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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

CHESS 2025: Field-collected vegetation attributes and site photos

This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Samples were collected in the field using tablet computers and digital forms, with target data differing by sample type (individual trees, individual shrubs, or 1-meter square plots of meadow and subshrub vegetation). Field samples were collected within 72 hours of airborne data collection using the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. Remote sensing data for the project is available on ESS-DIVE (DOI and citation to be added upon publication). Field data collected included canopy height and per-species horizontal proportional cover for meadow plots, species identity and height information for shrubs, as well as species identity, height, diameter at breast height, and health assessment information for trees. Photos of the focal site and surrounding landscape were taken for all sampling sites and are included in this archive. Green leaves or needles were collected for plant trait and foliar chemistry analysis. This data is archived separately (DOI and citation to be added upon publication). High-precision geospatial data for each sample (crown perimeter polygons for trees and shrubs, plot boundaries for meadow plots) is available here (Henderson et al., 2026). Field and remote sensing protocols largely followed those of a previous field and airborne imaging campaign performed in 2018 (described in Chadwick et al. 2020). Field data from the 2018 campaign can be found here (Chadwick et al., 2020 doi:10.15485/1618130). Because different field measurements were taken for meadow, shrub, and tree sites, data from these three sample types are archived as separate tables (chess_meadow_site_cleaned.csv, chess_shrub_site_cleaned.csv, chess_tree_site_cleaned.csv). Meadow proportional cover data is stored in a separate table (chess_meadow_cover_cleaned.csv). Taxonomy was treated identically between sample types, and the dataset shares a common set of voucher specimens (chess_voucher_IDs_cleaned.csv), as well as a single species list (chess_species_list_cleaned.csv). All taxonomic determinations were performed to the species level, and adhere to the Global Biodiversity Information Facility (GBIF) backbone taxonomy as of January 10th, 2026 (GBIF Secretariat 2023). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2025

Microcarbonation of Naphthalene: An Experimental and Computational Study of Photoionization in Naphthalene-Carbon Dioxide Clusters

The photoionization of naphthalene (N)-carbon dioxide (CO 2 ) clusters was studied using tunable vacuum ultraviolet (VUV) radiation from a synchrotron in the photon range of 8.0 to 13.7 eV, in combination with time-of-flight mass spectrometry. Clusters of monomer, dimer, and trimer naphthalene with CO 2 (N­(CO 2 ) 0–6 , N 2 ­(CO 2 ) 0–3 , N3) were observed. The lowest-energy conformers were obtained via a conformer search, followed by geometry optimizations at the ωB97X-V2/aug-cc-pVTZ (monomer) and ωB97X-V2/aug-cc-pVDZ (dimer) levels of theory. Carbon dioxide was found to preferentially cluster on top of the naphthalene molecule (in an out-of-plane configuration). From the mass spectra, photoionization intensity curves (PICs) were constructed, and appearance energies (AEs) were determined. No substantial trend in AE was observed with increasing size of the naphthalene-carbon dioxide clusters; rather, AE oscillations around the value for pure naphthalene were observed. These AE oscillations are also observed in a recently studied naphthalene-water cluster system, though in this system a slight downward trend in AE for pure naphthalene clusters (N1/2/3/4) was observed. The differences between the two systems are attributed to differing interaction strengths. In conclusion, understanding these differences may aid in determining how photoprocessing can proceed differently depending on the dominant matrix component in interstellar ices.

