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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Robust Containment Queries over Collections of Rational Parametric Curves via Generalized Winding Numbers

Point containment queries for regions bound by watertight geometric surfaces, i.e., closed and without self-intersections, can be evaluated straightforwardly with a number of well-studied algorithms. When this assumption on domain geometry is not met, such methods are either unusable, or prone to misclassifications that can lead to cascading errors in downstream applications. More robust point classification schemes based on generalized winding numbers have been proposed, as they are indifferent to these imperfections. However, existing algorithms are limited to point clouds and collections of linear elements. We extend this methodology to encompass more general curved shapes with an algorithm that evaluates the winding number scalar field over unstructured collections of rational parametric curves. In particular, we evaluate the winding number for each curve independently, making the derived containment query robust to how the curves are arranged. We ensure geometric fidelity in our queries by treating each curve as equivalent to an adaptively constructed polyline that provably has the same generalized winding number at the point of interest. Our algorithm is numerically stable for points that are arbitrarily close to the model, and explicitly treats points that are coincident with curves. We demonstrate the improvements in computational performance granted by this method over conventional techniques as well as the robustness induced by its application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Infrasonic directivity of monopole, dipole and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (⁠<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (⁠<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Infrasound↗
DOE OSTI2024

Extracting Topological Orders of Generalized Pauli Stabilizer Codes in Two Dimensions

In this paper, we introduce an algorithm for extracting topological data from translation invariant generalized Pauli stabilizer codes in two-dimensional systems, focusing on the analysis of anyon excitations and string operators. The algorithm applies to Z d qudits, including instances where d is a nonprime number. This capability allows the identification of topological orders that differ from the Z d toric codes. It extends our understanding beyond the established theorem that Pauli stabilizer codes for Z p qudits (with p being a prime) are equivalent to finite copies of Z p toric codes and trivial stabilizers. The algorithm is designed to determine all anyons and their string operators, enabling the computation of their fusion rules, topological spins, and braiding statistics. The method converts the identification of topological orders into computational tasks, including Gaussian elimination, the Hermite normal form, and the Smith normal form of truncated Laurent polynomials. Furthermore, the algorithm provides a systematic approach for studying quantum error-correcting codes. We apply it to various codes, such as self-dual CSS quantum codes modified from the two-dimensional honeycomb color code and non-CSS quantum codes that contain the double semion topological order or the six-semion topological order. Published by the American Physical Society 2024

Physics↗
DOE OSTI2026

Chromium-for-Aluminum Substitution in Synthetic Serpentine

Cr-bearing clay minerals are products of hydrothermal alteration and fluid–rock interactions of ultramafic rocks that form serpentine minerals. Cr is typically observed to substitute for Al in serpentine minerals, but the crystal chemistry and environmental constraints on this substitution are unknown. Here, we synthesized endmember and Cr-substituted amesite, a typical Al-serpentine mineral, via the hydrothermal method. We found that the phase purity highly depends on the pH of the hydrothermal solution, which should be controlled at ~12.7 to avoid the formation of impurity phases. Additionally, amesite can incorporate Cr at a concentration equivalent to ~39.5% substitution of Al. The Cr-free and Cr-substituted amesite are highly defective and contain multiple polytypes, including 6R 2 , 2M 1 , and possibly 2H 2 . However, the relative proportions of these polytypes do not change with increasing chromium substitution.

Al-lizardite↗
DOE OSTI2024

One-Step Spark Plasma Erosion Processing of Carbon-Coated Sn-Si Nanoparticles for Lithium-Ion Battery Anodes

High density portable energy storage is desirable owing to the energy requirements of portable electronics and electric vehicles. The Li-ion battery’s high energy density could be even further improved through the utilization of alternative materials (instead of carbon) for the anode, such as Sn or Si. Nonetheless, the large volume expansion upon lithiation, up to ~300% for Li 22 Si 5 , causes pulverization and rapid capacity degradation during cycling. Sn also forms a Li 22 Sn 5 compound with the equivalent stoichiometric Li capacity but with enhanced ductility. Nano-sized Si and Sn have demonstrated distinctive nanoscale properties, facilitating the retention of higher capacities, particularly when coated with carbon, which improves mechanical stability. To date, the methods of synthesizing coated Si, Sn, or Si-Sn alloyed nanoparticles are complicated, costly, and not readily scalable to meet the demands of cost-effective manufacturing. Spark plasma erosion in a hydrocarbon dielectric has been explored as a one-step process to produce Sn-Si alloy nanoparticles coated with a thin carbon film, offering a scalable and cost-effective processing route. The resulting Sn-Si particles exhibited a bi-modal size distribution at ~5 nm and ~500 nm and were carbon-coated, as intended, from the hydrocarbon dielectric breakdown. The spark-eroded nanoparticles were thoroughly characterized using TEM/EDS, XPS, AES, SSNMR, and TGA, and their improved electrochemical performance was assessed through half-cell experiments.

