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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comparison of wind-farm control strategies under realistic offshore wind conditions: wake quantities of interest

Wind-farm control strategies aim to increase the efficiency, and therefore lower the levelized cost of energy, of wind farms. This is done by using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the wake that negatively affects downstream turbines in the farm. Two inherently different wind-farm control methods have been identified in the literature: wake steering (WS) and active wake mixing (AWM). As one of two companion papers focused on understanding practical aspects of these two wind-farm control strategies using large-eddy simulation (LES), we below analyze the wake quantities of interest for a single wind turbine performing WS and AWM, while the companion article (Frederik et al., 2025) focuses on turbine quantities of interest including power and structural loads for the same computational setup and also includes two-turbine arrays with full and partial wake overlap. The simulations, which are based in the LES solver AMR-Wind, are tailored to have inflow conditions representative of measurements from a site off the East Coast of the US, including with strong veer and low turbulence. The turbine, which is modeled in OpenFAST and coupled to the LES, is the IEA 15 MW, an open-source offshore design. After presenting an overview of the wake recovery for the different wake-control cases, the analysis probes the fluid-dynamic causes for the different performance of the arrays reported in the companion article by examining control volumes around the wakes and the budget of the mean-flow kinetic energy (MKE) within these volumes. In the high veer environment considered, the MKE recovery is dominated by mean convection, and this is shown to especially benefit the WS strategy when a neighboring turbine is directly downstream: there is ≈65 % more available power for a downstream turbine than in the baseline case, and this power is gained primarily through mean convection on the left-tip and top-tip faces of the control volume. However, the case with imperfect knowledge of the exact wind direction favors the pulse-type AWM strategy, largely because of ≈9 % increased turbulent entrainment from aloft versus the baseline that could be related to an apparent resistance to skewing in the pulsed wake. The general reduced effectiveness of helix-type and other individual-pitch-based AWM strategies for inflow with high veer and low turbulence as reported in the companion paper is due, in part, to low magnitudes of phase-averaged turbulent entrainment. Two main findings of this study are thus that veer has a significant impact on the effectiveness of different wake-control strategies and that pulse-type AWM may be a useful strategy when the objective is power maximization in realistic, offshore flow environments with imperfect knowledge of the exact wake overlap position on the downstream turbine.

17 WIND ENERGY↗
DOE OSTI2026

Mitigating Data Center Impact on Grid Stability: A Coordinated Control Strategy Using Verrus StabiliGrid Architecture

Large data centers, which now represent a significant and growing share of the total U.S. grid load, can inadvertently destabilize the electrical grid when they disconnect simultaneously during brief voltage disturbances. The July 10, 2024, Eastern Interconnection incident, in which a sub-100-millisecond transmission fault triggered the cascading loss of approximately 1,500 MW of data center load, illustrates this vulnerability. While commercial battery energy storage systems (BESS) deployed in data centers provide device-level fault ride-through per IEEE 1547, they lack coordination with facility protection logic and uninterruptible power supplies (UPS), limiting their effectiveness as grid-stabilizing assets. This report presents the Verrus StabiliGrid architecture, a coordinated control framework that integrates BESS, UPS, and point-of-interconnection (POI) protection settings to enable data centers to ride through both undervoltage and overvoltage grid contingencies without disconnecting. The four-step strategy encompasses: (1) high-resolution power quality monitoring to detect the grid state during events such as undervoltage, overvoltage, underfrequency, and overfrequency; (2) POI protection settings that allow for extended ride-through and grid-connected operation during grid contingencies; (3) grid state-driven autonomous dispatch of assets to improve grid resilience by reducing power draw during undervoltage or absorbing more power during overvoltage events; and (4) coordinated post-recovery dispatch of data center assets to restore firm load to pre-contingency levels. Validated through controller-hardware-in-the-loop (C-HIL) simulations at the National Laboratory of the Rockies, results show grid import restoration to pre-fault levels within 100 milliseconds of voltage recovery. This work advances the ability of data centers to transition from passive, disturbance-sensitive loads to active participants in grid stability, a capability increasingly required by emerging NERC and ERCOT regulatory frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

