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DOE OSTI2025

Electromagnetic Transient Simulation of Large-Scale Inverter-Based Resources With High-Granularity

The power grid is undergoing a significant transformation with the rapid increase in inverter-based resources (IBRs), including large-scale photovoltaic (PV) plants. Ensuring reliable and resilient grid operation in this new paradigm necessitates high-granularity electromagnetic transient (EMT) modeling that accurately captures the behavior of individual inverters and their interactions within IBR plants. Central to this approach is the detailed representation of both the IBR plant’s collector system and the dynamics of individual inverters. To achieve this, a high-granularity EMT model of a large-scale PV plant has been developed using advanced simulation algorithms, including matrix splitting and the Schur complement. These proposed techniques significantly enhance simulation speed, numerical stability, and accuracy while improving the modularity and efficiency of the collector system’s representation. The effectiveness of the proposed methods is validated through simulations of a representative large-scale PV plant consisting of 125 individual PV inverters, 25 IBR unit transformers, and a 52-bus collector system.

Choi, Jongchan [Oak Ridge National Laboratory (ORN↗

DOE OSTI2024

Large $$N_c$$ QCD phase diagram at $$\mu _B=0$$

Abstract Lattice studies suggest that at zero baryon chemical potential and increasing temperature there are three characteristic regimes in QCD that are connected by smooth analytical crossovers: a hadron gas regime at$$T < T_{ch}\sim 155$$ T < T ch ∼ 155 MeV, an intermediate regime, called stringy fluid, at$$T_{ch}< T < \sim 3 T_{ch}$$ T ch < T < ∼ 3 T ch , and a quark-gluon plasma regime at higher temperatures. These regimes have been interpreted to reflect different approximate symmetries and effective degrees of freedom. In the hadron gas the effective degrees of freedom are hadrons and the approximate chiral symmetry of QCD is spontaneously broken. The intermediate regime has been interpreted as lacking spontaneous chiral symmetry breaking along with the emergence of new approximate symmetry, chiral spin symmetry, that is not a symmetry of the Dirac Lagrangian, but is a symmetry of the confining part of the QCD Lagrangian. While the high temperature regime is the usual quark-gluon plasma which is often considered to reflect “deconfinement” in some way. This paper explores the behavior of these regimes of QCD as the number of colors in the theory,$$N_c$$ N c , gets large. In the large$$N_c$$ N c limit the theory is center-symmetric and notions of confinement and deconfinement are unambiguous. The energy density is$$\mathcal{O}(N_c^0)$$ O ( N c 0 ) in the meson gas,$${{\mathcal {O}}}(N_c^1)$$ O ( N c 1 ) in the intermediate regime and$${{\mathcal {O}}}(N_c^2)$$ O ( N c 2 ) in the quark-gluon plasma regime. In the large$$N_c$$ N c limit these regimes may become distinct phases separated by first order phase transitions. The intermediate phase has the peculiar feature that glueballs should exist and have properties that are unchanged from what is seen in the vacuum (up to$$1/N_c $$ 1 / N c corrections), while the ordinary dilute gas of mesons with broken chiral symmetry disappears and approximate chiral spin symmetry should emerge.

Physics↗

DOE OSTI2024

Atacama Large Aperture Submillimeter Telescope (AtLAST) science: Resolving the hot and ionized Universe through the Sunyaev-Zeldovich effect

An omnipresent feature of the multi-phase “cosmic web” — the large-scale filamentary backbone of the Universe — is that warm/hot (≳ 10 5 K) ionized gas pervades it. This gas constitutes a relevant contribution to the overall universal matter budget across multiple scales, from the several tens of Mpc-scale intergalactic filaments, to the Mpc intracluster medium (ICM), all the way down to the circumgalactic medium (CGM) surrounding individual galaxies, on scales from ~ 1 kpc up to their respective virial radii (~ 100 kpc). The study of the hot baryonic component of cosmic matter density represents a powerful means for constraining the intertwined evolution of galactic populations and large-scale cosmological structures, for tracing the matter assembly in the Universe and its thermal history. To this end, the Sunyaev-Zeldovich (SZ) effect provides the ideal observational tool for measurements out to the beginnings of structure formation. The SZ effect is caused by the scattering of the photons from the cosmic microwave background off the hot electrons embedded within cosmic structures, and provides a redshift-independent perspective on the thermal and kinematic properties of the warm/hot gas. Still, current and next-generation (sub)millimeter facilities have been providing only a partial view of the SZ Universe due to any combination of: limited angular resolution, spectral coverage, field of view, spatial dynamic range, sensitivity, or all of the above. In this paper, we motivate the development of a wide-field, broad-band, multi-chroic continuum instrument for the Atacama Large Aperture Submillimeter Telescope (AtLAST) by identifying the scientific drivers that will deepen our understanding of the complex thermal evolution of cosmic structures. On a technical side, this will necessarily require efficient multi-wavelength mapping of the SZ signal with an unprecedented spatial dynamic range (from arcsecond to degree scales) and we employ detailed theoretical forecasts to determine the key instrumental constraints for achieving our goals.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗

