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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

On the Sampling-Based Computation of Nash Equilibria Under Uncertainty via the Nikaido–Isoda Function

We consider the computation of an equilibrium of a stochastic Nash equilibrium problem, where the player objectives are assumed to be L 0 -Lipschitz continuous and convex, given rival decisions with convex and closed player-specific feasibility sets. To address this problem, we consider minimizing a suitably defined value function defined using the Nikaido–Isoda function. Such an avenue does not necessitate either monotonicity properties of the concatenated gradient map or potentiality requirements on the game but does require a suitable regularity requirement under which a stationary point is a Nash equilibrium. We design and analyze a sampling-enabled projected-gradient-response method, reliant on inexact resolution of a player-level best-response subproblem. Here, by deriving suitable Lipschitzian guarantees on the value function, we derive both asymptotic guarantees for the sequence of generated iterates as well as rate and complexity guarantees for computing a stationary point by appropriate choices of the sampling rate and inexactness sequence.

Nikaido-Isoda function↗
DOE OSTI2025

Sample screening of uranium ore concentrates using portable spectrophotometers: investigating the correlation between visible colors and chemical signatures

A research collaboration between the Japan Atomic Energy Agency and the Department of Energy’s National Nuclear Security Administration examined nuclear forensic signatures and analytical methods for tracing the origins of uranium ore concentrates (UOCs). Here, this study focuses on utilizing portable spectrophotometers capable of reflectance measurements in the visible light spectrum as a potential rapid screening tool for nuclear forensics analysis. Unlike laboratory-based near-infrared spectroscopy or digital image analysis, this research investigated the potential to correlate visible color measurements with key nuclear forensics signatures using seven types of UOC samples with known origins and three UOC certified reference materials. Results demonstrated that distinct color groups, quantified using CIELAB values, correlated with major uranium compounds. Furthermore, the findings indicated that trace elements can influence the UOC colors, providing additional insights into material characteristics. Although this approach requires further validation across a broader range of UOC species, this study demonstrated that simple colorimetric analysis using visible spectrophotometry, which does not require complex sample preparation or data processing, can serve as a practical and novel rapid tool for preliminary screening and attribution in nuclear forensics investigations.

and nuclear chemistry↗
DOE OSTI2025

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.

Karamanis, Minas↗
DOE OSTI2024

3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry

High-energy diffraction microscopy (HEDM) combined with in situ mechanical testing is a powerful nondestructive technique for tracking the evolving microstructure within polycrystalline materials during deformation. This technique relies on a sophisticated analysis of X-ray diffraction patterns to produce a three-dimensional reconstruction of grains and other microstructural features within the interrogated volume. However, it is known that HEDM can fail to identify certain microstructural features, particularly smaller grains or twinned regions. Characterization of the identical sample volume using high-resolution surface-specific techniques, particularly electron backscatter diffraction (EBSD), can not only provide additional microstructure information about the interrogated volume but also highlight opportunities for improvement of the HEDM reconstruction algorithms. In this study, a sample fabricated from undeformed “low solvus, high refractory” nickel-based superalloy was scanned using HEDM. The volume interrogated by HEDM was then carefully characterized using a combination of surface-specific techniques, including epi-illumination optical microscopy, zero-tilt secondary and backscattered electron imaging, scanning white light interferometry, and high-precision EBSD. Custom data fusion protocols were developed to integrate and align the microstructure maps captured by these surface-specific techniques and HEDM. The raw and processed data from HEDM and serial sectioning have been made available via the Materials Data Facility (MDF) at https://doi.org/10.18126/4y0p-v604 for further investigation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2024

Tarda and Tagish Lake: Samples from the same outer Solar System asteroid and implications for D- and P-type asteroids

