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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cluster dynamics simulation of xenon diffusion during irradiation in UO 2

Diffusion of fission gas in UO 2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. In this work, we have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO 2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO 2 is adequately described by the Xe + U 2 O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U 4 O y vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U 4 O y vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Furthermore, predictions using the Xe + U 4 O y diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Lastly, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

UltraSep Acoustic Separation Platform

UltraSep is an intelligent ultrasonic separation platform that transforms solid–liquid separation through real-time eigenfrequency resonance locking and ultra-low power energy optimization. By dynamically matching ultrasonic output to system resonance while maximizing particulate removal per unit of applied energy, UltraSep replaces centrifugation and fouling-prone filtration with precision-controlled acoustic forces that significantly reduce power consumption, mechanical complexity, and operating cost while improving recovery performance. This integrated platform unites patented resonance-based acoustic control and energy-per-removal optimization with chemistry-enhanced separation and proprietary system software into a scalable, high-impact commercial technology.

42 ENGINEERING↗
DOE OSTI2026

Tuning Anion Composition and Mobility to Balance Ionic Conductivity and Cation Selectivity in Solid Polymer Electrolytes

Solid polymer electrolytes (SPEs) offer a promising route toward safe and high-performance electrochemical energy storage, yet a fundamental challenge in SPEs involves improving ionic conductivity while maintaining selective cation transport. The hurdle exists because ion transport is typically coupled closely to polymer segmental dynamics. Herein, a glassy single-ion-conducting polymer, poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate] (PLiMTFSI), in which the anions were tethered to the polymer, was blended with a flexible polymer, poly(oligo-oxyethylene methyl ether methacrylate) (POEM), and a series of small-molecule lithium salts, in which the anions were untethered [lithium bis(trifluoromethane­sulfonyl)imide (LiTFSI), lithium bis(fluorosulfonyl)imide (LiFSI), lithium trifluoromethanesulfonate (LiTf), or lithium perchlorate (LiClO 4 )]. The impact of salt anion volume and tethered-to-untethered anion ratio on the ion conduction behavior and thermal properties of blend electrolytes was investigated. In some cases, conductivity could be enhanced through this ternary blend approach. For example, a POEM-based polymer blend containing a bulky salt anion (TFSI⁻) and an equimolar mixture of PLiMTFSI and LiTFSI exhibited a Li + conductivity (4.8×10 -4 S/cm) an order of magnitude higher than that of a comparable POEM / LiTFSI system (6.3×10 -5 S/cm) at 100 °C. This enhancement was attributed to a more than ninefold increase in lithium transference number (0.66 in the ternary blend vs. 0.07 in POEM / LiTFSI). Overall, this study highlights the potential for tuning anion composition and mobility to achieve relatively high ionic conductivities and maintain selective cation transport in SPEs, offering a pathway to enable batteries that tolerate elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dynamics and observational signatures of core-collapse supernovae with central engines: hydrodynamics simulations with Monte Carlo post-processing

A long-lived central engine embedded in expanding supernova ejecta can alter the dynamics and observational signatures of the event, producing an unusually luminous, energetic, and/or rapidly evolving transient. We use 2D hydrodynamics simulations to study the effect of a central energy source, varying the amount, rate, and isotropy of the energy deposition. We post-process the results with a time-dependent Monte Carlo radiation transport code to extract observational signatures. The engine excavates a bubble at the centre of the ejecta, which becomes Rayleigh–Taylor unstable. Sufficiently powerful engines are able to break through the edge of the bubble and accelerate, shred, and compositionally mix the entire ejecta. The breakout of the engine-driven wind occurs at distinct rupture points, and the outflowing high-velocity gas may eventually give rise to radio emission. The dynamical impact of the engine leads to faster rising optical light curves, with photon escape facilitated by the faster expansion of the ejecta and the opening of low-density channels. For models with strong engines, the spectra are initially hot and featureless, but later evolve to resemble those of broad-line Ic supernovae. Under certain conditions, line emission from ionized, low-velocity material near the centre of the ejecta may be able to escape and produce narrow emission similar to that seen in interacting supernovae. We discuss how variability in the engine energy reservoir and injection rate could give rise to a heterogeneous set of events spanning multiple observational classes, including the fast blue optical transients, broad-line Ic supernovae, and superluminous supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enhancing Streamflow Forecast and Extracting Insights Using Long-Short Term Memory Networks With Data Integration at Continental Scales

