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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Liquid metal walls

Here, the plasma performance of fusion devices depends strongly on the chosen wall materials. Solid plasma-facing components (PFCs) are predominantly used in present devices, and are the most investigated candidates for fusion designs. High-Z materials such as tungsten (W) are the leading solid PFC material candidates. To date, a material choice that scales to steady-state reactor conditions has not been identified. Moreover, if plasma transient events such as edge-localized modes and disruptions cannot be altogether avoided or sufficiently mitigated, the projected peak heat and particle loads far exceed the power exhaust capabilities of solids. Liquid metal (LM) PFCs represent an intrinsic self-healing boundary that are both resilient to surface damage from transients, and that could handle high steady-state heat and particle fluxes. Flowing LM PFCs can be designed to remove “slag,” the buildup of material erosion due to plasma-material interactions, including charge exchange sputtering in the main chamber. Further, LM offer the prospect to manage hydrogenic species otherwise retained in the PFCs, which is important from a safety and inventory standpoint. The two most promising LMs are lithium (Li) and tin (Sn), although Sn–Li eutectics may be considered. While Sn offers a higher temperature window with low vapor pressure and low hydrogen retention, Li offers the prospect of enhanced energy confinement and higher acceptable core contamination limits, and this section focuses on Li PFCs. An LM PFC development research program developed LM PFC concepts for a nuclear fusion device via engineering design calculations, single-effect experiments, and staged prototypical experiments. A self-consistent design window was identified with liquid Li flow speeds ~5–10 m/s; plasma contamination was negligible for predicted Li evolution rates. While these preconceptual designs hold promise, there is substantial R&D needed to advance the technical readiness levels of LM PFCs for application to fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Effect of moisture ingression on material performance and particle generation in molten salts

This report summarizes activities conducted to understand and mitigate the negative consequences that moisture ingressions have upon the operations of pyroprocessing equipment. The objectives of the work conducted in FY25 were to characterize (1) the physicochemical properties of particles generated as a result of moisture ingressions, and (2) the corrosion of relevant structural materials with the introduction of moisture. Compositional and morphological analyses of the generated particles were conducted through a suite of characterization technologies, including X-ray diffraction, microscopy, and particle size analysis. The results gathered this year were compared to those obtained in FY24 when studies with oxygen ingressions were conducted on CeCl 3 -LiCl-KCl and UCl 3 -LiCl-KCl systems. Investigations involving performance evaluations of industrially relevant structural alloys were also conducted under moisture ingress conditions. In-line electrochemical monitoring of the bulk salt was augmented with microscopy of alloy samples to quantify the concentration and accumulation of corrosion products in the bulk salt. The results reported in this work provide a more holistic understanding of the effects of atmospheric ingressions on molten chloride salt chemistry such that effective redox control strategies may be implemented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts.

Schram, Malachi [Thomas Jefferson National Acceler↗
DOE OSTI2026

Continual Learning for Production-Level Machine Learning in Particle Accelerators

Particle accelerators operate in complex environments where data distribution can change dynamically, leading to data drifts that significantly challenge Machine Learning (ML) models. These non-stationary conditions often cause ML models to deteriorate in performance, making it difficult to maintain reliable predictions in operation. The primary sources of data drifts are changes in accelerator settings and changes in equipment performance which cannot be measured directly. To bridge this gap between ML development and long-term deployment in operational settings, we identify key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. We will provide a practical guide on selecting the appropriate method given resource constraints and desired stability plasticity trade offs. As a concrete example, we will present a real-world use case for anomaly detection to predict errant beams at the Spallation Neutron Source accelerator, where continual learning has been employed to demonstrate stable performance on drifting data streams. We will present practical challenges, lessons learned, and the results from the deployed ML model.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2026

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2025

Precise Synthesis of 4.75 V-Tolerant LiCoO 2 with Homogeneous Delithiation and Reduced Internal Strain