DOE OSTI2025

Assessing the Impact of Large Removable Beryllium Reflector Experiments on HFIR Performance and Safety Metrics

This study investigated the effect of various removable beryllium (RB) experiment configurations on High Flux Isotope Reactor (HFIR) metrics to address increasing interest in these facilities for materials and fuels irradiation research. The RB reflector contains eight large and four small irradiation experiment facilities that offer excellent neutron flux conditions to perform fission and fusion reactor materials and fuels irradiation research. This work aims to outline acceptable RB configurations based on safety, performance, and programmatic metrics. This study assessed experiment effects on reactivity, cycle length, fission rate density distributions, and neutron flux distributions using the Shift, HFIRCON, and SCALE ORIGEN codes. Initial evaluations focused on generic experiment materials including aluminum plugs, stainless steel plugs, molybdenum plugs, and aluminum plugs with gadolinium shields. Subsequent analyses of MiniFuel experiments were performed to evaluate a heterogenous experiment, consisting of a more complex geometry and bearing several materials, and to test the correlations developed with the generic materials on a real experiment. Furthermore, the effects of neutron poison concentrations in the standard beryllium plugs were evaluated. When assuming a reference RB configuration with eight large fresh beryllium plugs, perturbed configurations with three aluminum plugs, one stainless steel plug, one molybdenum plug, one gadolinium-shielded aluminum plug, and one MiniFuel experiment resulted in a cycle length reduction of less than 1.3 days, the current threshold before requiring additional approvals. Configurations with five aluminum plugs, one stainless steel plug, one molybdenum plug, one gadolinium-shielded aluminum plug, and two MiniFuel experiments meet the 1.3 day limit if irradiated beryllium plugs are considered. Fuel element fission rate density distributions remained within safety limits, with maximum local increases under 9%. Neutron flux calculations revealed large thermal flux depressions inside and around the perturbed RB facilities, while epithermal and fast neutron fluxes increased because of reduced neutron moderation by the perturbed materials. These findings provide valuable guidance for optimizing RB configurations to balance safety and performance at HFIR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Electricity Rate Designs for Large Loads: Evolving Practices and Opportunities 2026 Update

Electricity demand from large-load customers such as data centers is projected to grow significantly in the near term. While these large loads play an important role in advancing technology innovation and economic growth in the United States, meeting their energy needs requires utilities and regulators to consider important operational and financial risks, such as insufficient energy supply or underutilized investments, that can impact all customers. This paper builds on similar research published in January 2025, providing an overview of how utilities and regulators are managing these risks through different tariffs, including rate structures and electric service agreements. Regulators, utilities, customers, and other stakeholders can use this paper as a foundation when discussing issues and sharing perspectives on developing or reviewing large-load tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

High-Resolution Large-Eddy Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the Large-Eddy simulations. The data will be divided according to the storm intensity level at the simulation time. Category 2: Harvey, Nate Category 3: Michael, Delta Category 4: Michael, Laura

17 WIND ENERGY↗

DOE OSTI2024

Photocatalytic water splitting for large-scale solar-to-chemical energy conversion and storage

Sunlight-driven water splitting allows renewable hydrogen to be produced from abundant and environmentally benign water. Large-scale societal implementation of this green fuel production technology within energy generation systems is essential for the establishment of sustainable future societies. Among various technologies, photocatalytic water splitting using particulate semiconductors has attracted increasing attention as a method to produce large amounts of green fuels at low cost. The key to making this technology practical is the development of photocatalysts capable of splitting water with high solar-to-fuel energy conversion efficiency. Furthermore, advances that enable the deployment of water-splitting photocatalysts over large areas are necessary, as is the ability to recover hydrogen safely and efficiently from the produced oxyhydrogen gas. This lead article describes the key discoveries and recent research trends in photosynthesis using particulate semiconductors and photocatalyst sheets for overall water splitting, via one-step excitation and two-step excitation (Z-scheme reactions), as well as for direct conversion of carbon dioxide into renewable fuels using water as an electron donor. We describe the latest advances in solar water-splitting and carbon dioxide reduction systems and pathways to improve their future performance, together with challenges and solutions in their practical application and scalability, including the fixation of particulate photocatalysts, hydrogen recovery, safety design of reactor systems, and approaches to separately generate hydrogen and oxygen from water.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Tetranuclear Polypyridylruthenium(II) Complexes as Selective Nucleic Acid Stains for Flow Cytometric Analysis of Monocytic and Epithelial Lung Carcinoma Large Extracellular Vesicles