Wannenmacher, Anna [Lawrence Berkeley National Lab↗
DOE OSTI2025

Status Report on Design of In-situ Thermomechanical Testing at LANSCE

Nuclear fuel encounters severe thermomechanical environments in which its mechanical response is determined by its microstructure, temperature and stress level histories. Simulating the response of such microstructures is crucial for predicting both performance and transient fuel mechanical responses and experimental verification of such predictions is therefore of great interest. While most of the deformation in a nuclear fuel rod occurs in the cladding, deformation of the fuel itself is still of interest with deformation mechanisms at operating temperature and above including creep, swelling, cracking as well as pellet-clad interaction. Characterization of these properties and understanding of the underlying deformation phenomena at operating or excursion temperatures is therefore of great importance for development and ultimately licensing of improved and novel nuclear fuel forms. Diffraction techniques offer unique insight on the atomistic (e.g. crystal structure) and microstructure (e.g. phase transformations, texture, defects) length scales and have a long history of providing unique data to inform relevant deformation models that enable the required predictive capabilities. For example, dislocations lead to diffraction peak broadening that can be characterized to estimate the dislocation density and study the role of dislocations on the deformation while measuring lattice strains allows to studie load sharing in two phase materials. In this report the requirements for a sample environment for high temperature deformation of nuclear fuels are defined. The HIPPO neutron time-of-flight diffractometer at LANSCE will host this sample environment and is also described. This instrument covers diffraction angles from 140° to 40° and is also equipped with an event-mode neutron imaging detector system, enabling energy-resolved neutron imaging in parallel with the diffraction that could measure sample temperature from Doppler broadening of neutron absorption resonances or measure pore densities from changes in the attenuation. Designs of devices to characterize thermomechanical properties of nuclear fuel without diffraction are also considered to guide the design. While this report is focused on applications for nuclear fuels, the device can also characterize cladding, moderator or structural materials and therefore contribute to other fields of research and development for advanced reactors. The temperatures planned to be reached are above 2000℃, thus enabling characterization of LWR reactor fuels under accident scenarios but also reaching temperatures of fuels developed for nuclear thermal propulsion and providing opportunities to characterize those. In conjunction with the energy-resolved neutron imaging detector, this setup would allow to measure neutron cross-sections at high temperatures, filling a gap towards development of reactors operating at high temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Quantifying health benefits of sustainable aviation fuels: Modeling decreased ultrafine particle emissions and associated impacts on communities near the Seattle-Tacoma International Airport

Exposure to ultrafine particles (UFP, ≤100 nm) is an emerging health concern linked to premature mortality, with jet fuel combustion identified as a significant source of UFPs near airports. Sustainable aviation fuel (SAF) adoption has the potential to reduce aviation-related UFPs and may particularly benefit populations who reside nearby. However, assessing aviation-specific impacts on health remains challenging due to the lack of tools capable of addressing: fine-scale exposure evaluation, novel ambient pollutants, and groups with increased exposure or susceptibility. We develop and apply a method to estimate reductions in mortality associated with aviation-related UFP reductions at the Seattle-Tacoma (SEA-TAC) International Airport under SAF adoption scenarios, with a focus on near-airport communities. Using UFP exposure surfaces generated from AERMOD modeling, flight count data, and UFP measurements, we evaluated UFP reductions under various control scenarios. We estimated mortality reductions by combining this with population data, baseline mortality, and a hazard ratio of 1.012 (95 % confidence interval: 1.010, 1.015) per interquartile range increment of 2723 particles/cm 3 . Our analysis included 412 census tracts representing almost 1.5 million adults. Baseline aviation-related UFP exposures averaged 1145 (SD: 277) particles/cm 3 . The highest baseline concentrations and subsequent reductions under SAF scenarios were near SEA-TAC. Mortality case reductions averaged between 3.1 (95 % range: 2.5–3.7) for a 5 % UFP reduction to 31.0 (24.6–37.4) for a 50 % reduction, with corresponding mortality rate reductions of 0.2 (0.2–0.3) to 2.1 (1.7–2.5) cases per 100,000 people per year. Mortality rate reductions were larger among populations residing closer to SEA-TAC, including those that were Hispanic or Latino, below-poverty, and did not identify as White. Reducing aviation-related UFPs through SAF adoption could lead to lower mortality, particularly in near-airport communities. This reproducible approach can be adapted to other settings to evaluate health benefits from aviation-related UFP reductions.