From IMT Device Measurements to Network-Level Consequences: When Learning Suppresses Beyond-LIF Neuron Dynamics

Emerging neuromorphic devices such as insulator--metal transition (IMT) devices exhibit complex temporal dynamics, including slow internal state memory, hysteresis, and burst-like firing, which are poorly captured by conventional leaky integrate-and-fire (LIF) neurons. However, it remains unclear when such dynamics influence learning and inference at the network level, particularly under commonly used unsupervised plasticity rules. We present a controlled, full-stack co-design study spanning experimental characterization of individual IMT devices, compact neuron model development, and large-scale spiking network simulations with identical architectures and learning rules. Rather than optimizing benchmark accuracy, our goal is to diagnose when neuron-level dynamics survive learning and competition, and when they are suppressed, to inform the co-design of devices, networks, and learning rules that can exploit beyond-LIF complexity.

42 ENGINEERING↗
DOE OSTI2024

Dual blockade of IL-10 and PD-1 leads to control of SIV viral rebound following analytical treatment interruption

Human immunodeficiency virus (HIV) persistence during antiretroviral therapy (ART) is associated with heightened plasma interleukin-10 (IL-10) levels and PD-1 expression. We hypothesized that IL-10 and PD-1 blockade would lead to control of viral rebound following analytical treatment interruption (ATI). Twenty-eight ART-treated, simian immunodeficiency virus (SIV)mac 239 -infected rhesus macaques (RMs) were treated with anti-IL-10, anti-IL-10 plus anti-PD-1 (combo) or vehicle. ART was interrupted 12 weeks after introduction of immunotherapy. Durable control of viral rebound was observed in nine out of ten combo-treated RMs for >24 weeks post-ATI. Induction of inflammatory cytokines, proliferation of effector CD8 + T cells in lymph nodes and reduced expression of BCL-2 in CD4 + T cells pre-ATI predicted control of viral rebound. Twenty-four weeks post-ATI, lower viral load was associated with higher frequencies of memory T cells expressing TCF-1 and of SIV-specific CD4 + and CD8 + T cells in blood and lymph nodes of combo-treated RMs. These results map a path to achieve long-lasting control of HIV and/or SIV following discontinuation of ART.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2024

ROADRUNNER MiniFuel Experiment: Irradiation Target Design and Sample Characterization

High-density uranium nitride (UN) is a fuel candidate for several advanced nuclear reactor designs currently under development. Because there are limited UN performance data relative to fuel fabrication impurity and density variation, an irradiation campaign has been developed as part of a collaborative effort among the University of Texas at San Antonio (UTSA), Westinghouse Electric Company, Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL) under the Nuclear Science User Facilities program. This project, entitled ROADRUNNER, or Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments, aimsto support UN fuel qualification for advanced reactors by investigating the impact of density and impurity variations on UN performance as a function of irradiation temperature and burnup. The MiniFuel experiment vehicle developed by ORNL, which leverages the High Flux Isotope Reactor, was selected to perform this accelerated separate-effects irradiation testing. The experiment test matrix consists of six MiniFuel targets containing miniature UN fuel disks, and targets three distinct burnup levels (37.5, 60, and 75 MWd/kg U) and three distinct temperatures (600, 900, and 1200°C). Neutronics and thermal analyses were performed to determine the experimental parameters needed to meet the desired irradiation conditions and to predict the experiment components temperatures. UN pellets were fabricated at LANL with tightly controlled parameters to produce specimens with three distinct densities and three levels of carbon content. The pellets were then thinned down by UTSA to the experiment-required thickness. The pre-characterization of the specimens includes density measurements, carbon and oxygen contents, microstructure analysis, and x-ray computed tomography. The selected specimens will be assembled into the MiniFuel experiment, and the first ROADRUNNER MiniFuel targets are intended for HFIR insertion during the Fall of 2024. After irradiation, the targets will be shipped to ORNL’s hot cell facility for disassembly. The post-irradiation examination on the fuel specimens includes fission gas release measurements, visual inspection, fuel swelling measurements, gamma spectroscopy, and microstructure analysis. The data collected post-irradiation will be used to develop fuel performance models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Graphite crystals in catalytically-graphitized glass-like carbon

