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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements

The overall vision of this project is to provide ownership and support for maintaining existing material-based hydrogen storage systems models. This includes making models accessible to the research community through a public web page and updating and enhancing storage systems models to support material developers in assessing their materials relative to DOE vehicle-level targets. Key elements for FY24: Continue to update and enhance existing models for broader application and user-friendliness. Develop tools to evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. Expand the application of current hydrogen storage models beyond light-duty vehicles to include medium-, heavy-duty, and mining vehicles and stationary application(s). Develop models for alternatives, such as LOHCs, to material-based systems (liquefied & gaseous H2) and compare for various mobile and stationary use cases.

ENERGY STORAGE,HYDROGEN↗
DOE OSTI2022

Performance of $\text{BDX-MINI}$ veto systems

Here this paper describes the veto system of the BDX-MINI detector installed at Jefferson Lab (US). The BDX-MINI experiment is the first electron beam-dump experiment specifically designed to search for Light Dark Matter (LDM) particles in the MeV-GeV mass range. The core of the BDX-MINI detector is a lead-tungstate electromagnetic calorimeter, for a total volume of 4 dm 3 . The calorimeter is surrounded by a multi-layer veto aimed at rejecting cosmic background: the innermost layer of the veto is made by a passive tungsten shielding for low energy radiation, while plastic scintillators make the middle and outer layers for charged cosmic particles rejection. Being located about 20 m downstream, the dirt between the beam dump and the detector provides sufficient shielding from the beam-related background. In 2019–2020, BDX-MINI was exposed for about six months to weakly interacting particles (neutrinos and, if existing, DM) produced by a 2.176 GeV electron beam incident on the beam dump of experimental Hall-A at Jefferson Lab.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Ultra-Light Hybrid Composite Door Design, Manufacturing and Demonstration

New Corporate Average Fuel Economy regulations require improved fuel efficiency of the future vehicle fleet. Weight reduction is key to achieving these targets. Replacing metallic body and chassis components with carbon fiber-reinforced composites offers the most weight reduction potential at up to 70%. Introduction of the BMW i3 and i8 in 2014 required mass production processes to meet 20,000+ units per year. Preforming with High Pressure Resin Transfer Molding has been implemented and meets rate, cost, and performance requirements. We will advance these technologies to develop an ultra-light driver’s side door for the vehicle with production rates of 40,000 units annually per plant in Detroit, Michigan. This project sought to employ a comprehensive systems approach for designing, manufacturing, and demonstrating an ultra-light hybrid composite automotive door. Composite structural components are integrated with other functional systems to reduce part count and full-system weight by a minimum of 42.5%. The approach will be demonstrated on a driver’s- side front door and will consider all fit, functional, safety, and cost requirements. These concepts will be evaluated using structural and crash simulations and linked to a manufacturing feasibility study, resulting in producible designs of an integrated door system. A cost model will evaluate part of the cost for the various designs and will ensure the cost target of less than $5 per pound of weight saved is met. Hybrid composites consisting of carbon, glass, and metal components will be included in our trade-off studies to satisfy these cost and performance goals.