25 ENERGY STORAGE↗
DOE OSTI2025

Abiotic influences on continuous conifer forest structure across a subalpine watershed

Understanding the abiotic drivers of high-elevation forest physiognomy is essential for forecasting how mountain ecosystems will respond to emerging environmental pressures. Most prior studies of these relationships have relied on small samples of the full landscape, resulting in limited power to detect dominant covariates and their interactions. Here we report the first evaluation of abiotic influences on a complement of accurate, wall-to-wall estimates of conifer forest structure and composition at the watershed scale. In a subalpine conifer domain in the Colorado Rocky Mountains (USA), we developed a novel method for deriving stand structure metrics from waveform LiDAR data, which showed high fidelity with field inventory. We quantified the relationships between structural and compositional metrics and climate, topographic, edaphic, and geologic factors. Our results showed that peak snow water equivalent (SWE), snow disappearance rate, and elevation explained most of the variation in forest structure. The highest stand density, basal area, maximum canopy height, and quadratic mean diameter occurred in sites with SWE around one standard deviation below mean, but with long snow residence times. Stand density decreased linearly with elevation, while other metrics peaked between 3000 m and 3200 m. Substrate properties had weaker influence. Continuous mapping of through-canopy forest structure enabled our novel findings of the dominant role of snowpack in explaining structural and compositional variation, and of elevation thresholds. Our reproducible approach facilitates assessment of forest-topoclimate relationships in other conifer-dominated landscapes and improves understanding of the baseline patterns controlling forest structure, which is needed for predicting long-term ecological change.

forest ecology↗
DOE OSTI2026

Carbon–Mineral Slurry Electrodes for Energy-Efficient Lithium Leaching from Low-Grade Clay Feedstocks

Lithium extraction from clay deposits is typically hampered by low lithium grades and the high capital and energy demands of conventional processing. We report an ambient temperature electrochemical leaching method that bypasses high-temperature roasting and concentrated-acid leaching, directly liberating 93% of lithium from low-grade hectorite in 24 h at 1 V, with 77% Faradaic efficiency, an energy intensity of 3.91 MWh/t lithium carbonate equivalent (LCE). Utilizing a carbon-mineral composite slurry electrode strategy we achieve electron-driven lattice deconstruction through iron oxidation coupled with proton uptake to drive lithium deintercalation, offering a new strategy for low-temperature critical-metal recovery. A preliminary cost analysis highlights pathways to achieving cost intensities below $3000/t LCE. Challenges remain in improving current density, extraction kinetics, and demonstrating process scalability, however, this work establishes a foundation for effective electrochemical lithium extraction from abundant but previously uneconomical clay deposits.

Haddad, Andrew Z↗
DOE OSTI2026

Spectral deconvolution without the deconvolution: Extracting temperature from x-ray Thomson scattering spectra without the source-and-instrument function

X-ray Thomson scattering (XRTS) probes the dynamic structure factor of the system, but the measured spectrum is broadened by the combined source-and-instrument function (SIF) of the setup. In order to extract properties such as temperature from an XRTS spectrum, the broadening by the SIF needs to be removed. Recent work [Dornheim et al. Nat. Commun. 13 , 7911 (2022)] has suggested that the SIF may be deconvolved using the two-sided Laplace transform. However, the extracted information can depend strongly on the shape of the input SIF, and the SIF is in practice challenging to measure accurately. Here, we propose an alternative approach: we demonstrate that considering ratios of Laplace-transformed XRTS spectra collected at different scattering angles is equivalent to performing the deconvolution, but without the need for explicit knowledge of the SIF. From these ratios, it is possible to directly extract the temperature from the scattering spectra, when the system is in thermal equilibrium. We find the method to be generally robust to spectral noise and physical differences between the spectrometers, and we explore situations in which the method breaks down. Furthermore, the fact that consistent temperatures can be extracted for systems in thermal equilibrium indicates that non-equilibrium effects could be identified by inconsistent temperatures of a few eV between the ratios of three or more scattering angles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming

Abstract Human activities affect the Earth’s climate through modifying the composition of the atmosphere, which then creates radiative forcing that drives climate change. The warming effect of anthropogenic greenhouse gases has been partially balanced by the cooling effect of anthropogenic aerosols. In 2020, fuel regulations abruptly reduced the emission of sulfur dioxide from international shipping by about 80% and created an inadvertent geoengineering termination shock with global impact. Here we estimate the regulation leads to a radiative forcing of $$+0.2\pm 0.11$$ + 0.2 ± 0.11 Wm −2 averaged over the global ocean. The amount of radiative forcing could lead to a doubling (or more) of the warming rate in the 2020 s compared with the rate since 1980 with strong spatiotemporal heterogeneity. The warming effect is consistent with the recent observed strong warming in 2023 and expected to make the 2020 s anomalously warm. The forcing is equivalent in magnitude to 80% of the measured increase in planetary heat uptake since 2020. The radiative forcing also has strong hemispheric contrast, which has important implications for precipitation pattern changes. Our result suggests marine cloud brightening may be a viable geoengineering method in temporarily cooling the climate that has its unique challenges due to inherent spatiotemporal heterogeneity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CUDO: closed-form universal dwell-time optimization for computer-controlled optical surfacing

