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DOE OSTI2024

Application of Superconducting Cavities as Ultra-Sensitive RF Photon Detectors

Superconducting radio frequency (SRF) cavities are the world’s most efficient engineered oscillators, and they have long been employed for extremely high efficiency transfer of energy to beams of charged particles. Decades of R&D for particle accelerators have led to modern treatments for SRF cavities that achieve higher performance than was previously possible. Advanced SRF cavities using particle accelerator technology are now being used to search for new physics, including dark matter and gravitational waves. The extremely high Q makes it possible to search for very small signals from photons in the radio frequency range, and the extremely high electric fields makes it possible to perform experiments that involve pumping one mode of a cavity in order to search for power transfer mediated by new physics. This talk will present novel experiments that employ SRF cavities, including searches for axions and dark photons dark matter, light-shining-through-walls, and high frequency gravitational waves. Results to be presented include searches with world record sensitivity.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

DOE OSTI2023

Totally chlorine-free peracetic acid pulping for nanocellulose isolation from hemp and poplar

Nanocellulose is a promising and sustainable feedstock for developing advanced and functional materials. However, the characteristics of nanocellulose, such as crystallinity, surface energy, and aspect ratio, can vary depending on biomass source and pretreatment methods, leading to variable performance of the nanocellu-lose-based materials. In this study, cellulose nanocrystals (CNCs) were isolated from hemp and poplar using totally chlorine free (TCF) peracetic acid and sodium chlorite delignification and bleaching pretreatments to probe the influences of biomass source and treatment methods on the isolation and characteristics of CNCs. Our results showed that hemp and poplar were almost completely delignified by peracetic acid treatment, whereas sodium chlorite treatment left 5%–6% lignin in the pulp. The yields of CNCs from raw hemp and poplar biomass ranged from 9.8% to 21.9% and 10.9% to 28.3%, respectively, depending on the treatment methods. The dimensions of CNCs from TCF-treated biomass generally maintained a larger width and aspect ratio than those from sodium chlorite-treated biomass. The poplar-derived CNCs exhibited slightly higher crystallinity of 53%–58% than hemp-derived CNCs of 49%–54%. The zeta potential of the CNCs, ranging from -20.1 mV to -31.1 mV, ensured a well-dispersed aqueous solution. The surface energy (dispersive energy of 40–80 mJ/m2 and specific energy of 2–10 mJ/m2), water interaction, and thermal stability of the CNCs were comparable, regardless of the biomass source and pretreatment methods. Our finding suggests that the TCF technique with peracetic acid treatment is a promising delignification and bleaching approach to obtain cellulose-rich pulps from herbaceous and hardwood biomass for nanocellulose isolation.

09 BIOMASS FUELS↗

NASA NTRS1997

Propellant Technologies: A Persuasive Wave of Future Propulsion Benefits

Rocket propellant and propulsion technology improvements can be used to reduce the development time and operational costs of new space vehicle programs. Advanced propellant technologies can make the space vehicles safer, more operable, and higher performing. Five technology areas are described: Monopropellants, Alternative Hydrocarbons, Gelled Hydrogen, Metallized Gelled Propellants, and High Energy Density Materials. These propellants' benefits for future vehicles are outlined using mission study results and the technologies are briefly discussed.

