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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Cu-, Co-, and Zn-Based Metal–Organic Framework-Derived Nanoporous Ion Emitters for Picogram Level Analysis of Actinides

Thermal ionization mass spectrometry (TIMS) is often regarded as the preferred technique for trace-level isotopic analysis of actinides owing to its high sensitivity and absence of carry-over effects. However, actinide sample utilization efficiency (SUE) is typically low (<0.05%) without the use of activators or specialized loading approaches which can yield SUEs of >5%. To this effect, we investigate a series of metal–organic framework (MOF)-based nanoporous ion emitters (nano-PIEs) that show enhanced ionization of actinides when used in TIMS loading. We study the impact of physical and chemical properties of MOFs on TIMS SUEs using two families of MOFs that can be synthesized under similar reaction conditions. The structural and chemical properties of these MOFs can be systematically modified one at a time while keeping other features the same. This allows us to strategically investigate their impact on SUEs. The first family of MOFs considered in this study is Zeolitic Imidazole Frameworks (ZIFs) which are made using 2 methyl-imidazole as an organic linker with zinc (ZIF-8) and cobalt (ZIF-67) as metal centers. Additionally, the effect of morphology was also studied using Zn-based ZIF-L with a 2-dimensional structure. The second family of MOFs was synthesized using benzene-1,3,5-tricarboxylate (BTC) with copper (Cu-BTC) and zinc (Zn-BTC) as the metal center. Among the MOFs tested, Cu-BTC showed the highest SUE with an average SUE of 0.27 ± 0.15%, followed closely by Zn-BTC (0.24 ± 0.10%), ZIF-8 (0.17 ± 0.10%), and trailed by the other MOFs. When the MOFs were pyrolyzed in N 2 before loading, an apparent increase in the SUE was observed with ZIF-8 and Cu-BTC showing average SUEs of 0.25 ± 0.08% and 0.34 ± 0.13%, respectively, with the highest measured SUE of 0.53% for pyrolyzed Cu-BTC. In conclusion, this observed increase in SUE by up to an order of magnitude compared to bare filaments demonstrates the efficacy and potential of MOF-derived nano-PIEs for TIMS application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Particle-in-cell simulations of expanding high energy density plasmas with laser ray tracing

The design and analysis of high energy density (HED) laser experiments typically rely on radiation hydrodynamics simulations. However, some laser–plasma interaction regimes are not collisional and cannot be adequately modeled with hydrodynamics. For example, strongly driven magnetic reconnection and magnetized collisionless shock experiments possess extended hydrodynamic or even kinetic properties, necessitating first-principles kinetic simulations. In this paper, we present the benchmarking and first results obtained with a laser-ray-tracing and inverse bremsstrahlung absorption module implemented in the particle-in-cell code PSC. The simulation results are compared to radiation hydrodynamic simulations using the FLASH code as well as analytical estimates. We successfully benchmark the energy deposition model and overall hydrodynamic evolution of the systems. We also consider possible kinetic effects that may be expected from laser-target ablation in the HED regime, including non-local transport and two-temperature effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simultaneous analysis of collinear neutron time-of-flight (nToF) traces applied to pulsed fusion experiment

On pulsed fusion experiments, the neutron time of flight (nToF) diagnostic provides critical information on the fusion neutron energy spectrum. This work presents an analysis technique that uses two collinear nToF detectors, potentially to measure nuclear bang time and directional flow velocities. Two collinear detectors may be sufficient to disambiguate the contributions of nuclear bang time and directional flow velocities to the first moment of the neutron energy spectrum, providing an independent measurement of nuclear bang time. In conclusion, preliminary results from measured nToF traces on the National Ignition Facility and additional applications of this technique are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data from: Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery

