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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Design and Construction of a High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory, together with Lawrence Berkeley National Laboratory, is building a new High Field Vertical Magnet Test Facility (HFVMTF) to be situated in the Magnet Test Facility at Fermilab. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics, and Fusion Energy Sciences, and will serve as a superconducting cable test facility for both communities. The background magnetic field for test samples is 15 T and will be produced by a magnet provided by LBNL operating at 1.9 K in superfluid helium. The samples will be placed in the background magnetic field, cooled to between 4.5 K and a user-specified upper limit, and will be powered with a super-conducting transformer at up to 100 kA. Additionally, this facility will be used to test high-field superconducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program. Presently, the various tasks of the project are at different stages of execution, from conceptual to ready-for-construction designs. Here, this paper describes the parameters and design status of the pit construction, cryostat, heat exchanger, lambda plate, power system, and quench protection and monitoring systems of the facility.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Unraveling the Stable Cathode Electrolyte Interface in all Solid‐State Thin‐Film Battery Operating at 5 V

Abstract Spinel‐type LiNi 0.5 Mn 1.5 O 4 (LNMO) is one of the most promising 5 V‐class cathode materials for Li‐ion batteries that can achieve high energy density and low production costs. However, in liquid electrolyte cells, the high voltage causes continuous cell degradation through the oxidative decomposition of carbonate‐based liquid electrolytes. In contrast, some solid‐state electrolytes have a wide electrochemical stability range and can withstand the required oxidative potential. In this work, a thin‐film battery consisting of an LNMO cathode with a solid lithium phosphorus oxynitride (LiPON) electrolyte is tested and their interface before and after cycling is characterized. With Li metal as the anode, this system can deliver stable performance for 600 cycles with an average Coulombic efficiency >99%. Neutron depth profiling indicates a slight overlithiated layer at the interface prior to cycling, a result that is consistent with the excess charge capacity measured during the first cycle. Cryogenic electron microscopy further reveals intimate contact between LNMO and LiPON without noticeable structure and chemical composition evolution after extended cycling, demonstrating the superior stability of LiPON against a high voltage cathode. Consequently, design guidelines are proposed for interface engineering that can accelerate the commercialization of a high voltage cell with solid or liquid electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2024

High performance Calcium Copper Titanate/Polyimide dielectrics composites enabled through colloidal stabilization

Transition to electrified transportation demands advanced power electronic components with the capability to improve range, reliability, and cost of ownership to accelerate mass market adoption. Thus, improvement in the current designs, manufacturing processes, materials, and components capable of providing reliable and efficient operation at higher temperatures play important roles in meeting future needs. To address these challenges, this article focuses on novel dielectric materials designed to reduce the volume of the most important and bulky component of a power electronic system, a capacitor. A new composite dielectric material was developed by integrating the positive attributes of both polymer and ceramic capacitors to overcome the challenges of state-of-the-art dielectric materials. Further, the developed composite properties have been evaluated and showed promising results, achieving a dielectric constant of 250 at 100 Hz, 25°C, unseen in current literature. Additionally, these materials can function at high temperatures (>150°C) with good breakdown strength, providing promising working conditions for capacitors, especially in electric vehicle applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards accelerating particle-resolved direct numerical simulation with neural operators

In this paper, we present our ongoing work aimed at accelerating a particle-resolved direct numerical simulation model designed to study aerosol–cloud–turbulence interactions. The dynamical model consists of two main components—a set of fluid dynamics equations for air velocity, temperature, and humidity, coupled with a set of equations for particle (i.e., cloud droplet) tracing. Rather than attempting to replace the original numerical solution method in its entirety with a machine learning (ML) method, we consider developing a hybrid approach. We exploit the potential of neural operator learning to yield fast and accurate surrogate models and, in this study, develop such surrogates for the velocity and vorticity fields. We discuss results from numerical experiments designed to assess the performance of ML architectures under consideration as well as their suitability for capturing the behavior of relevant dynamical systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2025