Palaszewski, Bryan↗

NASA NTRS1998

NASA Advanced Fuels Program

NASA with the USAF Research Laboratory and it's industry partners, has been conducting planning and research into advanced fuels. This work is sponsored under the NASA Advanced Space Transportation Program (ASTP). The current research focus is on Alternative Hydrocarbon fuels, Monopropellants, and Solid Cryogens for storing atoms of Hydrogen, Boron, Carbon, and Aluminum. Alternative hydrocarbons that are under consideration are bi cyclo propylidene, spiro pentane, and tri propargyl amine. These three fuels have been identified as initial candidates to increase the specific impulse of hydrocarbon fueled rockets by 10-15 seconds over 02/RP-1. Formulation of these propellants is proceeding this year, and rocket engine testing is planned for the near future. Monopropellant investigations are focused on dinitramine based fuels, and potential collaborations with the US Navy. The dinitramine fuel work is being conducted under an Small Business Innovation research (SBIR) contract with the team of Orbital Technologies Corp. (Madison, WI) and SRI (Menlo Park, CA). This work may lead to a high density, high specific impulse monopropellants that can simplify the operations for launch vehicles and spacecraft. Solid Cryogens are being considered to store atoms of Hydrogen, Boron, Carbon, and Aluminum. Stored atom propellants are potentially the highest specific impulse chemical rockets that may be practical. These fuels are composed of atoms, stored in solid cryogenic particles, suspended in a cryogenic liquid or gel. The fuel would be fed to a rocket engine as a slurry or gelled cryogenic liquid with the suspended particles with the trapped atoms. Testing is planned to demonstrate the formation of the particles, and then characterize the slurry flows. Rocket propellant and propulsion technology improvements can be used to reduce the development time and operational costs of new space vehicle programs. Advanced propellant technologies can make the space vehicles safer, more operable, and better performing. Five technology areas are described: Monopropellants, Alternative Hydrocarbons, Gelled Hydrogen, Metallized Gelled Propellants, and High Energy Density Materials. The benefits of these propellants for future vehicles are outlined using mission study results and the technologies are briefly discussed.

Palaszewski, Bryan↗

NASA NTRS2024

Determining the Quantum Detection Efficiency of A Soft X-Ray Micro-Channel Plate Detector for the Lunar Mission, LEXI

Micro-channel plate (MCP) detectors have long been a workhorse for space-based x-ray research and are advantageous over other imaging detectors because of their low size, weight and power. The Lunar Environment heliospheric x-ray Imager (LEXI), will utilize a MCP to image Earth’s magnetosphere in soft x-rays from the lunar surface. A critical element for interpreting on-orbit data is to understand the quantum detection efficiency (QDE) of the MCP. LEXI’s MCP is coated with potassium bromide (KBr) to increase the soft x-ray QDE. Historically, few measurements of QDE exist in the soft x-ray band for KBr detectors. This paper reviews the performance of LEXI’s detector, and the QDE experiment procedure conducted at and results from the Advanced Light Source synchrotron soft x-ray beam line (6.3.2) over the energy range 70eV-1300eV. A unique beam line setup was required to limit the photon flux as to not saturate the pores of the MCP or detector signal chain. The experimental results are similar to previous literature, with some caveats unique to this MCP and experimental setup.

X-ray imaging↗

DOE OSTI2019

Simulation of Thermal Spectrum MSR using PROTEUS

In recent years, there has been renewed interest in Molten Salter Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. Given the current interest for MSRs, it is a good opportunity to demonstrate that the advanced tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program are useful for modeling MSRs. In addition, one objective of the program is to develop modeling and simulation capabilities to predict the performance and safety of all types of advanced nuclear reactor. For this study, PROTEUS [1], the primary reactor physics tool within the program, was assessed and used to model one of the preliminary core designs provided by ThorCon, one of the leading MSR companies from industry. The focus of this first step in the modeling and simulation work is to predict the core design’s steady state performance.

Fei, T.↗

DOE OSTI2024

Virtual Test Bed (VTB): NRIC FY24 Program Review

NRIC: Deliver successful demonstration and deployment of advanced nuclear energy EBRII Test Bed (DOME) ZPPR Test Bed (LOTUS) Virtual Test Bed (VTB): Accelerate deployment of advanced reactors by leveraging state-of-the-art ModSim tools to evaluate performance and safety Ok, but what is it? Library of Reference Model: database of advanced multiphysics advanced reactor models that users can download, edit, and re-run Continuous Software QA: linking repository to software development to avoid legacy issues while enabling rapid code development Virtual models of the test bed: developing demonstration-relevant models (e.g., candidates for DOME/LOTUS) to accelerate safety evaluations

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Power Electronics and Electric Machines for Advanced Aircraft

Power electronics and electric machines are critical components of efficient, high-performance aircraft - from fixed-wing turbine to electric vertical takeoff and landing aircraft and beyond. Improvements to these components create enormous energy efficiencies, enable cost savings, and ensure fail-safe operations. National Renewable Energy Laboratory researchers are developing innovative power electronics, electric motors, integrated electric traction drives, and thermal management systems to build highly efficient, lightweight, ultrareliable powertrains for aircraft.