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental-scale median Nash-Sutcliffe Efficiency coefficient value of 0.86. Integrating moving-average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow-dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation-energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater-dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high-aridity basins with 1-day flash peaks. Despite this limitation, there is much promise for a deep-learning-based forecast paradigm due to its performance, automation, efficiency, and flexibility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High Performance Solvent for NGCC Flue Gas CO 2 Capture (Final Technical Report)

Amine-based solvent absorption is the most mature and reliable technology for large scale CO 2 capture, dating back to the 1930s when monoethanolamine (MEA) was used to treat acid gases from oil refineries. However, while strategic advancements have optimized the CO2 capture process, the cost of capture remains high, where current estimates suggest that CO 2 capture costs are around $\$$72/tonne of CO 2 . To address this, solvent development and optimization have become a focus of current research. This project sought to develop a high-performance solvent to reduce the overall cost of CO 2 capture from NGCC flue gas. Here, solvent optimization focused on: (1) reducing the energy required for CO 2 desorption in a reboiler, (2) improving CO 2 absorption and desorption reaction kinetics, (3) improving solvent stability, and (4) reducing environmental impacts. Susteon has developed and evaluated a promoted solvent, Sustenol™, for NGCC flue gas CO 2 capture. The optimized Sustenol™ also shows a higher dynamic CO 2 absorption capacity of ~0.5 mol CO2 /mol amine compared to 0.25 mol CO2 /mol amine for 30 wt% MEA. Additionally, the solvent is oxidatively, thermally and hydrothermally stable, which leads to lower solvent loss and emissions. These advancements have resulted in a solvent regeneration energy of 2.16 GJ/tonne of CO 2 which is >30% lower than current state-of-the-art commercial and emerging solvents. Combined with empirical data from the bench and pilot scale testing, this preliminary TEA study indicated the cost of CO 2 capture by Sustenol™ for 97% CO 2 removal at $\$$54/tonne and for 90% removal at $\$$49/tonne, with a pathway to achieve $\$$45/tonne of CO 2 with continued process and solvent advancements. Susteon has developed a technology roadmap to reduce the cost of CO 2 capture to <$\$$45/tonne for NGCC flue gas. Susteon plans to derisk this technology for commercial deployment through comprehensive solvent degradation testing, long-term testing in a pilot plant at 5 tonne CO2 /day and demonstration scale testing at 100 tonne CO2 /day with NGCC flue gas and engineering design studies to qualify Sustenol™ as a drop-in replacement solvent.

03 NATURAL GAS↗
DOE OSTI2023

High-temperature active oxidation of nanocrystalline silicon-carbide: A reactive force-field molecular dynamics study