Here, we report a comprehensive study of the ungrouped type 2 carbonaceous chondrite, Tarda, which fell in Morocco in 2020. This meteorite exhibits substantial similarities to Tagish Lake, Wisconsin Range 91600, and Meteorite Hills 00432, which are generally considered to have originated from a D-type asteroid(s). We constrain the compositions and petrologies of the materials present in a potential sample of a D-type asteroid by reporting the petrography, bulk chemical compositions, bulk H, C, N, Cr, and Ti isotopic compositions, reflectance spectra, and in situ chemical compositions of metals, sulfides, carbonates, and FeO-poor and FeO-rich chondrule silicates of Tarda. We also present new data for Tagish Lake. We then compare Tarda with the other Tagish Lake-like meteorites. Tarda and Tagish Lake appear to be from the same parent body, as demonstrated by their similar petrologies (modal abundances, chondrule sizes), mineral compositions, bulk chemical and isotopic compositions, and reflectance spectra. While the two other Tagish Lake-like meteorites, Wisconsin Range 91600 and Meteorite Hills 00432, show some affinities to Tagish Lake and Tarda, they also share similar characteristics to the Mighei-like carbonaceous (CM) chondrites, warranting further study. Similarities in reflectance spectra suggest that P-type asteroids 65 Cybele and 76 Freia are potential parent bodies of Tarda and the Tagish Lake-like meteorites, or at least have similar surface materials. Since upcoming spacecraft missions will spectrally survey D-type, P-type, and C-type Trojan asteroids (NASA's Lucy) and spectrally study and return samples from Mars' moon Phobos (JAXA's Martian Moons eXploration mission), which is spectrally similar to D-type asteroids, these meteorites are of substantial scientific interest. Furthermore, since Tarda closely spectrally matches P-type asteroids (but compositionally matches the D-type asteroid like Tagish Lake meteorite), P-type and D-type asteroids may represent fragments of the same or similar parent bodies.

58 GEOSCIENCES↗
DOE OSTI2025

Deuterium retention in pre-lithiated samples and Li–D co-deposits in the DIII-D tokamak

Divertor designs involving liquid lithium have been proposed as an alternative to solid designs and wall conditioning techniques. However, Li affinity with tritium poses a risk for the fuel cycle. This study investigates deuterium retention in pre-lithiated samples and Li–D co-deposits in the DIII-D tokamak, making for the first time a direct comparison between Li–D co-deposits and pre-deposited Li films. Samples were exposed to H-mode plasmas in the far scrape-off layer (SOL), and Li powder was injected in-situ with the impurity powder dropper to study the uniformity of Li coatings, and the dependence of fuel retention on Li thickness. The results show that at temperatures below the melting point of lithium, deuterium retention is independent of the thickness of pre-deposited Li layers, with Li–D co-deposits being the primary factor for fuel retention. Both pre-deposited and in-situ deposited Li showed lower erosion than predicted by sputtering yield calculations. These results suggest that fuel retention in fusion reactors using lithium in the divertor will likely be dominated by co-deposits rather than in the divertor itself. If one desires to use Li to achieve flatter temperature profiles, operando Li injection is advantageous over pre-deposited Li films, at least at temperatures below the melting point of lithium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2026

Comparing Liquid Vortex Capture & the Rapid Droplet Sampling Interface for Single Cell Mass Spectrometry

High-throughput single-cell mass spectrometry is a rapidly evolving field that requires innovative sampling and ionization techniques to balance speed, sensitivity, and reliability for metabolomic and lipidomic analyses. This study provides a comparative analysis of two cutting-edge ionization platforms for single-cell analysis: Liquid Vortex Capture (LVC) and Rapid Droplet Sampling Interface (RDSI). The performance was benchmarked by testing pharmaceuticals, EquiSPLASH, and single-cell experiments. RDSI demonstrated up to 100-fold improvements in sensitivity for drugs and lipids such as propranolol, amiodarone, atorvastatin, and phosphocholines in water and phosphate-buffered solutions. This was attributed to its low-flow rate operation (3 μL/min) and reduced dilution. Conversely, LVC excelled in handling higher liquid volumes with greater reproducibility due to its higher solvent flow rate (200 μL/min), enabling increased dilution, solubility, and cleaning. Single-cell uptake of atorvastatin incubated for 10 min, or amiodarone incubated for 24 h in HepG2 cells, similarly revealed up to 85-fold enhancement in sensitivity by RDSI for drugs and lipids. These findings highlight the potential of RDSI for enhancing sensitivity in single-cell drug monitoring and lipidomics.