Aviation-related air pollution↗
DOE OSTI2025

Ultrasonic Characterization of Lithium Ion Thermal Runaway Conditions for Real-time Ultrasonic Enabled BMS Integration

The demand for energy storage is growing, and lithium-ion batteries are a promising technology to meet this need due to their high power/energy density, high round-trip efficiency, rapid response time, and portability. However, recent catastrophic events caused by thermal runaway have slowed their adoption, highlighting the need for an early warning system for battery failure. In this work, ultrasound is used to detect physical changes in 950 mAh batteries by identifying material property changes independent of voltage and current. [Ultrasound signal features (e.g., time of flight, maximum frequency component) were extracted as the batteries were cycled and subjected to both constant current and constant voltage overcharge and were used to develop two metrics identifying failure: a warning to detect the start of overcharge and an emergency stop (E-stop) to immediately take the battery out of service. The identification method involved locating magnitude differences of several ultrasound features compared to baseline operation considering different currents and temperatures, and the warning/stopping metrics were consistent across all experiments. For an average overcharge time of 140 minutes, the average warning was issued 124 minutes before the failure and the average E-stop was triggered 94 minutes before failure. As a test of using ultrasound for early warning detection, a battery was forced into overcharge and returned to normal cycling conditions based on the previously determined warning metric. Both the voltage profile and the ultrasound measurements returned to their baseline behavior, indicating that ultrasonic detection can not only identify battery failure before a catastrophic event, but can also provide early enough warnings such that overcharges can be detected and corrected quickly enough so the battery does not need to be decommissioned.]

25 ENERGY STORAGE↗
DOE OSTI2026

Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO 3 H 3 − (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.

HER active sites↗
DOE OSTI2026

Machine learning inversion of interatomic force constants from single-crystal inelastic neutron scattering

Atomic vibrations govern many macroscopic properties of materials, but experiments to comprehensively probe them remain challenging. Inelastic neutron scattering (INS) is a powerful technique to map phonon dispersions in crystals, especially when leveraging modern time-of-flight (ToF) spectrometers with large detectors. However, efficiently and robustly extracting interatomic force constants (FCs) parameterizing phonon dynamics from experimental spectra remains a bottleneck due to the complexity and high dimensionality of ToF INS datasets. Here, we present a machine learning approach for the direct inversion of FCs from single-crystal INS measurements. The framework leverages synthetic training data generated using universal machine-learned force fields and an efficient physics-based forward model. We benchmark two neural architectures–one emphasizing structured latent representation learning and the other direct, supervised spectral regression–across simulated datasets for two materials under idealized and noisy conditions. The latent-representation model is subsequently applied to experimental single-crystal INS data on germanium. The model is shown to reproduce FCs derived from both first-principles simulations and from iterative optimization, and furthermore achieves reliable inference even from sparse, single-orientation measurements representing short data acquisitions. Analysis of the learned latent space reveals semantically continuous and physically interpretable encodings that support strong cross-domain generalization. By bridging theoretical and experimental domains, we establish a path toward rapid inversion of experimental spectra and data-driven interpretation of temperature-dependent lattice dynamics.

42 ENGINEERING↗
DOE OSTI2025

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Microstructure-dependent particulate populations in ODS steels revealed by single-particle ICP-TOF-MS

In this work, we evaluated the ability of single-particle inductively coupled plasma time-of-flight mass spectrometry (SP-ICP-TOF-MS) to characterize particulates generated from 300 series stainless steels and oxide dispersion–strengthened (ODS) steels. Particulates were produced using two different rotary tools (cutting disk and grinding bit) to assess the influence of particle generation on effluent particulates. Across all materials and preparation techniques, SP-ICP-TOF-MS detected a substantial population of particles containing the expected constituent elements, with average compositions closely matching the nominal alloy values. A secondary population of Y-bearing particles was evident in ODS steels; their formation is strongly favored in particulates generated using the grinding bit. Specifically, in PM2000, Y-bearing particles were predominantly colocated with Al, whereas in 14YWT, Y-bearing particles were less frequently Fe-free but showed stronger colocation with Ti. These trends are consistent with the known microstructural differences between Y–Al–O oxide particles in PM2000 and finer Y–Ti–O nanoclusters in 14YWT. Together, these results demonstrate that SP-ICP-TOF-MS can resolve distinct particulate populations in complex, multicomponent steels at the femtogram mass scale, enabling particle-resolved insight into microstructure-driven phase separation and preparation-dependent particle generation.