Flexible woven SiC ceramics are prone to accelerated fiber embrittlement under high temperature oxidation in dynamic oxygen environments. The nanocrystalline structure of the constituent fibers impacts the reaction kinetics and phase transformations during active oxidation. However, fundamental understanding and quantification of grain boundary effects on oxidation behavior in nanocrystalline SiC remain elusive when temperatures exceed 1500 K. This study deploys large-scale molecular dynamics simulations with a reactive force-field to elucidate the complex roles of atomic oxygen reservoir conditions and grain size on oxidation kinetics and the nature of oxides produced in both monocrystalline and nanocrystalline 3C-SiC between 1100 K and 2000 K. The simulations with dynamically replenished oxygen provide good agreement with oxidation kinetics and activation energies for the monocrystalline Si(100) and C(100) orientations published in the available literature. This study reveals that, by contrast, nanocrystalline SiC samples exhibit two distinct oxidation kinetics with a transition point at 1500 K due to surface melting, which is supported by experimental evidence. The introduction of a grain-boundary network produces a two-fold decrease in oxidation activation energies compared to monocrystalline SiC below 1500 K. Above 1500 K, however, the activation energies rise substantially due to the formation of a liquid Si phase at the SiC/Si oxide interface. Further, it is shown that the stability of the interfacial liquid phase is promoted by incoherent grain boundaries in the crystalline SiC. These findings are important for the deployment of nanocrystalline SiC fibers in advanced thermal protection systems for high-temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GCAM-USA: IM3 Phase 2 Official Simulations

Overview GCAM-USA simulates 21st century energy-water-land interactions in global regions with sub-national detail in the United States (US). The IM3 project is focused on US multisector dynamics and has created eight GCAM-USA simulations by combining two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight GCAM-USA simulations are named: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Detailed Assumptions The SSPs describe alternative socioeconomic futures and their implications for both the US and global environmental challenges. As implemented in GCAM-USA, the primary difference between SSP3 and SSP5 in the US is their population growth projections, with SSP3 foreseeing lower growth and SSP5 projecting higher growth. The four climate projections explore moderate (RCP4.5) and high (RCP8.5) greenhouse gas emission (GHG) trajectories, each with a hotter and cooler climate variation based on the range of global climate model simulations in CMIP6s. These four climate projections are used in precursor models to develop climate impacts on building heating and cooling degree-hours, water availability, and agricultural yields that are provided as inputs to GCAM-USA. GCAM-USA reproduces the RCP4.5 and RCP8.5 GHG emissions trajectories consistent with each climate projection, using dynamic carbon prices to achieve RCP4.5. When the four climate projections are combined with the two SSP projections, the resulting eight scenarios allow GCAM-USA to explore how a wide, yet plausible, range of climate and socioeconomic impacts affects the interconnected energy, water, and land systems across the contiguous United States. Technical Details IM3 uses a version of GCAM-USA v5.3 that has an enhanced electricity sector and an updated data system needed to represent regional to local scale dynamics.

IM3↗
DOE OSTI2021

Scalable Distributed Reachability Analysis for Cyber-Physical Networked Microgrids with Communication Latency

Due to the high penetration of power-electronic-interfaced distributed energy resources (DERs), a microgrid's inertia is significantly reduced, making it sensitive to cyberand physical operational changes. When multiple microgrids are interconnected to form networked microgrids for improving system's resilience, the changes of one microgrid can quickly escalate to the overall system. In cyber-physical networked microgrids, the communication latency varies a lot. To efficiently quantify the impact of the communication latency on the dynamics of networked microgrids, a scalable distributed reachability analysis approach is presented in this paper. Reachable sets are calculated for each microgrid and then composited for the overall system dynamics evaluation. Extensive tests in the full paper will demonstrate the influence of communication latency on system dynamics and validate reachable sets can bound a system's all dynamic trajectories subject to latency changes. The test results also offer an insight into designing and managing the communication network for enhancing the system's resilience.

Li, Yan↗
DOE OSTI2023

Integrating Control Methods and Digital Twins for Advanced Nuclear Reactors

Advanced nuclear reactors offer new capabilities such as the ability to adapt to variable energy demand, operate autonomously with remote supervision, be deployable in rural locations, be compact in size, afford lower power ratings, and rely on novel techniques for increased operational safety. However, realizing these capabilities requires intelligent control systems that can track changing power demands and make autonomous decisions based on these demands. The unique aspects of advanced reactors (e.g., strict regulatory requirements, harsh operating environments, high consequences, highly coupled dynamics, evolving knowledge, and limited operating histories) directly impact the design and deployment of control systems for these reactors. The present work identifies and evaluates these aspects so as to develop a set of control system requirements to guide future research and development. To meet these requirements, a layered control system approach is proposed that integrates digital twins with different control paradigms. This work aims to demonstrate how different methods interface with enabling solutions, and to identify any gaps that need to be researched.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Structure and Dynamics of Aqueous Electrolytes Confined in 2D-TiO 2 /Ti 3 C 2 T 2 MXene Heterostructures