Precision optical figuring demands fast and accurate dwell time optimization to reach nanometer- and sub-nanometer-level accuracy in next-generation optical systems. We introduce CUDO (closed-form universal dwell-time optimization), the first, to the best of our knowledge, unified closed-form analytical framework that supports both function-form and matrix-form dwell time models in computer-controlled optical surfacing (CCOS). In contrast to traditional methods, which rely on iterative optimization and hyperparameter tuning, our framework derives direct analytical solutions with no adjustable parameters. This approach unifies the solution principles of existing methods within a single mathematical model, delivering three key advantages: (1) accuracy on par with, or superior to, iterative solvers, (2) substantial reduction in computation time, and (3) numerical robustness. Comparative studies with prior art confirm that closed-form solutions achieve equivalent residual error while removing runtime bottlenecks. By simplifying the implementation and enabling real-time, scalable deployment, CUDO establishes a practical foundation for future deterministic fabrication of large-aperture and high-performance optics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Partnership Center for High-Fidelity Boundary Plasma Simulation (Final Report)

Within the Partnership Center for High-Fidelity Boundary Plasma Simulation (HBPS), work at UT-Austin was aimed at improved verification, validation, and uncertainty quantification (VVUQ) for edge plasma simulations and on performing gyrokinetics simulations of pedestal instabilities and turbulence in order to expand foundational understanding of pedestal transport. Regarding VVUQ, the accomplishments can be summarized as follows. First, it was shown that the Moment Preserving Constrained Resampling technique, when applied periodically in particle-in-cell simulations in the XGC code, can dramatically improve the accuracy of the simulation at essentially equivalent computational cost. Second, a technique for estimating model correlations, which are required to solve the model selection and sample allocation problem in multifidelity UQ techniques, without sampling the highest fidelity, most computationally expensive model, was developed and demonstrated. Third, previously developed methods for estimating statistical and discretization errors were applied to numerical methods relevant to edge plasma simulations, namely in particle-in-cell-based approaches, and shown to work. Finally, benchmark studies for comparing gyrokinetic codes were developed and performed, leading to reasonable agreement between four commonly used codes. Regarding physics studies, gyrokinetic simulations to investigate microtearing modes in the DIII-D pedestal were performed using the GENE code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Automated shaker placement and regularized input estimation for MIMO testing.

Multi-input, multi-output (MIMO) testing is used in component qualification to reproduce operational responses in the laboratory. It is often preferred to single-input and base-shake testing because of the potential for equivalent or better tests using smaller actuators and shorter test suites. Given a target response, two key steps in MIMO test design are selecting actuator locations and solving for input loads. Actuator locations are often manually selected using expert judgment. If an automatic method is used, locations are usually determined by simulating the vibration control problem and minimizing a combination of the input energy and control residuals. To select a configuration, the relative importance of input energy and residuals must be specified. Specifying relative weights is, in general, a manual and subjective process. This paper develops an objective function that compares actuator configurations based on control accuracy and required input energy without any manual parameter tuning. The objective function uses an optimally selected tradeoff parameter for each candidate configuration. To choose actuator locations using the new objective function, a pivoting algorithm for integer programming problems is developed. Starting with an initial configuration (such as the one generated by a greedy algorithm), the pivoting algorithm guarantees an objective function decrease in each iteration until convergence is reached. In a simulation featuring a structure excited by a diffuse acoustic field, electrodynamic shaker locations and regularized inputs are solved for without any analyst-specified parameters. Simulations are performed in MIMO configurations where the number of target responses is less than, equal to, and greater than the number of actuators.

Multi-input multi-output↗
DOE OSTI2025

Towards Automated Reasoning Chains for Verification of LLM-Generated Scientific Code

With the rise of Large Language Model (LLM) generated code, including in domains like scientific computing, ensuring not only syntactical, but also mathematical correctness, has become a critical task. Traditional formal methods approaches often struggle with the ambiguity of floating-point code, and full symbolic execution is extremely costly and limited. We propose a chain-of-reasoning approach that iteratively lifts basic semantics from code into the SPIRAL system and then establishes numerical equivalency to the desired mathematical operation. Here, we leverage the ample mathematical knowledge already formalized in SPIRAL to enable the system to recognize not just different implementations of the same algorithm but fully separate approaches to solving the given problem. The chain establishes tight error bounds on the output of given code with respect to the true continuous solution it approximates, quantifying all sources of error. We demonstrate this approach by establishing the correctness of a pseudospectral solver for a simple 1-dimensional Poisson problem.