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN

Physics-informed neural network (PINN) has been successfully applied in solving a variety of nonlinear non-convex forward and inverse problems. However, the training is challenging because of the non-convex loss functions and the multiple optima in the Bayesian inverse problem. In this work, we propose a multi-variance replica exchange stochastic gradient Langevin dynamics method to tackle the challenge of the multiple local optima in the optimization and the challenge of the multiple modal posterior distribution in the inverse problem. Replica exchange methods are capable of escaping from the local traps and accelerating the convergence; two chains with different temperatures are designed where the low temperature chain aims for the local convergence, and the target of the high temperature chain is to travel globally and explore the whole loss function entropy landscape. However, it may not be efficient to solve mathematical inversion problems by using the vanilla replica method directly since the method doubles the computational cost in evaluating the forward solvers (likelihood functions) in the two chains. To address this issue, we propose to make different assumptions on the energy function estimation and this facilities one to use solvers of different fidelities in the likelihood function evaluation. More precisely, one can use a solver with low fidelity in the high temperature chain while using a solver with high fidelity in the low temperature chain. Our proposed method significantly lowers the computational cost in the high temperature chain, meanwhile preserving the accuracy and converging very fast. Here we give an unbiased estimate of the swapping rate and give an estimation of the discretization error of the scheme. To verify our idea, we design and solve four inverse problems which have multiple modes. The proposed method is also employed to train the Bayesian PINN to solve the forward and inverse problems; faster and more accurate convergence has been observed when compared to the stochastic gradient Langevin dynamics (SGLD) method and vanilla replica exchange methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High-temperature steam oxidation study of irradiated FeCrAl defueled specimens

Post irradiation examinations (PIE) were performed on irradiated iron-chromium-aluminum (FeCrAl) specimens. These FeCrAl specimens were fabricated at the US Department of Energy's Oak Ridge National Laboratory (ORNL). The experimental setup involved subjecting FeCrAl cladding, along with UO 2 pellets, to irradiation in the Idaho National Laboratory Advanced Test Reactor (ATR). In parallel, the FeCrAl alloy tubing without UO 2 pellets was irradiated at ORNL's High Flux Isotope Reactor (HFIR). After irradiation, the ATR-irradiated rodlet was transported to an ORNL hot cell, where it was sectioned into multiple samples for the PIE and severe-accident testing. The sectioning process revealed that the fuel was not bonded to the cladding and could be easily detached from sectioned cladding slices. Microstructural analysis of the fuel cross sections demonstrated no significant interaction between the fuel and the cladding. Additionally, high-temperature steam oxidation tests on defueled cladding segments showed minimal oxygen uptake even at 1200 °C. Here, the ATR-irradiated specimens began to exhibit signs of enhanced oxidation upon reaching a temperature of 1300 °C. Furthermore, enhanced oxidation was observed on the inner surface of the ATR-irradiated FeCrAl specimen, which had been subjected to 1300 °C for a duration of 1 min. By contrast, high-temperature steam oxidation experiments indicated that the HFIR-irradiated FeCrAl cladding provided good thermal stability when exposed to 1300 °C for up to 4 h. Comparative analysis encompassing the oxidation behavior of the ATR-irradiated fueled FeCrAl, HFIR-irradiated unfueled FeCrAl, and unirradiated FeCrAl suggests that the fuel–cladding interaction, although not visible via standard microscale electron microscopy measurements, may accelerate the deterioration of FeCrAl cladding in beyond-design-basis accident scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Optimization of the Second Target Station cold source moderators using an automated workflow

The Second Target Station (STS) at the US Department of Energy’s Oak Ridge National Laboratory is designed to become the world’s highest peak-brightness spallation source of cold neutrons. Successful completion of the STS, which is currently in the preliminary design phase, will provide transformative new capabilities to examine novel materials for future technologies. At STS, neutrons will be generated by spallation reactions in a solid tungsten target. They will be moderated and thermalized in two cold (20 K) para-hydrogen moderators. Careful optimization of these moderators is essential to the project’s success. To find optimal moderator designs, an advanced optimization workflow integrates high-fidelity neutronics calculations using the Monte Carlo N-Particle (MCNP) transport code MCNP6.2 with state-of-the-art optimization algorithms in the Dakota optimization toolkit. For each design iteration, a parametrized solid CAD geometry is generated in Creo and automatically converted into an unstructured mesh geometry by Attila 4MC for the neutronics calculation with MCNP. Iterations repeat until optimal designs are found. Herein this paper presents the results of a sensitivity and optimization study for the cylindrical and tube moderators. Both moderators can be optimized for maximum peak brightness, maximum time-integrated brightness, or any combination between these extremes. Maximum peak brightness is achieved by using smaller optimal dimensions of the moderators, whereas maximum time-integrated brightness is achieved by using larger dimensions. A Pareto front details the designs that optimally balance both brightness metrics. The Pareto front can be found in only 40–110 iterations with 4–5 design parameters when using the efficient global and Pareto-set optimization algorithms in Dakota. Additionally, important engineering constraints can be taken into account, such as the coupling between the cylindrical moderator radius and aluminum vessel wall thicknesses required to ensure structural integrity of the vessels. This interaction has a significant impact on the resulting optimal designs. Our new, highly efficient, fully automated optimization workflow will be used to optimize additional STS components in the future and can be adopted for design and optimization studies at other experimental neutron and accelerator facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Finite element modeling of electropolishing of radio frequency dipole Nb crab cavity in hydrofluoric-sulfuric acid electrolyte