Brubaker, Zach E. [Oak Ridge National Laboratory (↗
DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

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

Effects of dose rate on the microstructure and deuterium retention in γ-LiAlO 2 pellets

This report presents experimental findings obtained from November 2024 to September 2025. Defect accumulation and microstructural evolution during ion irradiation at elevated temperatures are governed by two competing processes: defect production, driven by dose rate, and defect recovery, controlled by defect diffusion, interaction, and annihilation. At a given dose, the resulting microstructural evolution depends on both the dose rate and irradiation temperature. As a continuation of our FY24 tritium science project, which investigated temperature effects at a fixed dose rate, this study focuses on dose-rate effects at a fixed temperature to provide deeper insights into the irradiated microstructure and compositional changes in γ-LiAlO 2 pellets. The study aims to elucidate the impact of dose rate on microstructure, precipitate morphology, deuterium retention, and lithium volatility in γ-LiAlO 2 pellets under sequential 120 keV He + and 80 keV D 2 + ion irradiation. Three dose rates of 7.3×10 4 , 2.9×10 4 and 6.8×10 5 dpa/s were applied to achieve the same total ion fluence of 2×10 17 (He + +D + )/cm 2 at 500 °C, corresponding to a maximum combined dose of 7.55 dpa at ~255 nm. The irradiated pellets were subsequently characterized using scanning transmission electron microscopy (STEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). The microstructural response of γ-LiAlO 2 to ion irradiation was found to be strongly dose-rate dependent. At medium and high dose rates, irradiation produced a surface amorphized layer and an underlying crystalline layer containing LiAl 5 O 8 precipitates, with implanted gases accumulating and forming blisters at the crystalline-amorphous interface. It remains to be investigated whether the amorphized layer was produced by He + ion irradiation prior to D 2 + ion irradiation. In contrast, at low dose rates, the material remained crystalline, with cavities, likely gas-filled, distributed around precipitates, within the γ-LiAlO 2 matrix, and along grain boundaries. While precipitate morphology exhibited anisotropy, their size showed little sensitivity to dose rate in the applied range of this study. This result, however, does not rule out the possibility that further reductions in dose rate could influence precipitate size. High dose-rate irradiation enhanced protonium–deuterium isotopic exchange and lithium depletion in the amorphized region. Collectively, the results show that dose rate governs amorphization, gas redistribution, isotopic exchange, and lithium depletion, providing important insights into the mechanisms underlying structural evolution in γ-LiAlO 2 pellets under reactor-relevant irradiation conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

X-Ray and Particle Detection With the Si(Li) Tracker Module of the GAPS Experiment

Here, this work describes the architecture and the experimental results from the characterization of the lithium-drifted silicon (Si(Li)) detector module, which constitutes the building block of the tracker in the general antiparticle spectrometer (GAPS) experiment to search for dark matter. The instrument is designed for the identification of low-energy cosmic anti-nuclei (antiprotons, antideuterons, and antihelium) to be performed during an Antarctic long-duration balloon flight scheduled for late 2025. The GAPS Si(Li) tracker, that is the core of the instrument, is the assembly of 252 modules, each comprised of four Si(Li) detectors and a full custom-integrated circuit designed for detector readout and produced in a commercial 180-nm planar CMOS technology. A general overview of the detector module architecture and its components is provided, together with a description of the test setup and the experimental results obtained from the characterization of the low-noise analog readout channel. In order to verify the effective operation of the entire module, results concerning the detection of X-rays from a 241Am source and cosmic muons are also provided.