02 PETROLEUM↗
DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗
DOE OSTI2023

Maritime Fuel Cell Generator Project: 2018 – 2023

This report summarizes activity in the Maritime Fuel Cell (MarFC) Generator Project from 2018 – 2023. FY 2018 saw the implementation of upgrades and repairs, making the unit more reliable and operator friendly. In FY2019 the team engaged the Scripps Institution of Oceanography (SIO) to use the MarFC to provide zero-emission shore power to the research vessel R/V Robert Gordon Sproul while in port at the Nimitz Marine Facility in San Diego, CA. In FY2020, the MarFC unit was shipped to San Diego, CA. A fueling contract with IGX was established to support MarFC operations at SIO, with renewable hydrogen provided by the California State University Los Angeles (CSULA) hydrogen station. The project team (Sandia, Cummins/Hydrogenics) provided training to SIO staff on the technical details of the MarFC, the safe use of hydrogen in general and the MarFC in particular. The first fueling of the unit at the SIO pier was successfully completed by IGX. The first powering of a vessel with fuel-cell shore power was conducted with the R/V Robert Gordon Sproul. While the mechanical systems (lights, AC, ventilation, hydraulics, pumps and cranes) were powered without incident, problems arose when powering the computer systems. Inspections carried out in FY2021 revealed the MarFC needed routine maintenance. Maintenance was performed and the unit was upgraded. The MarFC was turned on after the year pause, and initial test data on power levels and stability were collected. FY2022 was a year spent repairing, upgrading and testing the MarFC unit. Spikes in power and voltage were observed above 60 kW that could potentially extend below 60 kW with time. Such spikes could cause problems with the Sproul electrical systems. These age-related problems, the extended time for the Sproul spent in dry dock for scheduled upgrades, and the associated need to reschedule the vessel’s high-priority science missions made it no longer possible to deploy the unit at SIO. After due consideration, the decision was made by DOE, MARAD and the project team to cease the deployment, remove the MarFC from SIO, and not pursue further deployment activities. On December 2, 2022, the MarFC unit was removed from the Scripps Nimitz Marine Facility and shipped to Fridley, Michigan. The Cummins/Hydrogenics plan for the unit is to assess the condition of the MarFC subcomponents, and then use it as a training/learning system for technical employees new to hydrogen fuel-cell technology. After summarizing project activity from 2018 – 2023, this report provides a review of lessons learned. This report provides next steps in contemplating a follow-on project that would further advance the use of fuel-cell-based shore power in a marine setting. A comparison is made of the project results to the original objectives. This report ends with an accounting of presentations stemming from the project, and a list of references.

08 HYDROGEN↗
DOE OSTI2023

When Spectral Modeling Meets Convolutional Networks: A Method for Discovering Reionization-era Lensed Quasars in Multiband Imaging Data

Over the last two decades, around 300 quasars have been discovered at z ≳ 6, yet only one has been identified as being strongly gravitationally lensed. We explore a new approach—enlarging the permitted spectral parameter space, while introducing a new spatial geometry veto criterion—which is implemented via image-based deep learning. We first apply this approach to a systematic search for reionization-era lensed quasars, using data from the Dark Energy Survey, the Visible and Infrared Survey Telescope for Astronomy Hemisphere Survey, and the Wide-field Infrared Survey Explorer. Our search method consists of two main parts: (i) the preselection of the candidates, based on their spectral energy distributions (SEDs), using catalog-level photometry; and (ii) relative probability calculations of the candidates being a lens or some contaminant, utilizing a convolutional neural network (CNN) classification. The training data sets are constructed by painting deflected point-source lights over actual galaxy images, to generate realistic galaxy–quasar lens models, optimized to find systems with small image separations, i.e., Einstein radii of θ E ≤ 1''. Visual inspection is then performed for sources with CNN scores of P lens > 0.1, which leads us to obtain 36 newly selected lens candidates, which are awaiting spectroscopic confirmation. These findings show that automated SED modeling and deep learning pipelines, supported by modest human input, are a promising route for detecting strong lenses from large catalogs, which can overcome the veto limitations of primarily dropout-based SED selection approaches.