The synthesis of heterostructures of different two-dimensional (2D) materials offers an approach to combine advantages of different materials constituting the heterostructure and ultimately enhance their performance for applications such as electrochemical energy storage, achieving high energy, and high-power densities. Understanding the behavior of ions and solvents in confinement between these dissimilar layers is critical to understand their performance and control. Considering aqueous electrolytes, we explore the heterostructure of 2D lepidocrocite-type TiO 2 (2D-TiO 2 ) and hydroxylated or O-terminated Ti 3 C 2 MXene using ReaxFF molecular dynamics simulations and elastic/quasielastic neutron scattering techniques. Simulating a bilayer water intercalation, we find that the extent of interlayer hydration is impacted most by the surface terminations on the MXene and is marginally affected by 2D-TiO 2 . However, the introduction of 2D-TiO 2 decreases the water self-diffusion due to the notch sites (i.e., surface oxygen ridges) entrapping water molecules. Intercalating alkali cations into the heterostructures, we find that Li + is predominantly adsorbed at the 2D-TiO 2 surface instead of the MXenes with the preferential occupation of the notch sites. In contrast, Na+ forms a planar solvation with water, while K + is adsorbed both at the O-terminated MXene and 2D-TiO 2 . This behavior is altered when OH-terminated MXene is involved—the repulsion from the protons on the MXene surface forces the K + ions to be adsorbed exclusively to 2D-TiO 2 , while Na + retains some of its solvation in the water layer due to its smaller size. In OH-terminated MXenes, we see a consistent transfer of protons from the MXene surface toward 2D-TiO 2 , implying a greater capacity to store protons in the heterostructures. Of the three cations simulated, Na + hinders the proton migration the least and Li + the most because of its position near the 2D-TiO 2 surface. Furthermore, 2D-TiO 2 /MXene heterostructures are likely to exhibit a higher energy density but lower power density, especially with Na + intercalation.

25 ENERGY STORAGE↗
DOE OSTI2022

Porosity Development at Li-Rich Layered Cathodes in All-Solid-State Battery during In Situ Delithiation

Structural evolutions are crucial for determining the performance of high-voltage lithium, manganese-rich layered cathodes. Moreover, interface between electrode and electrolyte plays a critical role in governing ionic transfer in all-solid-state batteries. In this work, we unveil two different types of porous structure in Li 1.2 Ni 0.2 Mn 0.6 O 2 cathode with LiPON solid-state electrolyte. Na-nopores are found near the cathode/electrolyte interface at pristine state, where cation mixing, phase transformation, oxygen loss and Mn reduction are also found. In situ Li + extraction induces the evolution of nanovoids, initially formed near the inter-face then propagated into the bulk. Despite the development of nanovoids, layered structure is conserved, suggesting the nature of nanopores and nanovoids are different and their impact would be divergent. This work demonstrates the intrinsic interfacial layer, as well as the dynamic scenario of nanovoid formation inside high-capacity layered cathode, which help understanding the performance fading in cathodes and offer insights into the all-solid-state battery design.