Manghisoni, Massimo [Università di Bergamo (Italy)↗
DOE OSTI2025

An Improved Convection Parameterization with Detailed Aerosol–Cloud Microphysics for a Global Model

Abstract A new microphysical treatment that includes aerosol–cloud interactions and secondary ice production (SIP) mechanisms is implemented in the convection scheme of the Community Atmosphere Model, version 6 (CAM6). The approach is to embed a 1D Lagrangian parcel model in the bulk convective plume of the existing deep convection parameterization. Aerosol activation, growth processes including collision/coalescence, and three processes of SIP mechanisms, two of which are normally overlooked in atmospheric models, are represented in this embedded parcel model. These microphysical processes are treated with a hybrid bin/bulk scheme and a high spatial and temporal resolution for the integration of the embedded parcel in 1D, allowing vertical velocity to determine the microphysical evolution following the in-cloud motion during ascent. Simulations of an observed case (Midlatitude Continental Convective Clouds Experiment) of a mesoscale convective system in Oklahoma, United States, with a single-column model (SCAM) version of CAM, are compared with aircraft in situ and ground-based observations of microphysical properties from the convection and precipitation. Results from the validation show the new microphysical scheme has a good representation of the ice initiation in the bulk convective plume, including the known and empirically quantified pathways of primary and secondary initiation, with benefits for the accuracy of properties of its supercooled cloud liquid. The sensitivity simulations and use of tagging tracers for the validated simulation confirm that the newly included SIP mechanisms are of paramount importance for convective microphysics and can be successfully treated in the global model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Molecular Imaging of Microbially Induced Corrosion of Synthetic Archeological Glasses by a Rhizosphere Bacterium

Microbially induced corrosion (MIC) focuses on the degradation of solid materials, such as glass or metal. Soil microbes are often associated with the corrosion of foreign objects in the rhizosphere. Paenibacillus polymyxa SCE2, a facultative anaerobic bacterium in soil, is of the same genus as bacteria found near nuclear waste disposal sites. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used for imaging surface changes induced by P. polymyxa SCE2 cultured on two synthetic glass coupons to represent natural analogs of materials that were studied in relation to the vitrification of nuclear waste. Multimodal imaging was used to verify bacterial coverage across the glass surface after long-term growth. ToF-SIMS spectral analysis showed detection of glass component ions, such as silicon oxide (m/z – 59.96 SiO 2 – ) and aluminum oxide (m/z – 101.95 Al 2 O 3 – ), and biofilm’s extracellular polymeric substance (EPS) components, such as pentadecanoic acid (m/z – 241.22 C 15 H 29 O 2 – ) and sterol lipids (m/z – 311.16 C 20 H 23 O 3 – ). ToF-SIMS spectral, imaging, and depth profiling analyses showed that the glass rich in silica and other light elements (“granite glass”) had more “corrosion related” peaks than the glass that was less silica-rich and contained more iron (“dike glass”). Furthermore, these surface and interface compositional and spatial differences observed in the mass spectra and imaging were attributed to bacterial metabolism and an electron transfer mechanism influenced by morphological and compositional differences between the two types of glasses. ToF-SIMS is effective in studying microbial effects, bringing new molecular insights into MIC in a broader context of materials degradation.

Amorphous materials↗
DOE OSTI2025

High Power Density, Carbon Neutral Electrical Power Generation for Air Vehicles

The synergistic integration of a Solid Oxide Fuel Cell-Combustor (SOFC-C) with a turbogenerator (TG) will provide a very high fuel-to-electricity conversion efficiency while maintaining high power-to-weight ratio during high-altitude flight. The proposed SOFC-C-TG power generation technology exceeds the REEACH technical performance targets (TPT). This unique concept addresses many of the challenges faced in all electric propulsion-based aviation. The system has high part-load efficiency (more than 65% lower heating value (LHV)) during long cruise times, load following capability, high-power capacity at high altitudes adapting to low temperatures and pressures, rapid startup time of less than 30 minutes (proven with current SOFC technology), high power density (more than 3.2 kW/kg), efficient thermal management, and a foundation for a compact, efficient electrical storage and power generation system (ESPG). The SOFC-C concept achieves the technology targets by reducing the complexity of traditional fuel cell-gas turbine hybrid systems (FC-GT). The SOFC-C does not require heat exchangers and dramatically reduces the balance of plant increasing power density and performance in efficiency. The reduction in mass through elimination of heat exchangers, external reformer, and other components dramatically decreases the overall thermal dampening of the system which enables rapid startup and load following capability. Direct control of the cathode inlet temperature of the SOFC-C enables rapid warm-up of the SOFC tubes with the ability to reach operating temperature and full power in less than 30 minutes.