High-redshift galaxies↗
DOE OSTI2021

Modeling Savings for ENERGY STAR Smart Home Energy Management Systems

The objective of this study was to develop a repeatable and defensible methodology to analyze the energy savings for Home Energy Management Systems (HEMS) that meets the minimum requirements for certification under ENERGY STAR ® Smart Home Energy Management System (SHEMS) Version 1. Mandatory connected loads include a smart thermostat, two smart lights, and one smart power strip or smart outlet. Control strategies must include feedback to occupants through an in-home display, user programming, occupancy sensor-based controls, and responsiveness to utility signals such as demand response programs. Several occupant behavior patterns were selected to quantify the range of energy savings potential for a HEMS with this basic functionality. A literature review was conducted to establish realistic room-by-room occupancy levels and usage patterns for connected devices. A series of event-driven hourly profiles were created, followed by adjustments based on application of HEMS control strategies to thermostats, interior lighting, and plug load schedules. EnergyPlus modeling was performed using these hourly schedules in three locations (Boston, Houston, and Phoenix) to examine climate dependence of energy savings. Total site energy savings ranged from 4.3 to 27.1 MBtu/year (7%-35%), and utility bill savings ranged from $\$$123 to $\$$670/year (6%-29%). The highest predicted savings was realized by occupants that were not energy conscious prior to HEMS installation, but highly engaged with the HEMS controls once the system was installed. The smart thermostat accounted for most of the savings, followed by the smart power strip. Smart lighting did not save a significant amount of energy in our analysis, based on an assumption that efficient LEDs with no standby power would normally be installed anyway.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Tantalum Experiments in Fully-Reflected Water-Moderated Triangular-Pitched U(6.90)O 2 Fuel Rod Lattices (1.02 cm Pitch)

The United States (US) Department of Energy (DOE) Nuclear Energy Research Initiative funded the design and construction of the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories (SNL). The start-up of the experiment facility and the execution of the experiments described here were funded by the DOE Nuclear Criticality Safety Program. The 7uPCX is designed to investigate critical systems with fuel for light water reactors in the enrichment range above 5 % 235 U. The 7uPCX assembly is a water moderated and — reflected array of aluminum-clad U(6.90 %)O 2 fuel rods. Other critical experiments performed in the 7uPCX assembly are documented in LEU-COMP-THERM-078, LEU-COMP-THERM-080, LEU-COMP-THERM 096, LEU- COMP-THERM-097, LEU-COMP-THERM-101, LEU-COMP-THERM-102, and LEU-COMP-THERM-111. Applied interests in neutron-absorbing elements at epithermal and intermediate neutron energy ranges at DOE’s Hanford Site and Savannah River Site were identified through DOE Office of Environmental Management (EM) workshops and needs surveys performed in conjunction with the National Nuclear Security Administration/Nuclear Criticality Safety Program. In response, a team lead by Oak Ridge National Laboratory (ORNL) performed a study evaluating the use of 7uPCX for testing the epithermal cross sections of materials at SNL. This marked the inception of the set of experiments described here. The purpose of these experiments was to measure the effects of tantalum in nearly-critical systems. The tantalum was introduced into the fuel arrays as experiment rods within a central test region. The central test region was designed to target the epithermal neutron energy range by providing a dry cylindrical cavity constructed of aluminum and lined with 0.04 in (0.1016 cm) thick cadmium sheet. The central test region has an outer diameter of 3.75 in (9.525 cm) length of 31 in (78.74 cm) and can hold 85 tantalum rods nominally 0.25 in (0.635 cm) outside diameter and 31.25 in (79.375 cm) long. The critical experiments were done using a set of triangular-pitched grid plates fabricated for these experiments. The grid plate set accommodated a fuel array of a total of 2016 fuel rod positions on a pitch of 0.4 in (1.016 cm) in a series of 21 hexagonal rings positioned around the central test region. The fuel used in these experiments was fabricated using unirradiated 6.90 % enriched UO 2 fuel pellets from fuel elements designed to be used in the internal nuclear superheater section of the Pathfinder boiling water reactor operated in South Dakota by the Northern States Power Company in the 1960s. The fuel elements were obtained from The Pennsylvania State University where they had been stored for many years. The fuel pellets in those fuel elements were removed from the original Incoloy cladding and reclad in 3003 aluminum tubes and end caps for use in the experiments reported here. The eight cases in this experiment series were performed in 2024 in the Sandia Critical Experiments (SCX) at the Sandia Pulsed Reactor Facility by varying the number of fuel rods in the critical assembly. The personnel involved in conducting these experiments included David Ames, Elijah Lutz, Beth Hanson, Patrick Ward, Jason Soares, and Augie Chapa from SNL, as well as Mathieu Dupont and B.J. Marshall from ORNL. Case 1 had no tantalum experiment rods. Case 2 had seven tantalum rods in the center of the central test region. Case 3 had 18 tantalum rods in the third hexagonal ring of the central test region. Case 4 had 19 tantalum rods in the center of the central test region. Case 5 had 30 tantalum rods in the outer most positions of the central test region. Case 6 had 37 tantalum rods in the center of the central test region. Case 7 had 61 tantalum rods in the center of the central test region. Case 8 had 85 tantalum rods filling all positions in the central test region. All eight critical experiments are judged to be acceptable as benchmark experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Risk-Informed and Performance-Based Evaluation of Defense-in-Depth Adequacy