The superior performance of niobium superconducting radio frequency (SRF) cavities is achieved through meticulous surface treatment, notably via chemical electropolishing, ensuring exceptionally smooth surfaces. While this technique has been extensively employed for cylindrically symmetric structures, addressing more intricate geometries poses significant challenges in achieving uniform polishing and controlled material removal, especially when moving away from retractable cathodes. This presents a multifaceted electrochemical, thermal, and fluid dynamics conundrum. A prime example is the 197 MHz radio frequency dipole (RFD) crabbing cavity proposed for the Electron Ion Collider (EIC) project, exemplifying such complex structures. Our groundbreaking work integrates the localized oxide thickness variation, considering its impact on current distribution and Joule heating, within the framework of multi-physics modeling using the COMSOL® simulation suite. This approach was applied to a comprehensive model of the RFD cavity, allowing us to investigate optimal external cooling water flow conditions necessary for achieving desirable outcomes. In conclusion, this illustrates the increasing utility of such multi-physics codes to greatly aid in designing solutions to challenging processing requirements for increasingly complex accelerator cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Artificial intelligence methods for protein structure and interaction prediction: Recent advances and challenges

Recent advances in artificial intelligence have introduced novel methods for high-accuracy prediction of protein tertiary structures, protein complex structures, and interactions between proteins and other biomolecules, such as small molecules and nucleic acids. Such advancements are accelerating biomedical research and the development of new protein design and bioengineering methods among many other important biotechnology applications. Here, in this review, we outline the recent advances in protein-centric biomolecular structure and interaction prediction, highlight some major challenges in the field, and discuss potential directions to address them.

Morehead, Alex [Lawrence Berkeley National Laborat↗
DOE OSTI2022

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modeling strain and quantum confinement in GaAs/Ga x In 1−x P superlattices for spin-polarized electron sources

In this study, we systematically design and simulate a series of GaAs-based superlattice configurations aimed at enhancing heavy-hole–light-hole band splitting while simultaneously optimizing band alignment to reduce the conduction band barrier, thereby facilitating efficient electron transport. These combined effects are crucial for achieving high electron spin polarization and high quantum efficiency, the two key performance metrics of next-generation spin-polarized electron sources. We investigated three types of superlattice architectures: (1) compressively strained GaAs wells on GaInP barriers, yielding a maximum band splitting of 140 meV, (2) lattice-matched GaAs/GaInP structures, resulting in the maximum band splitting of 75 meV, and (3) tensile strained GaAs wells on GaInP barriers, with a maximum band splitting of 40 meV. The results demonstrate the tunability of heavy-hole–light-hole band splitting and establish a design framework for high-performance spin-polarized photocathodes based on a combination of strain engineering, quantum confinement, and optimized heterostructure design.

Electron sources↗
DOE OSTI2025

Form-factor dependence of neutrino-nucleus cross sections using microscopic methods

To achieve its design goals, the next generation of neutrino-oscillation accelerator experiments requires percent-level predictions of neutrino-nucleus cross sections supplemented by robust estimates of the theoretical uncertainties involved. The latter arise from both approximations in solving the nuclear many-body problem and in the determination of the single- and few-nucleon quantities taken as input by many-body methods. To gauge the sensitivity of realistic nuclear many body methods to these few-nucleon quantities, we compute flux-averaged double-differential cross sections using the Green’s function Monte Carlo and spectral function methods as well as different parameterizations of the nucleon axial form factors based on either deuterium bubble-chamber data or lattice quantum chromodynamics calculations. The cross-section results are compared with available experimental data from the MiniBooNE and T2K collaborations. We also discuss the uncertainties associated with N → Δ transition form factors that enter the two-body current operator. We quantify the relations between neutrino-nucleus cross section and nucleon form factor uncertainties. These relations enable us to determine the form factor precision targets required to achieve a given cross-section precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