42 ENGINEERING↗

DOE OSTI2016

Ultra-fast LuI{sub 3}:Ce scintillators for hard x-ray imaging

We have developed ultra-fast cerium-coped lutetium-iodide (LuI{sub 3}:Ce) films thermally evaporated as polycrystalline, structured scintillator using hot wall epitaxy (HWE) method. The films have shown a 13 ns decay compared to the 28 ns reported for crystals. The fast speed coupled with its high density (∼5.6 g/cm{sup 3}), high effective atomic number (59.7), and the fact that it can be vapor deposited in a columnar form makes LuI{sub 3}:Ce an attractive candidate for high frame rate, high-resolution, hard X-ray imaging. In crystal form, LuI{sub 3}:Ce has demonstrated bright (>100,000 photons/MeV) green (540 nm) emission, which is well matched to commercial CCD/CMOS sensors and is critical for maintaining high signal to noise ratio in light starved applications. Here, we report on the scintillation properties of films and those for corresponding crystalline material. The vapor grown films were integrated into a high-speed CMOS imager to demonstrate high-speed radiography capability. The films were also tested at Advanced Photon Source, Argonne National Laboratory beamline 1-ID under hard X-ray irradiation. The data show a factor of four higher efficiency than the reference LuAG:Ce scintillators, high image quality, and linearity of scintillation response over a wide energy range. The films were employed to perform hard X-ray microtomography, the results of which will also be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗

DOE OSTI2018

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at $0.06/kW-hr LCOE, energy conversion efficiency > 50%, and total power block cost < $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗

DOE OSTI2017

Updated Liquid Secondary Waste Grout Formulation and Preliminary Waste Form Qualification

This report describes the results from liquid secondary waste grout (LSWG) formulation and cementitious waste form qualification tests performed by Pacific Northwest National Laboratory (PNNL) for Washington River Protection Solutions, LLC (WRPS). New formulations for preparing a cementitious waste form from a high-sulfate liquid secondary waste stream simulant, developed for Effluent Management Facility (EMF) process condensates merged with low activity waste (LAW) caustic scrubber, and the release of key constituents (e.g. 99 Tc and 129 I) from these monoliths were evaluated. This work supports a technology development program to address the technology needs for Hanford Site Effluent Treatment Facility (ETF) liquid secondary waste (LSW) solidification and supports future Direct Feed Low-Activity Waste (DFLAW) operations. High-priority activities included simulant development, LSWG formulation, and waste form qualification. The work contained within this report relates to waste form development and testing and does not directly support the 2017 integrated disposal facility (IDF) performance assessment (PA). However, this work contains valuable information for use in PA maintenance past FY17, and for future waste form development efforts. The provided data should be used by (i) cementitious waste form scientists to further understanding of cementitious dissolution behavior, (ii) IDF PA modelers who use quantified constituent leachability, effective diffusivity, and partitioning coefficients to advance PA modeling efforts, and (iii) the U.S. Department of Energy (DOE) contractors and decision makers as they assess the IDF PA program. The results obtained help fill existing data gaps, support final selection of a LSWG waste form, and improve the technical defensibility of long-term waste form performance estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Updated Liquid Secondary Waste Grout Formulation and Preliminary Waste Form Qualification