This document supports the work contained in Nuclear Energy Institute (NEI) 18-04 “Risk-Informed Performance-Based Technology Inclusive Guidance for Advanced Reactor Licensing Basis Development” Revision 0. NEI 18-04 presents a modern, technology-inclusive, risk-informed, and performance-based (TI-RIPB) process for selection of Licensing Basis Events (LBEs); safety classification of structures, systems, and components (SSCs) and associated risk-informed special treatments; and determination of defense-in-depth (DID) adequacy for non-LWRs. The NEI guidance document provides one acceptable means for addressing the aforementioned topics as part of demonstrating a specific design provides reasonable assurance of adequate radiological protection. This report provides the framework and associated methodology guidelines and discussion for establishing, then evaluating, confirming, and documenting the adequacy of defense-in-depth (DID) for advanced non-light-water reactor technologies. It was developed as part of the Licensing Modernization Project led by Southern Company and cost-shared by the United States Department of Energy and has benefited from considerable NRC formal reviews and public workshops. The methodology converts the DID philosophy into a structured process that is implementable, embraces existing United States and international definitions and philosophies of DID that set the foundation for the process. It builds on the DID framework developed in the Department of Energy Next Generation Nuclear Plant Project and earlier works on this subject. The approach to establishing DID adequacy involves the incorporation of DID attributes into the plant capabilities and programmatic elements of DID. The integrated evaluation of DID adequacy includes both quantitative elements to incorporate risk-informed and performance-based (RIPB) considerations and qualitative elements that address uncertainties and limitations in the quantitative models and supporting data. Demonstration of DID adequacy ensures that there are multiple layers of defense for risk-significant challenges to the design and that the plant capabilities and programs that support each layer are provided in a manner that minimizes dependencies among these layers. The focus of this report is assurance of DID adequacy with respect to protection of the public from radiological exposures resulting from accidental releases of radioactive material. While other hazards are not specifically addressed, this methodology is expected to be beneficial for determining DID adequacy for them as well. Risk-informed evaluation of DID considers the integrated performance of all plant SSCs and associated programs to manage daily operational activities, transients, and accidents, including the evaluation of strategies for accident prevention and mitigation. The RIPB LBE scenario methodology used in this evaluation defines the challenges to the plant safety features included in the plant design basis and beyond, and the scope of all deterministic and probabilistic safety evaluations. By examining event sequences across the whole spectrum of LBEs, a systematic assessment of DID can be accomplished.