X-ray optics for the cavity-based X-ray free-electron laser

A cavity-based X-ray free-electron laser (CBXFEL) is a possible future direction in the development of fully coherent X-ray sources. CBXFELs consist of a low-emittance electron source, a magnet system with several undulators and chicanes, and an X-ray cavity. The X-ray cavity stores and circulates X-ray pulses for repeated FEL interactions with electron pulses until the FEL reaches saturation. CBXFEL cavities require low-loss wavefront-preserving optical components: near-100%-reflectivity X-ray diamond Bragg-reflecting crystals, outcoupling devices such as thin diamond membranes or X-ray gratings, and aberration-free focusing elements. In the framework of the collaborative CBXFEL research and development project of Argonne National Laboratory, SLAC National Accelerator Laboratory and SPring-8, we report here the design, manufacturing and characterization of X-ray optical components for the CBXFEL cavity, which include high-reflectivity diamond crystal mirrors, a diamond drumhead crystal with thin membranes, beryllium refractive lenses and channel-cut Si monochromators. All the designed optical components have been fully characterized at the Advanced Photon Source to demonstrate their suitability for the CBXFEL cavity application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A “Master Curve” Describing Reaction Inhomogeneity and Plating Onset during Fast-Charging of Graphite Electrodes

Lithium plating in porous graphite electrodes is a major limitation for fast charging. Theoretical evidence suggests plating during fast charging is largely due to inhomogeneous intercalation through the electrode thickness (caused by ionic/mass transfer limitations and inherent thermodynamic properties of the graphite material). Numerical and analytical predictions of plating onset during fast charging have been proposed but not compared directly with experiments. This work validates these model predictions against plating onset measurements via the “dOCV” method in graphite half-cells, for various electrode thicknesses and C-rates. Remarkably, it is shown that experimental and theoretical trends in plating onset (vs C-rate and electrode thickness) collapse to a single “master curve” using a nondimensional “reaction inhomogeneity” parameter. This observation supports the hypothesized reaction inhomogeneity mechanism for accelerating plating onset and provides practical guidance for electrode design. Furthermore, this work develops theory to quantify reaction inhomogeneity in situ directly from voltage V vs capacity Q data, using dQ / dV analysis. Here again, experiments and numerical predictions show good agreement, where peaks that correspond to LiC 6 correlate with plating onset. This work provides experimental validation of theoretical tools that can predict plating onset, aid electrode design, and give insight for plating onset mechanisms during fast charging.

25 ENERGY STORAGE↗
DOE OSTI2024

USPAS Digital Low-Level RF firmware and software suite (uspas_llrf) v1.0

The USPAS Digital Low-Level RF firmware and software suite was originally developed for the USPAS 2023 LLRF course, for demonstrating the close loop RF control on the BerkeleyLab Marble FPGA carrier and Zest digitizer platform in controlling the RF field for various accelerators. The suite features Register-transfer level (RTL) designs for the board-support layer, digital signal processing and verification test benches, system-on-chip architecture, and Experimental Physics and Industrial Control System (EPICS) support, utilizing a open-source tool chain.

Du, Qiang↗
DOE OSTI2026

Chromaticity compensation of a ghost collider

The GHOST collider final focus system is a pure quadrupole-drift beamline targeting ¿* = 2 mm at four serial interaction points, with peak ¿-functions reaching ~65 km in the final triplet. Beam tracking simulations reveal that a nominal bunch develops a pronounced C-shape in longitu- dinal phase space at IP1, with ¿¿ growing from 0.15 mm to ~2.3 mm — a factor of ~15× increase that directly re- duces luminosity. The mechanism is identified as chromat- ically amplified betatron path length: off-momentum par- ticles acquire enlarged betatron amplitudes in the high-¿ final triplet, generating excess path length via the geometric ¿¿ = - 1/2 ¿ (¿'2 + ¿'2) ¿¿ integral. Within the monoenergetic Balandin framework, ¿2¿2 with ¿ = - 1/2 ¿ ¿ ¿¿ dominates ¿2¿2 by over four million times; the full beam ¿¿ is a fur- ther factor of ~27 larger, driven by ¿¿ -induced chromatic amplitude growth. Phase-advance scans confirm that ¿¿ is insensitive to the apochromatic (¿ ˜ 0) condition. When combined with the geometric hourglass effect, this distor- tion poses a challenge to maximizing luminosity within the current lattice design.

Gamage, B. [Thomas Jefferson National Accelerator ↗