This report describes the results from liquid secondary waste grout (LSWG) formulation and cementitious waste form qualification tests performed by Pacific Northwest National Laboratory (PNNL) for Washington River Protection Solutions, LLC (WRPS). New formulations for preparing a cementitious waste form from a high-sulfate liquid secondary waste stream simulant, developed for Effluent Management Facility (EMF) process condensates merged with low activity waste (LAW) caustic scrubber, and the release of key constituents (e.g. 99Tc and 129I) from these monoliths were evaluated. This work supports a technology development program to address the technology needs for Hanford Site Effluent Treatment Facility (ETF) liquid secondary waste (LSW) solidification and supports future Direct Feed Low-Activity Waste (DFLAW) operations. High-priority activities included simulant development, LSWG formulation, and waste form qualification. The work contained within this report relates to waste form development and testing and does not directly support the 2017 integrated disposal facility (IDF) performance assessment (PA). However, this work contains valuable information for use in PA maintenance past FY17, and for future waste form development efforts. The provided data should be used by (i) cementitious waste form scientists to further understanding of cementitious dissolution behavior, (ii) IDF PA modelers who use quantified constituent leachability, effective diffusivity, and partitioning coefficients to advance PA modeling efforts, and (iii) the U.S. Department of Energy (DOE) contractors and decision makers as they assess the IDF PA program. The results obtained help fill existing data gaps, support final selection of a LSWG waste form, and improve the technical defensibility of long-term waste form performance estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at 0.06/kW-hr LCOE, energy conversion efficiency > 50 % ,and total power block cost< $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO 2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO 2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO 2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗

NASA NTRS2005

Hybrid Power Management Program Evaluated Ultracapacitors for the Next Generation Launch Transportation Project

The NASA Glenn Research Center initiated baseline testing of ultracapacitors to obtain empirical data in determining the feasibility of using ultracapacitors for the Next Generation Launch Transportation (NGLT) Project. There are large transient loads associated with NGLT that require a very large primary energy source or an energy storage system. The primary power source used for this test was a proton-exchange-membrane (PEM) fuel cell. The energy storage system can consist of batteries, flywheels, or ultracapacitors. Ultracapacitors were used for these tests. NASA Glenn has a wealth of experience in ultracapacitor technology through the Hybrid Power Management (HPM) Program, which the Avionics, Power and Communications Branch of Glenn s Engineering Development Division initiated for the Technology Transfer and Partnership Office. HPM is the innovative integration of diverse, state-ofthe- art power devices in optimal configurations for space and terrestrial applications. The appropriate application and control of the various advanced power devices (such as ultracapacitors and fuel cells) significantly improves overall system performance and efficiency. HPM has extremely wide potential. Applications include power generation, transportation systems, biotechnology systems, and space power systems. HPM has the potential to significantly alleviate global energy concerns, improve the environment, and stimulate the economy.

Eichenberg, Dennis J.↗

DOE OSTI2013

Technical Readiness and Gaps Analysis of Commercial Optical Materials and Measurement Systems for Advanced Small Modular Reactors

This report intends to support Department of Energy’s Office of Nuclear Energy (DOE-NE) Nuclear Energy Research and Development Roadmap and industry stakeholders by evaluating optical-based instrumentation and control (I&C) concepts for advanced small modular reactor (AdvSMR) applications. These advanced designs will require innovative thinking in terms of engineering approaches, materials integration, and I&C concepts to realize their eventual viability and deployability. The primary goals of this report include: 1. Establish preliminary I&C needs, performance requirements, and possible gaps for AdvSMR designs based on best available published design data. 2. Document commercial off-the-shelf (COTS) optical sensors, components, and materials in terms of their technical readiness to support essential AdvSMR in-vessel I&C systems. 3. Identify technology gaps by comparing the in-vessel monitoring requirements and environmental constraints to COTS optical sensor and materials performance specifications. 4. Outline a future research, development, and demonstration (RD&D) program plan that addresses these gaps and develops optical-based I&C systems that enhance the viability of future AdvSMR designs. The development of clean, affordable, safe, and proliferation-resistant nuclear power is a key goal that is documented in the Nuclear Energy Research and Development Roadmap. This roadmap outlines RD&D activities intended to overcome technical, economic, and other barriers, which currently limit advances in nuclear energy. These activities will ensure that nuclear energy remains a viable component to this nation’s energy security.

advanced small modular reactors↗

DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