42 ENGINEERING↗
DOE OSTI2021

Xenon doping of Liquid Argon in ProtoDUNE Single Phase: first results

Doping Liquid Argon (LAr) with xenon is a known technique to shift the light emitted by argon (128 nm) to a longer wavelength to ease its detection. The largest Xenon doping test ever performed in a LArTPC was carried out in ProtoDUNE Single Phase (ProtoDUNE-SP) at the CERN Neutrino Platform. The response of such a large TPC (7701 of Liquid Argon and 4401 of fiducial mass) has been studied using the ProtoDUNE Photon Detection System (PDS) and a dedicated setup installed before the run. With the first, it was possible to study the light detected in the system as a function of the xenon concentration and to characterise the light collection efficiency with respect to the track position. With the second system it was possible to disentangle the LAr (128 nm) light from the xenon (178 nm) light using two dedicated X-ARAPUCA modules. The run was fully satisfactory, it was possible to measure directly the increase of the xenon light component during doping; furthermore most of the LAr light quenched by impurities was fully recovered even at small Xenon concentration (< 20 ppm in mass). A study of the collected scintillation light as a function of the track position showed an improvement of the detector response uniformity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Excitation energy transfer in proteoliposomes reconstituted with LH2 and RC-LH1 complexes from Rhodobacter sphaeroides

Abstract Light-harvesting 2 (LH2) and reaction-centre light-harvesting 1 (RC-LH1) complexes purified from the photosynthetic bacterium Rhodobacter (Rba.) sphaeroides were reconstituted into proteoliposomes either separately, or together at three different LH2:RC-LH1 ratios, for excitation energy transfer studies. Atomic force microscopy (AFM) was used to investigate the distribution and association of the complexes within the proteoliposome membranes. Absorption and fluorescence emission spectra were similar for LH2 complexes in detergent and liposomes, indicating that reconstitution retains the structural and optical properties of the LH2 complexes. Analysis of fluorescence emission shows that when LH2 forms an extensive series of contacts with other such complexes, fluorescence is quenched by 52.6 ± 1.4%. In mixed proteoliposomes, specific excitation of carotenoids in LH2 donor complexes resulted in emission of fluorescence from acceptor RC-LH1 complexes engineered to assemble with no carotenoids. Extents of energy transfer were measured by fluorescence lifetime microscopy; the 0.72 ± 0.08 ns lifetime in LH2-only membranes decreases to 0.43 ± 0.04 ns with a ratio of 2:1 LH2 to RC-LH1, and to 0.35 ± 0.05 ns for a 1:1 ratio, corresponding to energy transfer efficiencies of 40 ± 14% and 51 ± 18%, respectively. No further improvement is seen with a 0.5:1 LH2 to RC-LH1 ratio. Thus, LH2 and RC-LH1 complexes perform their light harvesting and energy transfer roles when reconstituted into proteoliposomes, providing a way to integrate native, non-native, engineered and de novo designed light-harvesting complexes into functional photosynthetic systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Physics-Based Optical Neuromorphic Classification

Typical approaches to classify scenes from light convert the light field to electrons to perform the computation in the digital electronic domain. This conversion and downstream computational analysis require significant power and time. Diffractive neural networks have recently emerged as unique systems to classify optical fields at lower energy and high speeds. Previous work has shown that a single layer of diffractive metamaterial can achieve high performance on classification tasks. In analogy with electronic neural networks, it is anticipated that multilayer diffractive systems would provide better performance, but the fundamental reasons for the potential improvement have not been established. In this work, we present extensive computational simulations of two - layer diffractive neural networks and show that they can achieve high performance with fewer diffractive features than single layer systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Advances in Energy Hybridization for Resilient Supply: A Sustainable Approach to the Growing World Demand

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy through combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Optimum Operation of Microgrid Systems that Employ PV Solar and Battery Systems

On a global scale, over 1.3 billion lack access to electricity (85% in rural areas), and approximately 2.8 billion people rely on traditional biomass for cooking. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy by combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

Nagapurkar, Prashant↗
DOE OSTI2025

Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study

The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.