Catalytic graphitization of glass-like carbon leads to enhanced growth of micro-sized graphitic crystals with unusual shapes of wires, filaments, tubes, rods, whiskers, and spirals. Similar particles with axial symmetry are also found in pure glass-like carbon heat-treated at high temperatures. Nonetheless, the presence of a graphitization catalyst, Si in this case, in the heat-treatment process supports the transformation of porous, disordered carbon structure towards the graphitic atomic order and the formation of manifold peculiar polyhedral wires and particles of geometry distinct from the plate-like shape typical for conventional graphite. In contrast to conventional carbon nanotubes and fibers, the graphene layers are stacked perpendicular to the tube axis, while the size of the most common tube fibers can reach up to 10 μm in diameter and 100 μm in length. X-ray diffraction, Raman spectroscopy, scanning and transmission electron microscopy, small-angle X-ray scattering combined with complementary techniques have been used to characterize the structure of the glass-like carbon derived from furfuryl alcohol catalytically-graphitized using Si particles at 3000 °C. Finally, since control of graphite shape is vital to achieving the level of performance required in contemporary applications, the obtained results demonstrate that the catalytic graphitization method may be employed to produce filamentous graphite crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Evaluating the role of green infrastructure features in post-disaster recovery – Case Study of Beaumont, Texas after tropical storm imelda

While green infrastructure (GI) can provide multiple environmental benefits, its role in post-disaster economic and social recovery remains relatively underexplored. This article investigates whether different characteristics of GI, such as size, shape, connectivity, and amenities, affect the resilience of local businesses following Tropical Storm Imelda in Beaumont, Texas. The study utilizes SafeGraph mobility data to analyze foot traffic patterns to local businesses before, during, and after the disaster. FRAGSTATS indices measure GI characteristics (e.g., area, shape index, fractal dimension, proximity) while park features such as sports facilities, playgrounds, water features, and accessibility are cataloged through manual observation. Ordinary Least Squares regression models assess the relationship between park characteristics and post-recovery business performance, controlling for demographic variables including income, race, and poverty levels. Results indicate that certain GI attributes significantly enhance business recovery. Points of interest within walking distance (0.5 miles) of parks demonstrated better post-recovery status compared to those beyond this range. Specifically, parks with larger areas (p < 0.01) and more complex shapes measured by fractal dimension index (p < 0.01) had the strongest positive impact on surrounding businesses' recovery. Interestingly, playgrounds showed a negative correlation with recovery (p < 0.05), likely due to flood damage rendering them unusable during the immediate recovery period. Social vulnerability factors, including higher poverty rates and minority populations, negatively affected recovery outcomes despite park proximity.

Economic resilience↗
DOE OSTI2026

Shining a Light on Some Fundamental Research Opportunities in Semiconductor Photoelectrochemistry

Decades of research in semiconductor photoelectrochemistry have yielded a deep understanding of charge transfer, energetics, and stability at solid−liquid interfaces. Theoretical frameworks developed by Gerischer and contemporaries, together with extensive experimental validation, have clarified the key principles affecting the interfacial kinetics and energetics of semiconductor photoelectrodes. Nevertheless, significant opportunities remain for advances in fundamental understanding of semiconductor photoelectrochemistry. Exciting opportunities include exploiting advances in theory, synthesis, and instrumentation to determine the chemical identity and reactivity of surface states; exerting control of band-edge energetics through molecular-level surface modification processes; and systematically improving emerging photoelectrode protection strategies to enable long-term photoelectrode operation under both oxidative and reductive conditions. Advanced morphologies, such as nanowire and microwire arrays, present new pathways to combine efficient light absorption with effective charge collection and catalyst integration. Unique light−matter interactions during photoelectrochemical deposition of p-type semiconductors readily allow preparation at scale of complex 3D morphologies that are difficult, if not impossible, to access by other methods. Continued exploration of these avenues will expand the fundamental understanding of semiconductor−liquid interfaces and could additionally advance the realization of efficient, stable, and scalable systems for solar fuel generation and other emerging photoelectrochemical applications.