Cahill, John [ORNL] (ORCID:0000000298664010)↗
DOE OSTI2026

Highlighting the Importance of Authentic Reference Chemicals in the Unambiguous Identification of Unknowns during Routine Sample Analysis─An OPCW Proficiency Test Case

The unequivocal identification of unknown chemicals during routine sample analysis is a constant occurrence in the field of analytical chemistry. The process can be painstakingly tedious, particularly in situations where a tentatively identified unknown may possess isomeric counterparts yielding identical accurate mass values and very similar mass spectra. In this work, we present the experimental process involved in the correct identification of 1,4-oxathiane 4,4-dioxide and differentiation from its constitutional isomer, 2-hydroxyethyl vinyl sulfone, when present in a silica gel matrix featured in the 54th Environmental Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency test. After discovering that the library-generated mass spectrum for 2-hydroxyethyl vinyl sulfone in a preliminary gas chromatography–mass spectrometry (GC-MS) analysis did not match the one from an authentic reference chemical, we embarked on an unknown structure determination campaign involving GC-MS, liquid chromatography-tandem mass spectrometry (LC-MS-MS), and nuclear magnetic resonance (NMR) spectroscopy. All of the information obtained, coupled to the synthesis of an authentic reference chemical, was used to determine the identity of the unknown as 1,4-oxathiane 4,4-dioxide. The process described in this work highlights the important role played by authentic reference chemicals in the identification of unknown chemicals during routine sample analysis.

Chemistry↗
DOE OSTI2025

Multimodal Ambient Pressure Sample Environment for the HIPPIE Solid-Gas Endstation at MAX IV Laboratory

The HIPPIE APXPS instruments have undergone several major upgrades, such as developing a dedicated solid gas endstation to specialize in multimodal ambient pressure sample environments centered around X-ray photoelectron spectroscopy. Herein, the technical specifications of the HIPPIE solid gas endstation are detailed; upgrades to the laser heating and gas systems, as well as the addition of an offline 1 bar reactor, are introduced. To demonstrate how the endstation is currently being utilized, scientific examples of all upgrades are presented, as well as science cases using infrared reflection-adsorption spectroscopy. The HIPPIE solid gas endstation is maturing into an instrument offering bespoke sample environments aimed at pushing experimental capabilities, especially in the time-resolved domain.

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

Realizing string-net condensation: Fibonacci anyon braiding for universal gates and sampling chromatic polynomials

Abstract The remarkable complexity of a topologically ordered many-body quantum system is encoded in the characteristics of its anyons. Quintessential predictions emanating from this complexity employ the Fibonacci string net condensate (Fib SNC) and its anyons: sampling Fib-SNC would estimate chromatic polynomials while exchanging its anyons would implement universal quantum computation. However, physical realizations remained elusive. We introduce a scalable dynamical string net preparation (DSNP) that constructs Fib SNC and its anyons on reconfigurable graphs suitable for near-term superconducting processors. Coupling the DSNP approach with composite error-mitigation on deep circuits, we create, measure, and braids Fibonacci anyons; charge measurements show 94% accuracy, and exchanging the anyons yields the expected golden ratioϕwith 98% average accuracy. We then sample the Fib SNC to estimate chromatic polynomial atϕ + 2 for several graphs. Our results establish the proof of principle for using Fib-SNC and its anyons for fault-tolerant universal quantum computation and aim at a classically hard problem.

Science & Technology - Other Topics↗
DOE OSTI2026

Towards utility-scale electronic structure with sample-based quantum bootstrap embedding

One of the main applications for which quantum computers are hoped to find utility is in simulating ground state energies and other observables of molecular chemical systems. The recently proposed sample-based diagonalization method is a readily implementable method for this task on current-day hardware using short circuit depths and has been demonstrated on as many as 85 qubits in recent studies. In this work, we combine the recently proposed quantum bootstrap embedding (QBE) method with sampled-based diagonalization (QBE-SQD) and present the first benchmarking study of the QBE method on real quantum hardware, ibm_pittsburgh, a Heron r3 processor with 156 qubits. Our test system is a hydrogen ring with 8 hydrogen atoms in the cc-pVDZ basis. We show that for this system, QBE-SQD using an active space of (8e, 19o) per fragment with a 43 qubit footprint produces a ground state energy accuracy which exceeds that of an SQD calculation with an (8e, 30o) active space with a 67 qubit footprint when using a comparable number of Slater determinants. This demonstrates that the use of quantum bootstrap embedding techniques is a promising path towards extending the capabilities of state-of-the-art quantum eigensolvers on near-term devices.