Heavy-ion detectors↗
DOE OSTI2023

Probing turbulence with lasers and coherent light sources

Fluid and plasma turbulence consists of multi-scale interactions where the energy of the large scales is dissipated through a cascade to the smallest scales set by the microphysics. Turbulence and mixing can be detrimental to system performance, such as in inertial confinement fusion (ICF). Our current understanding of turbulence is mostly derived from studies of incompressible flows, where the intermediate-scaled eddies in the “inertial range” bridge the transfer of energy from the large eddies to the dissipative range, and that there is no communication between eddies of disparate scales. Whether a similar cascade process exists for compressible turbulence, however, remains to be seen; experiments have been limited by diagnostics and supersonic flow facilities. This project has focused on the development of techniques to measure the evolution of flows and microphysical transport properties using particle tracking velocimetry. This project has investigated three main areas: (1) particle-tracking experiments with x-ray radiography, (2) shock-particle interactions, (3) quantifying viscous effects on particles in shocked flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

High-Efficiency Solar-To-Fuel Photoelectrochemistry in Disordered Photonic Glass Electrodes (Final Technical Report)

This project investigated how photonic glass (PG) photoelectrodes—disordered arrangements of dielectric scatterers—can serve as scalable, tunable platforms for light trapping in photoelectrochemical (PEC) solar-to-fuel systems. By leveraging disorder-driven optical phenomena such as multiple scattering resonances and light localization, PG structures offer an alternative to conventional photonic crystals and inverse opals that require high structural precision. The scientific goals were to twofold: (1) develop approaches to predictive models for high performance PG electrodes based on light absorption simulations, and (2) fabricate, characterize, and optimize PG-based photoelectrodes for solar-to-hydrogen and solar-to-fuel photoelectrochemical applications. To overcome the complexity of ensemble optical simulations for disordered materials, the researchers developed a machine-learning-accelerated emulation of all configurations in the design space. With this approach, PG photoelectrodes based on a TiO2 semiconductor were designed to enhance PEC currents of up to one hundred times higher than the equivalent ultra-thin film photoanodes and several times higher than the equivalent photonic crystal. The research also explored integrated systems for electrochemical hydrogen production based on replacing water oxidation with the specific glycerol oxidation electrocatalysis. Overall, the project outlined an approach to a simple-to-fabricate photoelectrode system to drive photoelectrochemical reactions relevant to solar photochemical energy conversion.

14 SOLAR ENERGY↗
DOE OSTI2023

Using the Gerchberg-Saxton algorithm to reconstruct nonmodulated pyramid wavefront sensor measurements

Adaptive optics (AO) is a technique to improve the resolution of ground-based telescopes by correcting, in real-time, optical aberrations due to atmospheric turbulence and the telescope itself. With the rise of Giant Segmented Mirror Telescopes (GSMT), AO is needed more than ever to reach the full potential of these future observatories. One of the main performance drivers of an AO system is the wavefront sensing operation, consisting of measuring the shape of the above mentioned optical aberrations. Aims. The non-modulated pyramid wavefront sensor (nPWFS) is a wavefront sensor with high sensitivity, allowing the limits of AO systems to be pushed. The high sensitivity comes at the expense of its dynamic range, which makes it a highly non-linear sensor. We propose here a novel way to invert nPWFS signals by using the principle of reciprocity of light propagation and the Gerchberg-Saxton (GS) algorithm. We test the performance of this reconstructor in two steps: the technique is first implemented in simulations, where some of its basic properties are studied. Then, the GS reconstructor is tested on the Santa Cruz Extreme Adaptive optics Laboratory (SEAL) testbed located at the University of California Santa Cruz. This new way to invert the nPWFS measurements allows us to drastically increase the dynamic range of the reconstruction for the nPWFS, pushing the dynamics close to a modulated PWFS. The reconstructor is an iterative algorithm requiring heavy computational burden, which could be an issue for real-time purposes in its current implementation. However, this new reconstructor could still be helpful in the case of many wavefront control operations. In conclusion, this reconstruction technique has also been successfully tested on the Santa Cruz Extreme AO Laboratory (SEAL) bench where it is now used as the standard way to invert nPWFS signal.

47 OTHER INSTRUMENTATION↗