25 ENERGY STORAGE↗
DOE OSTI2023

A New Era of Discovery: The 2023 Long-Range Plan for Nuclear Science (V.1.2)

Nuclear science is the investigation of how protons and neutrons are formed from elementary particles and how the forces between those particles produce both nuclei and the vast variety of nuclear phenomena that occur in the universe. It has evolved into a broad field that addresses profound scientific questions: Where does the mass of visible matter come from? How do stars ignite, live, and die? How do nuclei illuminate the search for new laws of nature? This science points the way to using nuclei to build new technologies that benefit society. The 2015 Nobel Prize in physics was shared by nuclear physicists Art McDonald and Takaaki Kajita for the discovery of neutrino oscillations, which confirmed that neutrinos have mass. Our progress on big questions like this one since 2015 has been remarkable owing to new experimental tools, theoretical breakthroughs, powerful computational techniques, and the talented people who make these innovations possible. Focusing on these new tools, the Facility for Rare Isotope Beams (FRIB) at Michigan State University is already producing exciting results on decays of never-before-produced isotopes a year after it was completed on time and on budget. The energy upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) was also completed on schedule and on budget—new data from this facility are revealing the spectrum, structure, and dynamics of protons, neutrons, nuclei, and mesons. On the theory front, we can now calculate the distribution of quarks inside the proton from first principles. The implementation of artificial intelligence (AI) and machine learning (ML) techniques has led to improved data analysis and increased efficiency in running experiments and theoretical calculations. The impact of nuclear science goes beyond expanding the frontiers of knowledge about matter in the universe. We simultaneously develop a STEM work force that advances the security, technology, health, and wealth of our nation. Some connections are obvious. Expert scientists trained to work with radioactive nuclei are in demand in nuclear security arenas and are highly sought after by various government agencies and private industries. Graduate students and postdoctoral fellows (postdocs) obtain extensive computational, modeling, and data science skills that are similarly in high demand. Less obvious but equally important is the connection between these trained scientists and success in other professions, including medicine, energy, and entrepreneurial pursuits. The workforce that enables discovery in nuclear science also makes breakthroughs in technologies with tremendous impact on the nation’s economic advancement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Mechanistic Insights into Oxygen Reduction Reaction on Metal Cathode Over BaZrO 3 -Based Electrolyte under Moist Atmosphere: Interfacial Interactions and Reaction Pathways

The oxygen reduction reaction (ORR) is a critical process that often governs the overall performance of electrochemical systems such as proton conducting solid oxide fuel cells. Despite its significance, the current understanding about the ORR, especially when it involves H 2 O is still limited. In this study, the proton involved ORR (PI-ORR) on metal cathode (e.g., Pt) over BaZrO 3 (BZO) electrolyte is investigated using density functional theory (DFT) under moist atmosphere. Two scenarios are considered: one at relatively high temperature (900 K) in the presence of oxygen vacancy in BZO substrate and one at relatively low temperature (700 K) without oxygen vacancy. We systematically explored oxygen vacancy effects on adsorption sites and proton transfer pathways, calculated energy profiles and Gibbs free energies for elementary steps along the O 2 dissociated and the O 2 concerted reaction pathways. We also evaluated H 2 O impacts on intermediate oxygen species (*O and *OH) through Ab Initio molecular dynamics. These analyses revealed pathway-dependent reaction mechanisms and hydration effects at triple-phase boundary, advancing fundamental understanding of PI-ORR in metal cathode/Ba-based electrolyte systems for energy applications.

08 - HYDROGEN↗
DOE OSTI2021

A laser inverse Compton scattering diagnostic to study runaway electron dynamics during tokamak disruptions

The goal is to design a new diagnostic based on laser inverse Compton scattering (LICS) to study the dynamics of runaway electron formation and their subsequent loss during triggered disruptions in DIII-D. It is known that better measurements of the runaway electron population, throughout the evolution of a disruption, is critical for mitigating the impact of energetic electron beams especially in high plasma current discharges such as those in reactor relevant burning plasmas. The goal of the LICS approach being designed for DIII-D is to measure the timeresolved spatial profile and energy distribution of the runaway electrons while they are in the core of the tokamak plasma. During the last year, a code was developed to simulate the signals from a new laser scattering diagnostic for DIII-D, which will measure the relativistic electron population expected in DIII-D after disruptions triggered by argon pellet injection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Library of Advanced Models of large-scale PV (LAMP) (Final Technical Report)