Bean, Paul J. L. [California Institute of Technolo↗
DOE OSTI2025

Magnetic Properties Tuning via Broad Range Site Deficiency in Square Net Material UCu x Bi 2

HfCuSi 2 -type pnictogen compounds have recently been shown to be a versatile platform for designing materials with topologically nontrivial band structures. However, these phases require strict control over the electron count to tune the Fermi level, which can only be achieved in compositions with A 2+ M 2+ Pn 2 and A 3+ M + Pn 2 (A = lanthanides, M = transition metals, Pn = pnictogens P–Bi) charge distribution. While such lanthanide compounds have been thoroughly studied as candidate magnetic topological materials, their heavy element analogs with uranium and bismuth remain largely underexplored. In this report, we present the synthesis of UCu x Bi 2 single crystals and study their magnetic properties. Detailed structural analysis revealed that flux-grown crystals always form as a site-deficient UCu x Bi 2 composition, where x varies between 0.20 and 0.64. Magnetic property measurements revealed a dependence of the magnetic coupling on the Cu site deficiency, linearly changing the Néel temperature from 51 K for UCu 0.60 Bi 2 to 118 K for UCu 0.30 Bi 2 . Moreover, higher Cu concentration promotes a metamagnetic transition in highly magnetically anisotropic UCu 0.60 Bi 2 single crystals. We show that DFT calculations can successfully model site deficiency in the UCu x Sb 2 and UCu x Bi 2 systems. This work paves the way toward using the site deficiency to tune the Fermi level in more ubiquitous A 3+ M 2+ x Pn 2 phases, which previously have not been considered topological candidate materials due to unfavorable electron count.

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

TRISO Fuel’s Safety Functions, Contributions to Reactor Safety, and Necessary Safety Limits

Safety functions are the actions, passive or active, that structures, systems, and components of nuclear facility that contribute to the safety of the workers, the public, or the environment. Well-defined safety functions are the foundation of a solid safety case for a reactor. For reactors that use TRISO-coated particles, the TRISO fuel plays an important part of the safety case because of its ability to contain radionuclides in the fuel itself. This ability enables the use of a functional containment strategy for the reactor where radionuclide retention is the primary safety function supported by the safety functions of controlling reactivity control and controlling heat rejection. This paper establishes at a deeper level the role that TRISO fuel plays in each of these safety functions and associated quality assurance and testing requirements for TRISO particle manufacturing to ensure these safety functions. Safety limits necessary to protect these safety functions include: operational limits, time at temperature limits, and fission gas release activity limits. In conclusion, this approach demonstrates the role that specific aspects of TRISO fuel play in protecting the safety of workers, the public, and the environment.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Single-molecule infrared spectroscopy with scanning tunneling microscopy

Probing vibrations at the single-molecule level is essential for achieving bond-specific chemical control in realistic heterogeneous environments. Here, we introduce a new measurement scheme that integrates frequency-tunable infrared excitation with scanning tunneling microscopy to characterize vibration-mediated nuclear motions of single molecules. We first validated the technique by monitoring the infrared-induced rotation of the ethynyl radical and then applied it to mapping pyrrolidine’s conformational dynamics. The resulting broadband spectra captured fundamental vibrational modes together with rich overtone and combination bands inaccessible by conventional methods, which we confirmed with isotopic substitutions. Density functional theory calculations showed that delocalized modes coupled with pyrrolidine ring puckering drive the structural transition, revealing altered selection rules compared with traditional infrared spectroscopy. Here, this new experimental platform enables molecular vibrations and transformations to be probed with atomic precision.

Liang, Kangkai [University of California, San Dieg↗
DOE OSTI2024

Survey of Neutron Flux Sensors for Monitoring Advanced Reactor Concepts Operating with Low Neutron Fluence Rate and Extended Uninterrupted Lifespans

The purpose of this report is to provide a survey of neutron sensors applicable to the low power levels (low neutron fluence rate) for reactor monitoring and controls. A survey of detectors for reactor power monitoring and controls from various commercial vendors—Reuter Stokes, Framatome, Exosens, and Mirion—is presented in the following sections based on application of reactor power ranges. Detector specifications are provided where available per each of the vendor’s catalogues and specification sheets found on their websites. While this is not an all encompassing list, it provides an example of detector options. Fission chambers and self powered neutron detectors (SPNDs) for in-core application with changes to the neutron-sensitive materials—fissile depots for fission chambers and emitters for SPNDs—for regenerative capabilities will be discussed in the latter sections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Quantum Zeno Control of Superconducting Qubit Coherence

