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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Elemental analysis of air-sensitive frozen molten salt samples using an inert transfer chamber for LIBS/LA-ICP-TOF-MS analysis

A novel inert sample transfer system was developed and employed to enable, for the first time, the analysis of air-sensitive salt samples in a two-volume ablation cell using simultaneous laser-induced breakdown spectroscopy (LIBS) and laser ablation (LA)-inductively coupled plasma (ICP)-time-of-flight (TOF)-mass spectrometry (MS) analysis. Molten salts are of growing interest as a medium for advanced nuclear reactors and nuclear fuel reprocessing technologies continue to be developed around their use. However, compositional analysis of molten salt samples can be challenging because of their air-sensitive nature and varying solubilities leading to inaccurate measurements when digested. LA-based analysis provides an alternate method to digestion and can provide rapid elemental information with little sample preparation. In this study, LIBS and LA-ICP-TOF-MS were used to analyze the Ce content in frozen salt samples taken from a series of electrochemical experiments. Calibrations were built for each technique, and the resulting limits of detection for Ce were estimated to be 107 and 58 µg g −1 for LIBS and LA-ICP-TOF-MS, respectively. Test samples from the electrochemical experiments were analyzed using these calibrations. The results matched bulk digestion-based ICP-optical emission spectroscopy values, and daily trends in Ce concentration changes were identified. Additionally, the LIBS and LA-ICP-TOF-MS analysis was demonstrated for identifying microgram per gram levels of components and detecting trace contaminants. The impurities detected by LIBS included Al, Mg, Ca, and Na. The impurities detected by LA-ICP-TOF-MS included W, Ag, Al, Fe, Ni, Mo, Nd, Sm, Th, and U.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗
DOE OSTI2025

Assembly of small silica nanoparticles using lipid-tethered DNA ‘bonds’

Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.

Chiang, Huat Thart [Univ. of Washington, Seattle, ↗
DOE OSTI2026

Recovery of terephthalic acid from solar PV backsheets using waste solvent from distilled spirits production

Current research on solar photovoltaic (PV) recycling mainly focuses on recovering valuable metals and glass, often neglecting the polymeric components, particularly the backsheets, which are typically landfilled or thermally decomposed. This study explores an innovative approach to upcycle PV backsheets into value-added products, specifically terephthalic acid (TPA), using waste ethanol solvent from the distilled spirits industry. Experimental results show that increasing both exposure time and ethanol concentration significantly enhances backsheet delamination efficiency. Using waste ethanol, a maximum delamination efficiency of 80% was achieved at room temperature after 24 hours. In decomposition trials, both sodium hydroxide (NaOH) and potassium hydroxide (KOH) demonstrated comparable efficiencies (96.6–97.5%) over 8 and 24 hour reactions. With virgin ethanol, NaOH yielded 94–97.5% TPA recovery. Notably, using waste ethanol achieved a TPA recovery efficiency of 96.8%, underscoring the process's economic viability and sustainability. Analytical characterization of TPA recovered after 8 hours showed consistent spectral patterns across both alkalis and solvents, indicating a similar chemical environment and functional groups. The recovered TPA can be repolymerized into high-purity PET, suitable for manufacturing new PV backsheets. This work advances polymer-recycling by demonstrating that an industrial waste solvent (distilled-spirits ‘heads’) can replace virgin ethanol without loss in delamination performance or TPA yield. While PV backsheet PET is a modest share of global PET, using waste ethanol to upcycle this currently under-recycled stream demonstrates a transferable solvent-reuse pathway that can extend to higher-volume PET sources.

Nain, Preeti [Michigan State Univ., East Lansing, ↗
DOE OSTI2024

ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs

A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. This has been developed for a specific type of analysis using ATLAS data, one popularly referred to as Simulation-Based Inference (SBI). The JAX library is used for the parts of the workflow to compute gradients as well as accelerate program execution using just-in-time compilation, which becomes essential in a full SBI analysis and can also offer significant speed-ups in more traditional types of analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Voltage-induced modulation of interfacial ionic liquids measured using surface plasmon resonant grating nanostructures

We have used surface plasmon resonant metal gratings to induce and probe the dielectric response (i.e., electro-optic modulation) of ionic liquids (ILs) at electrode interfaces. Here, the cross-plane electric field at the electrode surface modulates the refractive index of the IL due to the Pockels effect. This is observed as a shift in the resonant angle of the grating (i.e., Δϕ), which can be related to the change in the local index of refraction of the electrolyte (i.e., Δnlocal). The reflection modulation of the IL is compared against a polar (D2O) and a non-polar solvent (benzene) to confirm the electro-optic origin of resonance shift. The electrostatic accumulation of ions from the IL induces local index changes to the gratings over the extent of electrical double layer (EDL) thickness. Finite difference time domain simulations are used to relate the observed shifts in the plasmon resonance and change in reflection to the change in the local index of refraction of the electrolyte and the thickness of the EDL. Simultaneously using the wavelength and intensity shift of the resonance enables us to determine both the effective thickness and Δn of the double layer. We believe that this technique can be used more broadly, allowing the dynamics associated with the potential-induced ordering and rearrangement of ionic species in electrode–solution interfaces.