A suite of dynamic models of photovoltaic (PV) systems is developed in this project to accurately capture PV system dynamics during different contingencies. The following models are included: (i) quasi-dynamic, (ii) high-fidelity electromagnetic transient (EMT), (iii) advanced, and (iv) baseline. The models have the flexibility to consider different control functionalities at different controller levels. The study’s requirements determine the type of model needed. For example, high-fidelity EMT models are recommended for contingency studies. Advanced models are recommended for online or real-time implementations with resource constraints, whereas quasi-dynamic models are useful for studying the impact of weather variations.

14 SOLAR ENERGY↗
DOE OSTI2025

Radiation damage effects in beryllium for next generation neutrino beam targetry (Final Technical Report)

Current and future high-power accelerators put severe requirements on materials used for target and beam windows and target facilities have been recognized as a critical challenge in development of future particle accelerators. In accelerators, window and target materials are exposed to extreme conditions, which include bombardment with very high energy protons (1- 100 GeV) and thermomechanical shock waves. Radiation can cause direct damage in the material, and it leads to production of transmutation products (especially helium), both phenomena having a potential adverse effect on the stability and durability of the target/window material. At high enough temperatures, He can aggregate to form gas bubbles, which in turn cause significant dimensional changes (swelling), enable easy crack propagation, and eventually cause failure by fracture. On the other hand, if the temperature is too low, radiation damage accumulates in the form of internal defects (e.g., dislocations), leading to hardening and a decreased ductility of the material. In this project, we will focus on beryllium since it is considered to be one of the candidate materials for beam windows and targets in the next-generation proton accelerators, e.g., the Long Baseline Neutrino Facility (LBNF). Radiation effects in Be have been studied in the context of nuclear fusion reactor applications. However, key differences exist between reactor and accelerator conditions, including neutron vs. proton irradiation, continuous vs. pulsed beam flux, much higher energies of bombarding particles in accelerators, and higher operating temperatures for typical reactors. For example, the impact of beam pulsing on the radiation damage and the He bubble kinetics is largely unknown. While results obtained on Be from fusion research might not be directly transferrable to understanding target materials, there is an opportunity to bring state-of-the-art tools from materials research in nuclear reactors to aid design of target and beam window materials in high-power accelerators. To this end, the overarching goal of this project are to develop an experimentally-validated computational framework capable of predicting radiation damage evolution in beryllium relevant to beam window and target conditions, focusing on He bubble formation and growth as a function of irradiation temperature. Our model will be based on the cluster dynamics formalism, where size distribution of defects and He bubbles is simulated as a function of time, temperature, and radiation dose. Parameters for the model will be taken from published experiments and from high-fidelity atomistic simulations proposed in this project. In addition, we will carry out a series of targeted ex-situ and in-situ dual-beam experiments using low-energy protons to provide critical data for validation of the model on the effects of radiation on He clustering, He bubble distribution, and dislocation loop density/size in proton irradiated Be.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Single-Bunch Instabilities Driven by Space Charge During Low-Energy Cooling at Injection in the EIC Hadron Storage Ring

This paper presents a simulation-based study of single-bunch dynamics at the injection energy of 23.8 GeV for protons in the EIC hadron storage ring, focusing on the impact of space-charge–driven instabilities. The analysis demonstrates that at this energy, the proton bunch experiences significant transverse space-charge forces, which can reduce the stability margin in the presence of the geometric and resistive wall impedance. Various collective effects were considered, with particular attention to the nonlinear nature of the transverse space charge. To stabilize the beam, high chromaticity and octupoles were introduced and their effects analyzed using the ELEGANT code. The results provide a quantitative assessment of the stability thresholds and offer guidance for the machine design and operational strategy at injection.

43 PARTICLE ACCELERATORS↗