The rapid advancements in 3C electronic devices necessitate an increase in the charge cutoff voltage of LiCoO 2 to unlock a higher energy density that surpasses the currently available levels. However, the structural devastation and electrochemical decay of LiCoO 2 are significantly exacerbated, particularly at ≥4.5 V, due to the stress concentration caused by more severe lattice expansion and shrinkage, coupled with heterogeneous Li + intercalation/deintercalation reactions. Herein, employing the molten-salt synthesis technique, we propose a universal morphology-shaping strategy to attain bulk reaction homogeneity and reduce internal strains, even at extremely high charge voltages. The newly designed flattened polygon prismlike LiCoO 2 (P-LCO) particle, featuring a regular symmetrical arrangement along the c-axis, demonstrates a more homogeneous Li + extraction/insertion reaction, which results in a restrained transformation to detrimental O1 phase and reduced variation in lattice volume throughout the (de)lithiation processes. This benefits the mitigation of the local stress accumulation misfit dislocations and particle cracking, ultimately maintaining the mechanical stability of the cathode. Consequently, P-LCO is capable of breaking the voltage ceiling and exhibits exceptional long-term cycling capability at an ultrahigh voltage of 4.75 V. In conclusion, this work offers a brand-new perspective for the rational design of cathode morphology to address capacity deterioration caused by inhomogeneous delithiation and internal strain, thus inspiring the development of high-energy-density cathodes with improved durability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale electro-chemo-mechanical model of high-capacity amorphous silicon anode material in sodium-ion batteries

The growing interest in sodium-ion batteries (SIBs) is fueled by their abundant resources and environmentally friendly nature, with amorphous silicon (a-Si) emerging as a promising anode material for enhancing capacity. However, the key challenge lies in sustaining reversible capacity during cycling. Here, in this work, we developed a multiscale electrochemical model incorporating an a-Si anode to elucidate the performance parameters of SIBs. Additionally, we integrated an electro-chemo-mechanical model at the particle level to capture stress generation, an essential factor in the degradation of high-capacity electrodes. Unlike existing models, our approach accounts for large-deformation chemo-mechanics at the particle scale and includes simulations under varying charge rates to explore multiscale behavior. The results reveal that coupled sodiation significantly prolongs complete cycling times and influences discharge dynamics, indicating that neglecting this coupling leads to an underestimation of actual capacity. Furthermore, we observed pronounced polarization effects at higher charge rates, resulting in heterogeneous stress distributions across the anode. With the identification of critical failure parameters for both active particles and binder materials, offering novel insights for mitigating degradation in high-capacity electrode systems.

Amorphous silicon anode↗
DOE OSTI2024

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗
DOE OSTI2025

Enhancing cold spray coatings: Microstructural dynamics and performance attributes of Inconel 625 with chromium carbide incorporation for hydropower applications

The incorporation of chromium carbide (CrC) particles into the cold spray (CS) process is known to mitigate nozzle clogging, although at the expense of deposition efficiency. This study explores the intricate microstructural changes induced by varying amounts of CrC powder (12.5 % and 6 %) in conjunction with Inconel-625 (Inc-625) powder. The deposition was carried out onto A27 cast steel under different CS parameters. Microstructural characterization, including detailed electron microscopy studies, reveals a complex yet structurally stable coating. Noteworthy features include grain fragmentation and a cellular structure enriched with Nb and Mo, with minimal plastic deformation of CrC in the matrix. The cold-sprayed coatings exhibit a significant (~4 times) increase in microhardness compared to the A27 substrate. Mechanical and cavitation erosion properties were systematically investigated. Coatings subjected to higher particle energy conditions with a gas pressure of 600 psi and gas temperature of 650 °C, demonstrated superior resistance to cavitation erosion. This resistance is attributed to a combination of factors, including microstructural characteristics and porosity. Altogether, the study provides valuable insights into the structural dynamics and performance of CS coatings enriched with CrC particles.

A27 cast steel↗
DOE OSTI2025

Extending TOUGH + HYDRATE with a parallel particle transport simulator: numerical investigation of sand production during gas production from hydrate deposits