Oschatz, Quentin [Carnegie Mellon University,Pitts↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Computing nuclear response functions with time-dependent coupled-cluster theory

We compute nuclear response functions by solving the time-dependent 𝐴-body Schrödinger equation, recording the time-dependent transition moment and extracting spectral information via Fourier transforms. The solution of the time-dependent many-body problem accounts for correlations on top of the mean field by taking advantage of a time-dependent formulation of coupled-cluster theory. As a validation, we focus on electric dipole transitions in 4 He and 16 O and compare moments of the response function distribution to the results of an equivalent static framework, finding negligible discrepancies. We investigate how proton and neutron densities evolve in time, and we see the traditional picture of soft and giant dipole resonances as collective oscillations of protons and neutrons emerging from our calculations in 16 O and 24 O. Furthermore, this method also allows us to investigate the behavior of the nucleus in the presence of a strong electric field. In that regime, the behavior of the system becomes chaotic. Qualitatively, the spectral information obtained in this limit is in line with previous time-dependent mean-field results.

Ab initio calculations↗
DOE OSTI2025

CABO-16S—a Combined Archaea, Bacteria, Organelle 16S rRNA database framework for amplicon analysis of prokaryotes and eukaryotes in environmental samples

Abstract Identification of both prokaryotic and eukaryotic microorganisms in environmental samples is currently challenged by the need for additional sequencing to obtain separate 16S and 18S ribosomal RNA (rRNA) amplicons or the constraints imposed by “universal” primers. Organellar 16S rRNA sequences are amplified and sequenced along with prokaryote 16S rRNA and provide an alternative method to identify eukaryotic microorganisms. CABO-16S combines bacterial and archaeal sequences from the SILVA database with 16S rRNA sequences of plastids and other organelles from the PR2 database to enable identification of all 16S rRNA sequences. Comparison of CABO-16S with SILVA 138.2 results in equivalent taxonomic classification of mock communities and increased classification of diverse environmental samples. In particular, identification of phototrophic eukaryotes in shallow seagrass environments, marine waters, and lake waters was increased. The CABO-16S framework allows users to add custom sequences for further classification of underrepresented clades and can be easily updated with future releases of reference databases. Addition of sequences obtained from Sanger sequencing of methane seep sediments and curated sequences of the polyphyletic SEEP-SRB1 clade resulted in differentiation of syntrophic and non-syntrophic SEEP-SRB1 in hydrothermal vent sediments. CABO-16S highlights the benefit of combining and amending existing training sets when studying microorganisms in diverse environments.

Eitel, Eryn M. (ORCID:0009000723919297)↗
DOE OSTI2026

A New UV Spot Test for Quality Control

Here, we present a fast, low-cost ultraviolet (UV) spot test to screen photovoltaic modules for UV-induced degradation (UVID). The measurement is based on a fiber-coupled arc lamp that delivers a highly accelerated local UV dose-approximately five years of equivalent field exposure in less than a day. Spot-exposed areas are evaluated using electroluminescence imaging. We test a “known bad” product, which was observed to experience UVID in the field, and a “known good” product which did not exhibit UVID in the field. Results indicate that the method may be useful as a quick and relatively inexpensive quality control screening tool for customers and manufacturers.

14 SOLAR ENERGY↗
DOE OSTI2026

Quantum dynamics of cosmological particle production: interacting quantum field theories with matrix product states

Understanding real-time dynamics of interacting quantum fields in curved space-time remains a major theoretical challenge. We employ tensor network methods to study such dynamics using interacting scalar and gauge theories in 1+1 spacetime dimensions, subject to a quench modeling a homogeneously expanding gravitational background. The models considered are the scalar λϕ 4 theory and the Schwinger model, i.e. a Dirac fermion coupled to a U(1) gauge field which is equivalent via bosonization to a scalar field with a cosine self-interaction. In the free scalar limit, both theories reproduce known analytical results, providing a nontrivial numerical validation of bosonization in curved spacetime for the Schwinger model. Our central finding is that self-interactions lead to a suppression of gravitational particle production compared to the free-field case, as evidenced by two-point functions and the spectra of produced particles. We further examine the behavior of entanglement generation and find that interactions suppress entanglement growth in the λϕ 4 theory, while in the Schwinger model, the interplay between suppressed particle production and enhanced inter-particle correlations leads to more complex entanglement behavior. Our results pave the way for further explorations of nonperturbative quantum real-time dynamics of interacting scalar and gauge theories in arbitrary gravitational backgrounds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