The repository folder contains spreadsheets and script for soil greenhouse gas (GHG) fluxes, soil moisture, soil temperature, air temperature, and precipitation measurements collected from the Tropical Responses to Altered Climate Experiment (TRACE) at the Sabana Research Field Station, El Yunque National Forest (USDA Forest Service; 18°19′28.74″ N, 65°43′50.09″ W) — an open-air field warming experiment located in a lowland tropical forest in Puerto Rico within the Luquillo Experimental Forest (LEF) — six to seven years after Hurricanes Irma and Maria (2017). All spreadsheets for soil and air microclimate data, as well as soil greenhouse gas data, are included as csv files. Air temperature data are also included as Excel spreadsheets (.xlsx). The script is built in R Studio, which is the only software required to run data analysis. This dataset is associated with the manuscript “Larocca Conte G ; Zuvela L ; Cruz-Pérez R ; Barreto-Vélez T ; Becerra-Santillan N ; Campbell S ; Chu H ; Dam T ; Grullón-Penkova I ; Kleit M ; Ortiz-Iglesias D ; Rubio-Lebrón L ; Cavaleri M ; Reed S ; Sihi D ; Wood T ; O'Connell C., 2026. Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery. Agricultural and Forest Meteorology. In review". The dataset was used to test the effect of warming on soil CH4 dynamics following long-term legacy effects of hurricane disturbance. The dataset includes: - An overall README file in word and pdf format describing methodology and spreadsheets’ structure. - Continuous measurements of soil temperature and moisture from January 2023 to July 2024 measured with Campbell CS655 probes (“TRACE_soil_temperature_and_moisture_2023_cleaned(in).csv” and “TRACE_soil_temperature_and_moisture_2024_cleaned. csv”). - Air temperature data measured with a HOBO MX23O1A data logger (“Hobo air temperature 2023 Sep 2024” and “Hobo air temperature 2023 Sep 2024” – “CSV FILES folders”). - Precipitation data from a nearby weather tower downloaded from González et al. (2025; “sabana_2020-2025.csv”). - Soil CH4 and CO2 effluxes measured intermittently in two summer campaigns (June – August 2023 and June – July 2024) with a LI-COR 8200-01S Portable Smart Chamber coupled with a LI-COR LI-7810 CH4/ CO2/H2O Trace Gas Analyzer (“23_24COMBO2.0.csv”). - R markdown script for data analysis (“Trace new_PLOTS.Rmd”).

54 ENVIRONMENTAL SCIENCES↗

Metabolic flux and resource balance in the oleaginous yeast Rhodotorula toruloides

The yeast Rhodotorula toruloides is a promising bioproduction organism due to its high lipid yields and ability to grow on cheap and abundant substrates. Quantitative, systems-level assessment of its metabolic activity is accordingly merited. Resource-balance analysis (RBA) models capture not only reaction stoichiometry but also enzyme requirements for catalysis, providing valuable tools for understanding metabolic trade-offs and optimizing metabolic engineering strategies. Here, in this work, we present systems-level measurements of R. toruloides metabolic flux based on isotope tracing and metabolic flux analysis. In combination with new proteomic measurements, these flux data are used to parameterize a genome-scale resource balance model rtRBA. We find that S. cerevisiae and R. toruloides grow at nearly indistinguishable rates using similar biosynthetic but dramatically different central metabolic programs. R. toruloides consumes one-fifth as much glucose, which it metabolizes primarily via the pentose phosphate pathway and TCA cycle unlike primarily glycolysis in S. cerevisiae . Overall, across these two divergent yeasts, protein abundances aligned more closely than metabolic flux. Resource balance modeling of these metabolic programs predicts superior theoretical yields but lower productivities in R. toruloides than S. cerevisiae for industrial chemicals, highlighting the value of rapid glucose uptake for productivity but respiratory metabolism for yields.