A new parallel code for simulating particle transport in porous media is integrated with the TOUGH + HYDRATE simulator to investigate sand production associated with gas production from unconsolidated gas hydrate-bearing sediments (HBS). Here, the parallel coupled simulator is named THMPT and uses the integral finite difference method to describe the Darcian and non-Darcian flow of fluids and heat transport, the finite element method to describe the associated geomechanical changes, and the discrete element method to track the trajectory of individual sand particles within the HBS. The THMPT simulator is written in Fortran, incorporates multiple optimized algorithms, and can comprehensively address the coupled flow, thermal, chemical, geomechanical, and particle transport processes that characterize the system behaviors during gas production from HBS. The simulator can capture all processes involved in sand particle transport in porous media, including sand detachment, collision, clogging (i.e., bridging), and migration. A benchmark case study of sand production in the course of depressurization-induced gas production from a representative HBS reveals various distinct microscopic particle migration mechanisms and the adverse impact of sand particle detachment, transport, and clogging. The numerical investigation also examines the effect of bottomhole pressure on mitigating sand production. The simulation results indicate that sand clogging near the wellbore significantly reduces permeability, decreasing gas production by at least 50%. Lastly, the efficiency of gravel packing in mitigating sand production is numerically evaluated, revealing that the structure of the porous media appears to profoundly influence the macroscopic motion behavior of sand particles and sand clogging characteristics.

discrete element method↗
DOE OSTI2025

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mitigating Transition in the Fermilab Booster Using a Triple Phase Jump

The PIP-II project will significantly enhance neutrino production for DUNE, Fermilab’s flagship long-baseline neutrino oscillation experiment, by doubling the beam power delivered by the accelerator complex. To achieve this, the total charge injected from the new PIP-II linac into the Booster rapid cycling synchrotron (RCS) will increase from $4.5\times 10^{12}$ to $6.5\times 10^{12}$ protons per pulse. Simultaneously, the Booster’s ramp rate will rise from 15 to 20 Hz, while the injection energy will go from 400 MeV to 800 MeV. The Booster accelerates the beam to 8 GeV and crosses transition at $\gamma_t=5.45$. In current operations, no dedicated $\gamma_t$ jump system is employed; instead, longitudinal emittance growth is controlled via an active quadrupole-mode feedback system. Downstream, the Recycler Ring uses slip-stacking to accumulate beam and increase bunch intensity. However, this process imposes a constraint on the longitudinal emittance at Booster extraction, limiting it to 0.1 eV-s (95\%) to avoid excessive particle loss. Because collective effects scale with intensity, additional measures to mitigate transition crossing may be required to stay below this limit. One potential approach is the so-called triple phase-jump technique. While the method has known limitations, it offers some advantages: it can be implemented using the existing digital low-level RF (LLRF) system, requires no additional magnets or pulsed power supplies, and remains compatible with quadrupole-mode feedback.

Ostiguy, J.-F. [Fermilab] (ORCID:0000000290883681)↗
DOE OSTI2025

Mitigating Transition in the Fermilab Booster Using a Triple Phase Jump

The PIP-II project will significantly enhance neutrino production for DUNE, Fermilab s flagship long-baseline neutrino oscillation experiment, by doubling the beam power delivered by the accelerator complex. To achieve this, the total charge injected from the new PIP-II linac into the Booster rapid cycling synchrotron (RCS) will increase from $4.5\times 10^{12}$ to $6.5\times 10^{12}$ protons per pulse. Simultaneously, the Booster s ramp rate will rise from 15 to 20 Hz, while the injection energy will go from 400 MeV to 800 MeV. The Booster accelerates the beam to 8 GeV and crosses transition at $\gamma_t=5.45$. In current operations, no dedicated $\gamma_t$ jump system is employed; instead, longitudinal emittance growth is controlled via an active quadrupole-mode feedback system. Downstream, the Recycler Ring uses slip-stacking to accumulate beam and increase bunch intensity. However, this process imposes a constraint on the longitudinal emittance at Booster extraction, limiting it to 0.1 eV-s (95\%) to avoid excessive particle loss. Because collective effects scale with intensity, additional measures to mitigate transition crossing may be required to stay below this limit. One potential approach is the so-called triple phase-jump technique. While the method has known limitations, it offers some advantages: it can be implemented using the existing digital low-level RF (LLRF) system, requires no additional magnets or pulsed power supplies, and remains compatible with quadrupole-mode feedback.

Ostiguy, Jean-Francois [Fermilab] (ORCID:000000029↗
DOE OSTI2025

Mitigating X-ray-induced damage for accurate analysis of battery cathodes using transmission X-ray microscopy

Here, we investigate the impact of X-ray-induced damage on the evolution of battery cathodes using synchrotron transmission X-ray microscopy. In an operando coin cell, exposure to the X-ray beam can induce bubble formation, potentially rendering cathode particles electrochemically inactive and displacing particles from their initial position. However, utilizing external pressure on a pouch cell can mitigate bubble formation and its associated effects.