Chemistry↗
DOE OSTI2024

Efficient exact exchange using Wannier functions and other related developments in planewave-pseudopotential implementation of RT-TDDFT

The plane-wave pseudopotential (PW-PP) formalism is widely used for the first-principles electronic structure calculation of extended periodic systems. The PW-PP approach has also been adapted for real-time time-dependent density functional theory (RT-TDDFT) to investigate time-dependent electronic dynamical phenomena. In this work, we detail recent advances in the PW-PP formalism for RT-TDDFT, particularly how maximally localized Wannier functions (MLWFs) are used to accelerate simulations using the exact exchange. We also discuss several related developments, including an anti-Hermitian correction for the time-dependent MLWFs (TD-MLWFs) when a time-dependent electric field is applied, the refinement procedure for TD-MLWFs, comparison of the velocity and length gauge approaches for applying an electric field, and elimination of long-range electrostatic interaction, as well as usage of a complex absorbing potential for modeling isolated systems when using the PW-PP formalism.

Chemistry↗
DOE OSTI2024

High-yield implosion modeling using the Frustraum: Assessing and controlling the formation of polar jets and enhancing implosion performance with applied magnetization

Frustraums have a higher laser-to-capsule x-ray radiation coupling efficiency and can accommodate a large capsule, thus potentially generating a higher yield with less laser energy than cylindrical Hohlraums for a given Hohlraum volume [Amendt et al., Phys. Plasmas 26, 082707 (2019]. Frustraums are expected to have less m = 4 azimuthal asymmetries arising from the intrinsic inner-laser-beam geometry on the National Ignition Facility. An experimental campaign at Lawrence Livermore National Laboratory to demonstrate the high-coupling efficiency and radiation symmetry tuning of the Frustraum has been under way since 2021. Simulations benchmarked against experimental data show that implosions using Frustraums can achieve more yield with higher ignition margins than cylindrical Hohlraums using the same laser energy. Hydrodynamic jets in capsules along the Hohlraum axis, driven by radiation-flux asymmetries in a Hohlraum with a gold liner on a depleted uranium (DU) wall, are present around stagnation, and these “polar” jets can cause severe yield degradation. The early-time Legendre mode P4<0 radiation-flux asymmetry is a leading cause of these jets, which can be reduced by using an unlined DU Hohlraum because the shape of the shell is predicted to be more prolate. Magnetization can increase the implosion robustness and reduce the required hotspot ρR for ignition; therefore, magnetizing the Frustraum can maintain the same yield while reducing the required laser energy or increase the yield using the same laser energy—all under the constraint that the ignition margin is preserved. Reducing polar jets is particularly important for magnetized implosions because of the intrinsic toroidal hotspot ion temperature topology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗
DOE OSTI2025

Experimental demonstration of transient CHI start-up using a floating biased electrode configuration

Transient coaxial helicity injection (CHI) current start-up in a spherical tokamak (ST) has been demonstrated for the first time using a reactor-relevant floating single biased (FSB) electrode configuration on QUEST. Unlike previous applications of CHI on HIT-II and on NSTX in which the entire ST vessel was split in two using two toroidal ceramic rings as vacuum breaks, in the FSB electrode configuration on QUEST, only the lower outer divertor plate is electrically insulated from the rest of the vessel. This is the CHI injector region. A CHI discharge is generated by driving current, using an external power supply, along magnetic field lines that connect the inner and outer divertor plates in the CHI injector region. The CHI plasma evolution and closed flux formation on QUEST are very similar to those on NSTX and have generated toroidal currents of 150 kA with 100 kA of current flowing on closed flux surfaces. An alternate, force-free model approach has been used to derive the CHI scaling relations. The resulting CHI scaling relations from the model are consistent with the conventional CHI scaling relations, which state that the CHI generated toroidal current is proportional to the CHI injector flux and the CHI injector current is inversely proportional to the toroidal field. These results from QUEST bode well for the application of CHI in a new generation of compact high field STs and low aspect ratio tokamaks in which the space for the central solenoid is very restricted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Ponderomotive barriers in rotating mirror devices using static fields