Selective staining of extracellular vesicles (EVs) is a major challenge for diagnostic and therapeutic applications. Herein, the EV labeling properties of a new class of tetranuclear polypyridylruthenium(II) complexes, Rubb7-TNL and Rubb7-TL, as phosphorescent stains are described. These new stains have many advantages over standard stains to detect and characterize EVs, including: high specificity for EV staining versus cell staining; high phosphorescence yields; photostability; and a lack of leaching from EVs until incorporation with target cells. As an example of their utility, large EVs released from control (basal) or lipopolysaccharide (LPS)-stimulated THP-1 monocytic leukemia cells were studied as a model of immune system EVs released during bacterial infection. Key findings from EV staining combined with flow cytometry were as follows: (i) LPS-stimulated THP-1 cells generated significantly larger and more numerous large EVs, as compared with those from unstimulated cells; (ii) EVs retained native EV physical properties after staining; and (iii) the new stains selectively differentiated intact large EVs from artificial liposomes, which are models of cell membrane fragments or other lipid-containing debris, as well as distinguished two distinct subpopulations of monocytic EVs within the same experiment, as a result of biochemical differences between unstimulated and LPS-stimulated monocytes. Comparatively, the staining patterns of A549 epithelial lung carcinoma-derived EVs closely resembled those of THP-1 cell line-derived EVs, which highlighted similarities in their selective staining despite their distinct cellular origins. This is consistent with the hypothesis that these new phosphorescent stains target RNA within the EVs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Visualizing How the Structure of Large-Radius Jets Shapes Their Wakes

The ATLAS collaboration has introduced and implemented a strategy for selecting and analyzing large-radius jets composed of skinny $R=0.2$ subjets in heavy ion collisions at the LHC. We show how measurements of these jets teach us about the resolution length $L_{\rm res}$ of quark-gluon plasma (QGP) and can teach us how jet substructure shapes the wakes that jets excite in the QGP droplets through which they pass. We use Hybrid Model calculations to reproduce measurements of $R_{AA}$ for large-radius jets in PbPb collisions, and study their dependence on the angle between the two skinny subjets involved in the final reclustering step of an $R=1$ jet. We show how these observables can constrain the value of $L_{\rm res}$ and demonstrate that the ATLAS data rule out any picture in which an entire parton shower loses energy coherently as if it were a single entity. Determining the degree to which the QGP can resolve partons within a jet is central to the broader program of using jet quenching measurements to probe QGP. We make further use of this setup by analyzing the response of the medium to the passage of large-radius $R=2$ jets containing two skinny subjets in gamma-jet events. We introduce novel jet-shape observables that allow us to visualize the angular shape of the soft hadrons originating from the wakes that wide jets with two skinny subjets excite in a droplet of QGP, as a function of the angular separation between the subjets. We find that even when they are $\sim 0.8- 1$ radian apart, a single broad wake is produced. Only when the two subjets are even farther apart is the presence of two sub-wakes revealed. We show that the way in which jet structure shapes jet wakes can be visualized with similar clarity in experiments by using only those hadrons with low $p_T$. These observables thus offer a new and distinctive way of seeing jet wakes in heavy ion collision data.

FOS: Physical sciences↗

DOE OSTI2024

Tracking precipitation features and associated large-scale environments over southeastern Texas

Abstract. Deep convection initiated under different large-scale environmental conditions exhibits different precipitation features and interacts with local meteorology and surface properties in distinct ways. Here, we analyze the characteristics and spatiotemporal patterns of different types of convective systems over southeastern Texas using 13 years of high-resolution observations and reanalysis data. We find that mesoscale convective systems (MCSs) contribute significantly to both mean and extreme precipitation in all seasons, while isolated deep convection (IDC) plays a role in intense precipitation during summer and fall. Using self-organizing maps (SOMs), we found that convection can occur under unfavorable conditions without large-scale lifting or moisture convergence. In spring, fall, and winter, front-related large-scale meteorological patterns (LSMPs) characterized by low-level moisture convergence act as primary triggers for convection, while the remaining storms are associated with an anticyclonic pattern and orographic lifting. In summer, IDC events are mainly associated with front-related and anticyclonic LSMPs, while MCSs occur more in front-related LSMPs. We further tracked the life cycle of MCS and IDC events using the Flexible Object Tracker algorithm over southeastern Texas. MCSs frequently initiate west of Houston, traveling eastward for around 8 h to southeastern Texas, while IDC events initiate locally. The average duration of MCSs in southeastern Texas is 6.1 h, approximately 4.1 times the duration of IDC events. Diurnally, the initiation of convection associated with favorable LSMPs peaks at 11:00 UTC, 3 h earlier than that associated with anticyclones.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures

The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.