The Quantum Zeno Effect (QZE) dictates how the dynamics of a quantum system can be modified through continuous or discrete measurements [1]. It has gained increasing attention in quantum computing community in recent years, both due to its inevitable implications for qubit readout as well as for its promise for enabling new methods of quantum state control such as reservoir engineering and Zeno-dragging. Here, we investigate Zeno effects implemented via weak measurements for controlling superconducting-qubit coherence during gate and readout operations in a multi-qubit setup. Building on prior observations [2] that measurement backaction can both suppress and enhance qubit relaxation, we predict and measure QZE-altered qubit coherence times by manipulating the spectral overlap of qubit spectrum with background noise sources. We also discuss modifications and opportunities for controllable QZE due to anharmonic effects in multi-level superconducting atoms. [1] S. Greenfield, A. Kamal, J. Dressel, E. Levenson-Falk, arXiv:2506.12679 (2025) [2] Thorbeck, Z. Xiao, L. Govia, A. Kamal, Phys. Rev. Lett. 132, 090602 (2024)

Seidel, Olivia [Texas U., Arlington; Fermilab]↗
DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗
DOE OSTI2025

Unfolding Structure Formation in the Dark Universe via Weak Gravitational Lensing: from Pixels to Cosmology in the Dark Energy Survey and Roman Space Telescope

Weak gravitational lensing (deflection of light from distant galaxies due to the gravitational potential of intervening mass) is one of the most exciting probes in cosmology as it is sensitive both to the growth of the large-scale structure and the expansion history of the Universe. We can measure the coherent distortion of galaxy shapes (which we call cosmic shear) and infer the matter distribution. With next-generation imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (Rubin LSST) and the Nancy G. Roman Space Telescope (Roman), there is immense new promise in understanding the fundamental nature of dark matter and dark energy. With datasets from current experiments like the Dark Energy Survey (DES), we see apparent cosmological tensions between experiments that may either be real and indicate new physics or new systematics we do not yet understand. LSST and Roman will increase the number of galaxies we have observed by an order of magnitude, leading to improved constraints on our cosmological model by up to 300%. These experiments will have the potential to prove if these cosmological tensions are real. However, our control of systematic uncertainties must also improve by similar levels to achieve the promise of what these missions can deliver. To achieve these scientific outcomes, the challenges of determining galaxy shapes and redshifts and modeling the impact of astrophysical effects must be solved. My PhD has focused on enabling weak lensing science in DES and Roman. I co-led the shear analysis teams in DES to produce the largest weak lensing galaxy sample, as well as the final DES cosmological analysis of cosmic shear. For Roman, I have led two papers characterizing and mitigating shear-related systematics with image simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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 (↗
DOE OSTI2026

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor

Generation of quantum states of light through off-resonance four-wave mixing in rubidium vapor is a straightforward and well-established technique. However, achieving a sufficiently high and consistent level of intensity difference squeezing (IDS) and intrinsic quantum correlations between photon pairs over an extended timescale, necessary for quantum-light-based nonlinear optical spectroscopy and microscopy, remains challenging and largely unexplored. Here, we report a simple stabilization method combining an active periodic laser frequency retuning with an automatic control algorithm based on quantitatively assessing the factors affecting the IDS level and squeezed light intensity. Validation of our method was performed by acquiring data over a 5-hour period, and the results demonstrate a remarkably stable squeezing level of -7.8 dB in combination with a > 4× reduction of the standard deviation of IDS level from 0.46 dB to 0.10 dB. The achieved stabilization further enables us to quantitatively assess the IDS reduction due to the scattering in a polystyrene bead suspension as a function of sample transmission. Our approach should enable a variety of applications requiring an extended squeezing stability over multiple hours, especially for those following biological processes and chemical reactions in real time.

Allen, Christian Harry [Oak Ridge National Laborat↗