Particularly for aneutronic fusion schemes, it is advantageous to manipulate the fuel species differently from one another and to expel ash promptly. The ponderomotive effect can be used to selectively manipulate particles. It is commonly a result of particle–wave interactions and has a complex dependence on the particle charge and mass, enabling species selectivity. If the plasma is rotating, e.g., due to E x B motion, the ponderomotive effect can be generated using static (i.e., time-independent) perturbations to the electric and magnetic fields, which can be significantly cheaper to produce than time-dependent waves. We propose that this feature can be particularly useful in rotating mirror machines where mirror confinement can be enhanced by rotation, both through centrifugal confinement and additionally through a ponderomotive interaction with a static azimuthal perturbation. We identify specific static perturbations that generate a ponderomotive barrier and other perturbations that can generate either a repulsive barrier or an attractive ponderomotive well, which can be used to attract particles of a certain species while repelling another. We identify the regimes in which the ponderomotive potential can enhance net plasma confinement and the regime in which plasma confinement is not enhanced. The viability of each of these effects is found to be dependent on the specifics of the rotation profile and the resultant dispersion relation in the rotating plasma.

Aneutronic fusion↗
DOE OSTI2025

Crossflow membrane filtration system for operando fouling characterization using transmission x-ray scattering

Membrane-based separations are widely used for wastewater treatment due to their low cost and efficiency. However, membrane fouling, which is the unwanted deposition or attachment of contaminants on membrane surfaces and/or within membrane pores, remains a major challenge as it increases the mass transfer resistance and reduces membrane productivity. Membrane fouling is typically probed by macroscopic performance metrics, such as flux decline, and ex situ characterization. However, this does not capture the membrane and fouling layer evolution under operating conditions, potentially masking important mechanisms and nonequilibrium pathways that impact fouling. Here, we present a remotely controlled crossflow membrane system and a custom membrane cell for operando fouling characterization using transmission small/wide angle x-ray scattering (SAXS/WAXS). This approach allows direct observation of the nanoscale changes occurring at the membrane surface during pressurized water treatment processes, enabling a new way to understand the connections between dynamic fouling behaviors and membrane performance. Nanoparticle fouling of porous membranes during ultrafiltration was investigated using operando SAXS, and mineral scaling of reverse osmosis membranes was investigated using operando WAXS. Furthermore, this system allows for tracking membrane fouling in real time and under realistic conditions, providing fundamental physical insights into how water chemistry and operating conditions affect macroscopic membrane performance. Moreover, this system opens the door for future in situ and operando studies, and it serves as a testbed for evaluating novel materials/processes for membrane-based separations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Fiber coupled laser ultrasound system using a single mode hollow core fiber for excitation laser: Theory and demonstration for on-machine thickness gauging

Laser ultrasound (LU) is a technique that uses a pump laser and a probe laser to optically generate and detect elastic waves in a material. Despite its advantages over traditional contact transducer-based ultrasound, industrial adoption has been limited by complex optical setups and the inability of multi-mode fibers to deliver a stable Gaussian profile for the pump laser. Here, we report a fully fiber-coupled thermoelastic LU system that uses an anti-resonant hollow-core single-mode fiber to deliver 1 mJ nanosecond pulses of 1064 nm light, while preserving the fundamental Gaussian mode (pump laser). When combined with a fiber-coupled interferometer (probe laser), a small, flexible, and environmentally robust sensor capable of optically generating and detecting high frequency broadband ultrasound is realized. We demonstrate such an LU system implemented in situ on a four-axis precision lathe. High-resolution thickness gauging is performed, before and after precision cutting, by exciting and measuring a zero-group velocity guided wave mode. The measurements are verified with ex-situ traceable coordinate measuring machine data. Mean absolute deviations of 0.1%, of nominal thickness, before cutting, and 0.2% and 0.3%, after stepped and tapered cuts, respectively, are reported. A theoretical background for thermoelastic ultrasound generation in an elastic waveguide is also presented. Attention is given to the effect of the pump laser profile on wave generation to elucidate the importance of using single-mode laser light. The fiber-coupled system demonstrated is well-suited for use in scientific and engineering sensing applications and facilitates the adoption of LU for industrial non-destructive testing.