60 APPLIED LIFE SCIENCES↗

Enhanced sensitivity to trace 238 U impurity of sapphire via coincidence neutron activation analysis

Sapphire has mechanical and electrical properties that are advantageous for the construction of internal components of radiation detectors such as time projection chambers and bolometers. However, it has proved difficult to assess its 232 Th and 238 U content down to the picogram per gram level. Here, this work reports an experimental verification of a computational study that demonstrates 𝛾⁢𝛾 coincidence counting, coupled with neutron activation analysis (NAA), can reach ppt sensitivities. Combining results from 𝛾⁢𝛾 coincidence counting with those of earlier single-𝛾 counting based NAA shows that a sample of Saint Gobain sapphire has 232 Th and 238 U concentrations of <0.26 ppt and <2.3 ppt, respectively; the best constraints on the radiopurity of sapphire.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗

Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel'dovich effect observations

We present a joint analysis of weak gravitational lensing (shear) data obtained from the first three years of observations by the Dark Energy Survey and thermal Sunyaev-Zel'dovich (tSZ) effect measurements from a combination of Atacama Cosmology Telescope (ACT) and Planck data. A combined analysis of shear (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) can jointly probe both the distribution of matter and the thermodynamic state of the gas, accounting for the correlated effects of baryonic feedback on both observables. We detect the shear$~\times~$tSZ cross-correlation at a 21$\sigma$ significance, the highest to date, after minimizing the bias from cosmic infrared background leakage in the tSZ map. By jointly modeling the small-scale shear auto-correlation and the shear$~\times~$tSZ cross-correlation, we obtain $S_8 = 0.811^{+0.015}_{-0.012}$ and $\Omega_{\rm m} = 0.263^{+0.023}_{-0.030}$, results consistent with primary CMB analyses from Planck and P-ACT. We find evidence for reduced thermal gas pressure in dark matter halos with masses $M < 10^{14} \, M_{\odot}/h$, supporting predictions of enhanced feedback from active galactic nuclei on gas thermodynamics. A comparison of the inferred matter power suppression reveals a $2-4\sigma$ tension with hydrodynamical simulations that implement mild baryonic feedback, as our constraints prefer a stronger suppression. Finally, we investigate biases from cosmic infrared background leakage in the tSZ-shear cross-correlation measurements, employing mitigation techniques to ensure a robust inference. Our code is publicly available on GitHub.

Pandey, S. [Johns Hopkins U.; Columbia U.] (ORCID:↗

Tuning Shinkarev’s Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ferrari, Nicholas [Louisiana State Univ., Baton Ro↗

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗

Refining HPCToolkit for application performance analysis at exascale

As part of the US Department of Energy’s Exascale Computing Project (ECP), Rice University has been refining its HPCToolkit performance tools to better support measurement and analysis of applications executing on exascale supercomputers. To efficiently collect performance measurements of GPU-accelerated applications, HPCToolkit employs novel non-blocking data structures to communicate performance measurements between tool threads and application threads. To attribute performance information in detail to source lines, loop nests, and inlined call chains, HPCToolkit performs parallel analysis of large CPU and GPU binaries involved in the execution of an exascale application to rapidly recover mappings between machine instructions and source code. To analyze terabytes of performance measurements gathered during executions at exascale, HPCToolkit employs distributed-memory parallelism, multithreading, sparse data structures, and out-of-core streaming analysis algorithms. To support interactive exploration of profiles up to terabytes in size, HPCToolkit’s hpcviewer graphical user interface uses out-of-core methods to visualize performance data. The result of these efforts is that HPCToolkit now supports collection, analysis, and presentation of profiles and traces of GPU-accelerated applications at exascale. These improvements have enabled HPCToolkit to efficiently measure, analyze and explore terabytes of performance data for executions using as many as 64K MPI ranks and 64K GPU tiles on ORNL’s Frontier supercomputer. HPCToolkit’s support for measurement and analysis of GPU-accelerated applications has been employed to study a collection of open-science applications developed as part of ECP. This paper reports on these experiences, which provided insight into opportunities for tuning applications, strengths and weaknesses of HPCToolkit itself, as well as unexpected behaviors in executions at exascale.