25 ENERGY STORAGE↗
DOE OSTI2025

Comprehensive analysis of disruption mitigation methods using gas and pellet-like injections in ITER-like Tokamaks

Abstract Inert-gas shielding could be an effective mechanism for protection of plasma facing surfaces (PFS) against plasma particles impact and photon radiation heat loads during transient events in fusion devices. Neutral gas injection is one promising way to mitigate erosion of tokamak components and contamination. The objective of this work is to study and optimize mitigation methods using neutral gas and pellet-like injections to decrease the heat load to the divertor surfaces and to prevent vaporization of the various internal surfaces due to transient events in ITER-like devices. The integrated self-consistent models implemented in the HEIGHTS package was used for detailed analysis of the potential secondary plasma generation from the injected inert gas, its radiative characteristics, and shielding effectiveness. We varied the density, size, and location of an argon gas cloud to minimize the disruption energy deposited into the divertor components. We also investigated innovative ways for minor changes in ITER-like internal design to mitigate disruptions. We found the optimum parameters to fully protect ITER tokamak surfaces from erosion and vaporization during plasma instabilities. This preliminary analysis showed that using Ar gas injection methods could lead to enhancement in components lifetime in ITER-like and future DEMO devices with minor design changes.

Science & Technology - Other Topics↗
DOE OSTI2025

Measuring the Muon Neutrino Magnetic Moment in the NOvA Near Detector

Measuring an enhanced neutrino magnetic moment would be a clear indication of physics beyond the Standard Model, shedding light on the correct beyond Standard Model theory or the potential Majorana nature of neutrinos. It would manifest in the NOvA near detector as an excess of neutrino-on-electron elastic scattering interactions at low electron recoil energies. Leveraging an intense and highly pure muon neutrino beam, along with a finely segmented liquid scintillator detector technology specifically designed for electromagnetic shower separation, enables NOvA to achieve a potentially world-leading sensitivity in probing the effective muon neutrino magnetic moment. This analysis, based on neutrino data collected between 2014 and 2021, corresponding to an exposure of $13.8\times10^{20}$ protons-on-target, yields a result consistent with the Standard Model-only hypothesis with a p-value of 0.31. An upper limit on the effective muon neutrino magnetic moment is set at $\mu_{\nu_\mu}<19.1\times 10^{-10}\mu_B$ at $90\%$ confidence level. Despite facing statistical limitations stemming from low cross section of the signal process, systematic uncertainties have a significant impact on this result. To address these challenges, the NOvA Test Beam experiment focuses on mitigating some of the largest systematic uncertainties within NOvA by investigating particle interactions and energy deposition in a small-scale replica NOvA detector. This thesis describes the calibration of the NOvA Test Beam detector, which is a crucial step in analysing the Test Beam data before they can be utilised to reduce NOvA systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Mechanistic Insights into the Surface Instabilities of TiNb 2 O 7, a High‐Power Li‐Ion Anode

TiNb 2 O 7 (TNO) is a promising Li-ion battery anode for high-power applications, such as implantable medical devices and heavy-duty equipment. Hailed as being safe due to its elevated operating potential near 1.6 V, TNO has long been assumed to be highly stable in the carbonate-based electrolytes used in Li-ion batteries. Herein, all mechanisms occurring at the surface of both TNO and Nd-doped TNO are identified, and both materials in fact show significant gassing. CO 2 is even released at open circuit conditions, demonstrating the poor chemical stability of the material in the electrolyte even prior to battery operation. Such extreme instability is a critical safety concern. In addition, it was found that Ti dissolves from the surface of TNO particles at low voltage (below 1.4 V vs Li), and in fact deposits on the counter electrode. Ti further inside TNO particles then diffuses to the Ti-poor surface during discharge. Partial carbon-coating as a mitigating measure has also been tested and found to exacerbate these processes. The findings identify novel reactions occurring within TNO, and clearly highlight the need to stabilize the surfaces of TNO in order to prevent such aggressive deterioration at the surface of the particles.

25 ENERGY STORAGE↗