Engineering↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Depletion Benchmark Analysis on a Lead Fast Reactor Using PyARC/OpenMC

PyARC is a user-friendly fast reactor analysis tool that automates multiphysics workflows using the “extended suite” of Argonne Reactor Computation (ARC) codes by providing a single common input for model definition, code execution, and output post-processing. A lead fast reactor (LFR) benchmark model is used to perform depletion calculations using the newly integrated OpenMC depletion capability in PyARC, building on previous analysis using the ARC codes through PyARC and Serpent. Results for core lifetime k-effective, shutdown decay heat, and end-of-life heavy-metal inventory are compared to verify the PyARC/OpenMC integration against the PyARC/ARC workflow and Serpent for depletion analysis of LFR designs. The results show satisfactory agreement among all three methods, with remaining discrepancies largely attributable to differences in nuclear data libraries and decay-chain modeling detail rather than to fundamental modeling limitations.

Kiesling, Kalin R.↗
DOE OSTI2024

Conceptual Design of a Thermal–to-14-MeV Neutron Conversion Device for Use in the Advanced Test Reactor

Here, this paper details the conceptual design of a thermal-to-14-MeV neutron converter consisting of a mixture of lithium and deuterium in a blanket material. Such a device operates a two-step reaction, first generating tritons via thermal neutron absorption in the tritium breeding material, and in the second step, high-energy neutrons are produced either via deuterium-tritium fusion reaction or with tritium reacting with lithium. A thermal-to-14-MeV neutron converter significantly hardens the neutron spectrum by virtually removing thermal neutrons and adding a high-energy 14 MeV component to the neutron spectrum. While similar concepts have been previously proposed and tested in other reactors, the unique characteristics of the Advanced Test Reactor (ATR), namely its important thermal flux (up to $10^{15}$ n.cm$^{-2}$.s$^{-1}$) makes it markedly attractive for obtaining a very large fast neutron flux, usable for irradiation studies under neutron flux conditions prototypical of fusion reactors. The paper provides a description of a new computational scheme developed for handling the coupled neutron-triton transport mechanism using the Geant4 toolkit. Resulting neutron spectra and high-energy neutron yields are summarized for different irradiation positions and potential neutron breeder materials. Maximum predicted thermal-to-14-MeV neutron yields are on the order of $2.10^{-4}$, which is consistent with previous studies found in the literature. Thus, when placed inside the ATR, such a neutron converter will be providing the largest high-energy neutron source available for activation and irradiation studies of materials foreseen for use in fusion reactors. Future steps will involve qualifying the computational scheme using the ATR critical facility using activation foil measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport

The pebble tracking transport (PTT) algorithm offers a high-fidelity deterministic approach for neutron transport for pebble bed reactors (PBRs). This approach requires the mesh for the active-core region to consist exclusively of tetrahedral elements, where each node in the pebble-packing region represents a pebble centroid. This paper investigates the application of PTT for full-scale PBRs, considering both the isothermal and the temperature-dependent core conditions. Macroscopic cross sections are generated using Serpent 2 full-core eigenvalue simulations where pebbles are grouped into disjoint subsets using machine learning. To minimize the need for individual cross-section sets for each pebble in the core, K-means clustering is used to group pebbles by temperature and neutronic environment parameters. Here, we compare the multiplication factor and power rate distributions between PTT simulations using the Griffin reactor physics software and reference solutions from Serpent 2. Our analysis shows that a full-core, high-fidelity PTT calculation produces accurate results with minimal local (pebblewise) errors. Additionally, timing results indicate that PTT simulations converge rapidly on modern supercomputing platforms.

Griffin↗
DOE OSTI2026

Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models

The configurations of instruments fielded on an experiment affect the amount of information captured and the quality of subsequent inference. Here, we investigate the problem of optimizing plasma x-ray radiation detectors in a magneto-inertial fusion experiment at Sandia National Laboratories. It is impossible to directly measure properties such as the temperature of the thermonuclear fusion plasma produced in these experiments because of the extreme environment and destructive nature of the experiment. Among other diagnostics, several detectors are placed with significant standoff from the fusion target to capture the x-rays emitted by the fusion plasma, which can be used to infer some of its properties. To optimize the configuration of these detectors, a high-fidelity model (HFM) is used for simulating outputs and a low-fidelity model (LFM) is used for inference. We develop methods based on A- and L-optimality criteria that are efficient to compute while explicitly accounting for the discrepancy between the HFM and the LFM. The method allows us to find detector configurations that perform similarly to or better than the configuration obtained using an existing sampling-based optimization method while decreasing computational time by a factor of 50. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Bayesian optimization↗