03 NATURAL GAS↗
DOE OSTI2025

Direct observation of key aluminum hydroxide prenucleation oligomers for gibbsite nucleation and crystallization in sodium aluminate solution by liquid ToF-SIMS

The mechanism of gibbsite (aluminum hydroxide) crystallization from highly alkaline solutions such as Bayer liquors remains poorly understood, where aluminum (Al) transforms from largely tetrahedrally coordinated aluminate monomers in sodium aluminate solutions into a network of octahedra in gibbsite crystals. A variety of traditional analytical approaches applied to this system do not readily reveal the presence of higher-order oligomeric intermediates. To overcome this limitation, we employed in-situ liquid Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to examine the Al species present in concentrated sodium aluminate solutions favoring crystallization of gibbsite or sodium aluminate. A complex mixture of Al oligomers was found. By comparing the change in the relative concentration of Al oligomers with +1 and -1 charge, we were able to identify three major Al oligomer candidates, iso-tetramers, iso-pentamers, and cyclic-hexamers, for the nucleation and crystallization of gibbsite. The concentrations of iso-tetramers and iso-pentamers significantly surpass those of cyclic-hexamers. Time-dependent in-situ Raman spectroscopy analysis indicated that the appearance of gibbsite coincided with the peak concentration of these oligomers. The Density-functional theory (DFT) calculation suggests that the formation of iso-oligomers is more favorable than that of cyclic-hexamers. The combined results suggest that iso-tetramers and iso-pentamers play the most substantial role in the nucleation and growth of gibbsite in the sodium aluminate solutions. Our findings also suggest that the oligomers that promote gibbsite crystallization are more stable in dilute sodium aluminate solutions, making these solutions particularly suitable for efficient gibbsite crystallization. In conclusion, our study fills a major knowledge gap in understanding Al speciation that leads to the nucleation and crystallization of gibbsite in concentrated sodium aluminate solutions.

Bayer liquor↗
DOE OSTI2025

Rapid isotopic analysis of uranium microparticles via SP-ICP-TOF-MS

Inductively coupled plasma – time-of-flight – mass spectrometry (ICP-TOF-MS) was employed for the isotopic analysis of uranium particles of varying 235 U enrichment levels. Here, a single particle (SP)-based introduction scheme was employed such that individual particles, in a suspension, were analyzed. The uranium oxide microparticles were comprised of depleted uranium (DU, 235 U/ 238 U of 0.0017316(14)), natural uranium (NU, 235 U/ 238 U of 0.0072614(39)), and low enriched uranium (LEU, 235 U/ 238 U of 0.051025(15)). The percent relative difference of the SP-ICP-TOF-MS measured isotopic ratios compared to the expected values for the DU, NU, and LEU particle populations were 8.75, 0.12, and 1.23 %, respectively. After characterization, the DU and NU particles were doped within a complex sample matrix (Arizona Test Dust) containing Fe, Ti, Al, and Si particles, among others. Then, the suspension was analyzed via SP-ICP-TOF-MS and the detected particles were classified as DU or NU based on their measured 235 U/ 238 U ratio. In the same analysis, the matrix particles (i.e., Al, Fe, and Ti) were detected, demonstrating the simultaneous nuclide detection provided by the measurement platform. The presented SP-ICP-TOF-MS methodology for uranium particle characterization proved to be a high throughput method for detecting and isotopically discerning uranium particles with varying enrichment levels, in a complex matrix.

Stanberry, Jordan S. [Oak Ridge National Laborator↗