thermodynamics, local structure, and transport of protons in triple-conducing oxide, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411)

Triple-conducting oxides (TCOs) are an emerging class of mixed ionic and electronically conducting materials that show great promise for oxygen reduction/oxygen evolution (ORR/OER) electrocatalysis—primarily in high-temperature ceramic electrochemical cells— but also in aqueous alkaline environments. Their high activity is attributed, at least in part, to their ability to incorporate and transport three mobile charge carriers: protons, oxygen vacancies, and electron-holes Despite their promise, fundamental studies of TCOs are challenging, as transport dynamics from three charge carriers cannot be fully disentangled via traditional electrical measurement techniques. Characterizing proton dynamics in TCOs is particularly difficult as protons are generally the minority carrier, and their conduction response is typically obscured by the oxygen vacancies and electron holes. Here, we demonstrate successful isolation of the proton behavior in an archetypal TCO, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411), using a combination of non-electrical techniques. We determine proton uptake and oxygen non-stoichiometry (δ) using thermogravimetric analysis (TGA). X-ray absorption near edge structure (XANES) and neutron diffraction (ND) are used to validate the oxidation state of Co and the δ values obtained through TGA. We apply 1H solid-state magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) to provide insights into local structure, dynamics, and proton kinetics. Finally, the proton transport properties are further quantified using tracer isotope exchange with time-of-flight secondary ion mass spectrometry (ToF-SIMS). Despite the very low proton concentrations in BCFZY4411 (<0.2% under most conditions), our analysis suggests that the oxygen Manuscript File Click here to view linked References 2 reduction and evolution reactions are nevertheless limited by the oxygen ion kinetics (e.g., oxygen surface exchange) rather than the proton kinetics at the reduced operating temperatures (<500 °C) that are targeted for electrochemical cell applications. These findings provide a comprehensive understanding of proton behavior in BCFZY4411 and pave the way for advancing the fundamental study of TCOs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Analysis of the density field around a supersonic conical projectile using quantitative schlieren

Quantitative schlieren imaging is a flow measurement technique that is capable of measuring density fields throughout refractive flowfields. The technique was applied here to measure the density field surrounding supersonic conical projectiles in free flight. Shock waves attached to a supersonic conical projectile offer a simple geometry with the well-established Taylor–Maccoll analytical flow solution to which these experimental measurements were compared. The schlieren images recorded a projection of the index of refraction field surrounding the 10° half-angle cones which was converted to density first through an Abel inversion and then the Gladstone–Dale law. Three Abel inversion methods—two-point, three-point, and arbitrary ray axisymmetric projection (ARAP)—were applied to deconvolute the three-dimensional flow within the constrained axisymmetric flow field. The resulting reconstructed density profiles were compared to the Taylor–Maccoll solution, parameterized by cone geometry and Mach number. The experimental density fields demonstrated strong agreement with the theoretical profiles. Experimental consistency was confirmed across various projectile speeds, demonstrating quantitative schlieren’s capability to accurately reconstruct the density of the flow field, even within the resolution constraints imposed by high-speed imaging. In conclusion, an assessment of experimental uncertainties in the density reconstruction was performed.

Abel Inversion↗
DOE OSTI2025

Review of High‐Speed Digital Image Correlation: Advancements and Good Practices

This paper reviews the current state of the art in high‐speed (HS) and ultrahigh‐speed (UHS) digital image correlation (DIC) techniques, emphasizing their critical role in experimental research across various scientific domains. HS and UHS DIC have evolved significantly, driven by advancements in camera systems, image processing algorithms and experimental methodologies. These developments have opened new avenues for capturing and analysing dynamic events with unprecedented temporal and spatial detail, but not without introducing challenges such as optical distortions, motion blur and lighting issues that can affect measurement quality. This review advocates for standardized reporting practices in HS/UHS DIC methodologies to improve reproducibility and reliability across studies, drawing on guidelines from the International Digital Image Correlation Society (iDICs). Through a comprehensive analysis of over 150 articles, this review identifies key advancements in imaging technology and their application in six research domains: material characterization, test development, fracture mechanics, model validation, ballistic and explosive phenomena assessment and measurement uncertainties. Distinctions between two‐dimensional (2D) and stereo‐DIC applications are explored, offering insights into their practical implementation and trade‐offs. Good practices for HS/UHS DIC applications are proposed along with suggestions for future directions for this evolving field, highlighting the indispensable role of technological innovation in expanding the capabilities of optical metrology.

experimental mechanics↗
DOE OSTI2024

New methods and simulations for cosmogenic induced spallation removal in Super-Kamiokande-IV

Radioactivity induced by cosmic muon spallation is a dominant source of backgrounds for 𝒪⁡(10 MeV) neutrino interactions in water Cherenkov detectors. In particular, it is crucial to reduce backgrounds to measure the solar neutrino spectrum and find neutrino interactions from distant supernovae. In this paper we introduce new techniques to locate muon-induced hadronic showers and efficiently reject spallation backgrounds. Applying these techniques to the solar neutrino analysis with an exposure of 2790 × 22.5 kton · day increases the signal efficiency by 12.6%, approximately corresponding to an additional year of detector running. Furthermore, we present the first spallation simulation at Super-Kamiokande, where we model hadronic interactions using fluka. The agreement between the isotope yields and shower pattern in this simulation and in the data gives confidence in the accuracy of this simulation, and thus opens the door to use it to optimize muon spallation removal in new data with gadolinium-enhanced neutron capture detection.

muons↗
DOE OSTI2025

Probing the PeV region in the astrophysical neutrino spectrum using 𝜈 𝜇 from the Southern sky

IceCube has observed a diffuse astrophysical neutrino flux over the energy region from a few TeV to a few PeV. At PeV energies, the spectral shape is not yet well measured due to the low statistics of the data. This analysis probes the gap between 1 and 10 PeV by using high-energy downgoing muon neutrinos. Here, to reject the large atmospheric muon background, two complementary techniques are combined. The first technique selects events with high stochasticity to reject atmospheric muon bundles whose stochastic energy losses are smoothed due to high muon multiplicity. The second technique vetoes atmospheric muons with the IceTop surface array. Using 9 yrs of data, we found two neutrino candidate events in the signal region, consistent with expectation from background, each with relatively high signal probabilities. A joint maximum likelihood estimation is performed using this sample and an independent 9.5-yr sample of tracks to measure the neutrino spectrum. A likelihood ratio test is done to compare the single power-law (SPL) vs SPL+cutoff hypothesis; the SPL+cutoff model is not significantly better than the SPL. High-energy astrophysical objects from four source catalogs are also checked around the direction of the two events. No significant coincidence was found.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