Bierman, Joel [North Carolina State University, Ra↗
DOE OSTI2025

Detection of Br and I as atomic anions using liquid sampling – atmospheric pressure glow discharge/Orbitrap mass spectrometry

The quantification and determination of halogen isotope composition is essential in many fields including geochemistry and nuclear forensics. Detection of the halogen elements is commonly attempted with inductively coupled plasma mass spectrometry (ICP-MS) however, there are multiple challenges faced. Most significantly this includes very poor ionization efficiency and the potential for isobaric interferences from either matrix or plasma species. Thus, sensitivity and accuracy are often limiting issues. Here a liquid sampling-atmospheric pressure glow discharge (LS-APGD) ionization source is coupled with an ultrahigh resolution Orbitrap MS to perform halogen detection of bromine and iodine as initial analytes. This facilitates simple and sensitive detection of these elements as atomic anions from simple aqueous salt solutions. Collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) energies were optimized to produce the maximum response of Br − and I − . The LS-APGD conditions were optimized using a design of experiments (DOE) approach for Br − and I − concurrently. Response curves for Br − and I − solutions determined limit of detection (LOD) values of 50 pg and 5 pg, respectively, in 20 μL aliquots. The curves indicated response factors of 0.67 for 79 Br − and 0.90 for 127 I − . Br isotope ratios were determined with precision between 0.7 and 7.3% RSD, with the isotope ratios determined with precision 0.8% RSD at concentrations above the limit of quantification. Preliminary tests were conducted to evaluate the effect of different cations (Na + , K + , and Mg 2+ ) on Br − responses, with no discernible impacts observed on the halogen signal responses. This study demonstrates the potential use of the LS-APGD-Orbitrap-MS for the detection of multiple halogens while avoiding interferences, minimizing sample preparation, and overcoming ionization barriers.

Lang, Dehlia A. [Clemson University, SC (United St↗
DOE OSTI2025

A simple and practical wax-encapsulation method for air-sensitive XAS samples

To facilitate X-ray absorption spectroscopy (XAS) measurements of air-sensitive samples, we present a simple method in which materials are encased in common paraffin wax to protect them from air and moisture. We demonstrate the efficacy of this approach using a highly reducing, air- and moisture-sensitive uranium(III) complex, the tris(amide) U[N(SiMe 3 ) 2 ] 3 (1). When finely dispersed in a boron nitride matrix and subsequently encased in inert paraffin wax, samples of 1 remain stable with no visible or spectroscopic degradation after several days under ambient conditions. The viability of this method for XAS measurements was further evaluated across a series of uranium compounds, ranging from uranyl species to highly air- and moisture-sensitive molecular complexes, at the uranium L 3 -edge. Edge energy determinations were highly reproducible (±0.1 eV between replicates) and, where available, showed excellent agreement with literature values. In conclusion, this low-cost, effective, and versatile method offers a viable solution for XAS studies of air-sensitive compounds and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Deep learning–driven rare-event sampling reveals an Ala7/d-Ala8 conformational hinge governing amphiphilic switching in cyclosporine A

Passive membrane permeability of N-methylated macrocyclic peptides remains poorly understood because high-energy conformational intermediates are rarely sampled by conventional methods. Using the deep learning–driven rare-event sampling framework ES-CRUMPLE, we show that cyclosporine A accesses transient amphiphilic states via a localized conformational hinge at Ala7/d-Ala8, revealing a kinetic design handle that is invisible to population-based analyses.

Lindberg, Edward T [University of Tennessee, Knoxv↗
DOE OSTI2025

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗
DOE OSTI2025

AC electrical transport detection of magnetic properties of small, granular, and heterogeneous samples

Experimental constraints and sample limitations can preclude ideal measurements of electrical transport properties of materials. In such situations, AC electrical transport methods are often employed due to a significant increase in signal-to-noise ratio they can provide. However, dynamic effects that are not often accounted for may be present that may modify the signals in these measurements. In particular, dynamic filtering effects are prominent in small, granular, and heterogeneous materials. We demonstrate that a lock-in amplifier based circuit can distinguish between these DC transport and AC filtering effects. Here, we further demonstrate that this filtering can reveal distinct signatures of magnetic transitions while providing a measure of sample quality.

47 OTHER INSTRUMENTATION↗