Adhianto, Laksono↗

A Bayesian approach to time-domain photonic Doppler velocimetry analysis

Photonic Doppler velocimetry (PDV) is an established technique for measuring the velocities of fast-moving surfaces in high-energy-density experiments. In the standard approach to PDV analysis, the short-time Fourier transform (STFT) is used to generate a spectrogram from which the velocity history of the target is inferred. The user chooses the form, duration, and separation of the window function. Here, in this study, we present a Bayesian approach to infer the velocity directly from the PDV oscilloscope trace, without using the spectrogram for analysis. This is clearly a difficult inference problem due to the highly periodic nature of the data, but we find that with carefully chosen prior distributions for the model parameters, we can accurately recover the injected velocity from synthetic data. We validate this method using PDV data collected at the STAR two-stage light gas gun at Sandia National Laboratories, recovering shock-front velocities in quartz that are consistent with those inferred using the STFT-based approach and are interpolated across regions of low signal-to-noise data. Although this method does not rely on the same user choices as the STFT, we caution that it can be prone to misspecification if the chosen model is not sufficient to capture the velocity behavior. Analysis using posterior predictive checks can be used to establish whether a better model is required, although more complex models come with additional computational cost, often taking more than several hours to converge when sampling the Bayesian posterior. We, therefore, recommend it be viewed as a complementary method to that of the STFT-based approach.

Allison, James R. [First Light Fusion Ltd., Yarnto↗

Symmetrization of Strong Hydrogen Bond under High Pressure in Bihydroxide-Ion-Containing NaCu 2 (SO 4 ) 2 ·H 3 O 2 Revealed by Experimental Charge Density, Single-Crystal Electron Diffraction, and Neutron Diffraction Studies

In minerals and inorganic compounds, strong hydrogen bonding can lead to the formation of complex ionic species such as the H 3 O 2 – bihydroxide anion and Zundel cation H 5 O 2 + . We studied [NaCu 2 (SO 4 ) 2 ·H 3 O 2 ] natrochalcite, which contains bihydroxide anions and undergoes hydrogen bond symmetrization at the lowest pressure reported so far among inorganic compounds. Hydrogen bond symmetrization leads to changes in the bulk modulus, seismic wave velocities, and proton mobility and plays a primary role in high-temperature superconductivity, but its characteristics are not well understood due to a lack of systematic studies and limitations of experimental methods sensitive to this subtle change. In this work, we applied experimental charge density analysis based on in situ single-crystal X-ray diffraction data, along with the single-crystal neutron and electron diffraction experiments, to probe the behavior of hydrogen atoms during the hydrogen bond symmetrization process under high-pressure conditions. On the way to the symmetrical H-bonding, natrochalcite undergoes a series of complex redistributions of electron density, which we trace with multipole refinement and detailed analysis of changes in the Laplacian of electron density values. Additionally, we deconvoluted the equation of state (volume of the unit cell vs pressure relation) into the atomic equation of states describing dependencies of atomic charges or volumes vs pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Position-Specific Carbon Isotope Fingerprinting of Fluorinated Organics and Degradation Products

Fluorinated organic compounds are of growing environmental and forensic relevance due to their widespread use in pharmaceuticals, agrochemicals, and consumer products, their environmental persistence, and potential ecological and human health impacts. Elucidating their sources and transformation pathways is therefore a major focus of current research. Stable carbon isotope analysis provides a powerful approach for tracing molecular origins and linking parent compounds to degradation products. Recent isotope measurements have largely relied on mass-spectrometry techniques, which provide only an average isotope ratio across a compound. In this work, we employ a novel nuclear magnetic resonance (NMR) spectroscopy tool to determine position-specific carbon isotope ratios ( 13 C/ 12 C) in organofluorine compounds and their degradation products. This approach enables isotope measurements without combustion or extensive purification and, crucially, resolves ratios at individual carbon positions rather than bulk averages. The resulting intramolecular isotope fingerprints are unique to a molecule’s source. Applied to selected pharmaceuticals and pesticides, these fingerprints allow discrimination of chemically identical compounds. Moreover, we show that the 13 C/ 12 C signature at the fluorinated carbon persists through degradation, demonstrated for lansoprazole and fipronil. The 19 F NMR data produced for the 13 C/ 12 C analyses are also well suited for impurity profiling, providing an additional dimension for fingerprinting fluorinated organics. These findings suggest that position-specific isotope analysis can serve as part of a broader suite of tools for source characterization of organofluorine compounds and their breakdown derivatives, with potential applications in product validation, forensics, and linking these compounds to their breakdown products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts

Self-admitted technical debt (SATD) impairs scientific software (SSW), yet its prioritization, sentiment, persistence, and propagation remains underexplored. Understanding how SSW developers express, and address SATD is crucial for improving SSW maintenance, and tooling. This study investigates how SATD types and artifacts in SSW are prioritized, how sentiment relates to urgency, SATD removal and resolution rates, and the extent to which SATD propagates across artifacts. We analyzed nine SSW repositories using a SATD classification model and a semantic embedding-based prioritization heuristic. SATD was examined across multiple artifacts, with sentiment assessed via a fine-tuned transformer. Propagation was traced, priority scores compared to static analysis, and removal and resolution rates quantified. SATD in comments, commits, and pull requests receive higher priority than SATD in issues, with negative sentiment amplifying urgency. Resolution and removal rates lag behind open-source software (OSS) averages. Most SATD remains confined to the originating artifact, but longer propagation chains are rare and correlate with higher priority, highlighting persistent and high impact debt. Prioritization is influenced by artifact type and sentiment, while low removal and resolution rates signal persistent debt. Cross-artifact propagation marks high priority, unresolved SATD, providing empirical guidance for targeted monitoring, review prioritization, and tool supported maintenance in SSW.

Melin, Eric [Boise State University]↗

Application of Nuclear Technology to Art Identification Problems: First Annual Report

Throughout the centuries, as man has become increasingly affluent, his interest in antiquities and objects of art, and the price he has been willing to pay for them, has increased. Inevitably, one result has been to attract the unscrupulous to the production and sale of counterfeit paintings, sculptures, and other works of art. The skill of forgers varies but often is highly sophisticated. However, dealers, museum curators, and other experts have also become more skillful in the detection of forgeries. Scientific tools of increasing sensitivity and sophistication have gradually been applied to the examination of the materials of art and archaeology. Such tools frequently support and render more reliable the judgment of the experts. The quality of forgeries may improve further as their makers become acquainted with the new methods of detection and in turn learn to circumvent or confound the methods. Therefore, the development of still more advanced methods of examination has great utility in the art world. This is particularly true if the ultimate effect is to make circumvention of the methods of examination so costly that the economic incentives for producing forgeries may be substantially reduced, if not eliminated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Doppler Backscattering Data Analysis and Integrated Modeling with OMFIT

One Modeling Framework for Integrated Tasks (OMFIT) is a widely used software tool in the magnetic fusion research community. OMFIT provides magnetic fusion energy researchers with a framework for the development of special-purpose physics modules. This paper describes an OMFIT physics module pertaining to the Doppler Backscattering (DBS) fusion plasma diagnostic. DBS measures density fluctuations and flow velocity through plasma scattering of electromagnetic waves. The OMFIT DBS module was developed to analyze experimental DBS data and facilitate modeling of DBS systems installed on multiple tokamak devices. The OMFIT DBS module is designed to support several analysis workflows: detailed analysis of experimental data, experimental planning, and theory-based synthetic diagnostic modeling. The DBS module uses integrated modeling by leveraging other OMFIT physics modules to perform tasks related to DBS, e.g. ray/beam–tracing simulations, edge-localized mode–synchronized data analysis, magnetic equilibrium reconstruction, and fitting kinetic profile data. Furthermore, this paper describes several supported workflows and serves a reference for the OMFIT DBS module.

Doppler backscattering↗