17 WIND ENERGY↗

DOE OSTI2025

Detection of supernova magnitude fluctuations induced by large-scale structure

The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure f sigma_8 to the auto- and cross-correlation function measurements we find f sigma_8 = 0.384 +0.094 -0.157, which is consistent with the Planck LambdaCDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve f sigma_8 constraints by a further order of magnitude.

Nguyen, A. [Swinburne U., Ctr. Astrophys. Supercom↗

DOE OSTI2024

OPER: Optimality-Guided Embedding Table Parallelization for Large-scale Recommendation Model

With the sharp increasing volume of user data, Deep Learning Recommendation Model (DLRM) becomes an indispensable infrastructure in large technology companies. However, large-scale DLRM on the multi-GPU platform is still inefficient due to unbalanced workload partitioning and intensive inter-GPU communication. To this end, we propose OPER, an OPtimality guided Embedding table placement for large-scale Recommendation model training and inference. OPER explores the potential of mitigating remote memory access latency in DLRM through fine-grained embedding table placement. Specifically, OPER proposes a theoretical modeling that builds up the relationship between EMT placement and the embedding communication latency in both training and inference. OPER proves the NP hardness of finding the optimal embedding table placement and proposes a heuristic algorithm that yields near optimal placement. OPER implements a SHMEM-based embedding table training system and a unified embedding index mapping to support fine-grained embedding table sharding and placement. Comprehensive experiments reveal that OPER achieves on average 3.4× and 5.1× speedup on training and inference respectively over state-of-the-art DLRM frameworks.

Wang, Zheng↗

DOE OSTI2025

Large Neutrino "Collider"

We propose using current and future large-volume neutrino telescopes as ``Large Neutrino Colliders" (L$ν$Cs) to explore TeV-scale physics beyond the Standard Model. Cosmic neutrinos with energies above 100 PeV colliding with nucleons in the detector reach center-of-mass energies beyond the 14 TeV limit of the Large Hadron Collider (LHC). Using recently predicted and measured high-energy and ultra-high-energy neutrino fluxes from IceCube and KM3NeT, we estimate mass-scale sensitivities for representative new physics scenarios at 1--30 km$^3$ L$ν$Cs. Our results demonstrate that L$ν$Cs provide a novel avenue to probe multi-TeV particles with sensitivities comparable to, or even surpassing, those of the LHC.

Bai, Yang [Wisconsin U., Madison; Argonne]↗

DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗

DOE OSTI2026

Alpha-Imaging Detector System Development for Large Area Monitoring

Effective management and disposal of legacy nuclear waste are essential for ensuring safe work environments and minimizing environmental impacts. Monitoring airborne actinide contamination is particularly critical due to the high internal dose potential of alpha-emitting radionuclides. Traditional continuous air monitoring systems (CAMs) used in the industry are limited in the volume of air they can sample, potentially leading to inaccurate radiation detection over large areas. For example, in 2018, elevated levels of airborne Plutonium-239 were detected beyond the controlled areas of the Hanford Plutonium Finishing Plant, highlighting the potential risks to both plant workers and nearby residents. To address these challenges, high-efficiency particulate absorbing (HEPA) air purifiers can enhance air flow by up to 1.5 orders of magnitude, thereby increasing monitoring efficiency and providing a cost-effective solution for large-area surveillance. To quantify the activities of alpha-emitting radionuclides on HEPA filters, the Savannah River National Laboratory is developing an advanced alpha-imaging detection system. This system includes scintillating materials combined with a digital scientific camera. A significant concern in operating such a large-area airborne monitoring system is the handling of HEPA filters, which may be contaminated with radioactive particles. To mitigate these hazards, it is crucial to ensure that any contamination is securely fixed onto the filters. Efforts have been made to optimize the sensitivity of scintillator-epoxy composites and apply them to HEPA filters. These materials were characterized using fluoroscence spectroscopy. These techniques confirmed the purity of the raw materials, the dispersion of scintillators in the epoxy matrix, and the stability of their optical and structural properties post-modification. The optimal scintillator-epoxy composite was selected for use on alpha-spiked HEPA filters to evaluate the efficiency of the sprayer. HEPA filters, embedded with alpha particles collected by an air purifier deployed in an airborne radiation area, have been tested to assess detection efficiency. Future work will focus on employing multiple imaging sensors simultaneously to enhance sensitivity across different regions of the HEPA filter.

Pham, Phuong [Savannah River National Laboratory (↗