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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Polywell Revisited

The Polywell fusion concept, originally proposed by Robert W. Bussard in 1985, has been investigated for over four decades as a potential solution for achieving net fusion energy in a compact and economically viable reactor. It combines two distinct approaches: high-beta magnetic cusp confinement of electrons using polyhedral coil configurations and electrostatic ion confinement via a potential well formed by injected electron beams. While the hybrid nature of the Polywell system offers advantages in plasma stability and engineering simplicity, previous efforts have been limited by persistent challenges in achieving sufficient plasma confinement required to generate a net energy gain. Here, in this study, we examine previous works and identify limitations of several Polywell embodiments that have historically impeded progress. We present an updated Polywell physics model incorporating experimental findings and recent first-principles particle-in-cell simulations. This updated model outlines a credible path toward overcoming confinement losses and achieving net energy gain using deuterium-tritium (D-T) fuels. Our findings provide a renewed scientific basis for the continued development of the Polywell fusion concept as a practical and scalable approach to fusion energy.

Electrostatic potential well↗
DOE OSTI2026

Optimizing Cryo-Focused Pyrolysis GC/MS for Tracing Soil Organic Matter Across Diverse Ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for peak deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs plantderived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Topologically Protected Flatness in Chiral Moiré Heterostructures

The observation of delicate correlated phases in twisted heterostructures of graphene and transition metal dichalcogenides suggests that moiré flat bands are intrinsically resilient against certain types of disorder. Here, we investigate the robustness of moiré flat bands in the chiral limit of the Bistritzer-MacDonald model—applicable to both platforms in certain limits—and demonstrate drastic differences between the first magic angle and higher magic angles in response to chiral symmetric disorder that arise, for instance, from lattice relaxation. We understand these differences using a hidden constant of motion that permits the decomposition of the non-Abelian gauge field induced by interlayer tunnelings into two decoupled Abelian ones. At all magic angles, the resulting effective magnetic field splits into an anomalous contribution and a fluctuating part. The anomalous field maps the moiré flat bands onto a zeroth Dirac Landau level, whose flatness withstands any chiral symmetric perturbation such as nonuniform magnetic fields due to a topological index theorem—thereby underscoring a topological mechanism for band flatness. Only the first magic angle can fully harness this topological protection due to its weak fluctuating magnetic field. In higher magic angles, the amplitude of fluctuations largely exceeds the anomalous contribution, which we find results in a physically meaningless chiral operator and an extremely large sensitivity to microscopic details and an exponential collapse of the single-particle gap. Through numerical simulations, we further study various types of disorder and identify the scattering processes that are enhanced or suppressed in the chiral limit. Interestingly, we find that the topological suppression of disorder broadening persists away from the chiral limit and is further accentuated by isolating a single sublattice polarized flat band in energy. Our analysis suggests the Berry curvature hot spot at the top of the K and K ′ valence band in the transition metal dichalcogenide monolayers is essential for the stability of its moiré flat bands and their correlated states. Published by the American Physical Society 2025

Crépel, Valentin (ORCID:0000000302403412)↗
DOE OSTI2026

RFID-Enabled Tamper-Indicating Seal

Tamper-indicating seals protect sensitive materials, valuable equipment, and critical shipments. Most conventional seals must be checked through manual visual inspection and do not provide a digital record of their condition. Some attempts to remove, alter, or bypass a seal may also leave little visible damage, making tampering difficult to identify during routine inspections. Los Alamos National Laboratory has developed a smart tamper-indicating seal that converts even subtle tampering into a persistent digital record. The seal communicates its identity and status wirelessly through standard radio-frequency identification (RFID) readers, giving organizations a faster, more reliable way to verify that an asset has remained secure.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗
DOE OSTI2024

Wastewater Surveillance for Poliovirus in Selected Jurisdictions, United States, 2022–2023

Wastewater testing can inform public health action as a component of polio outbreak response. During 2022-2023, a total of 7 US jurisdictions (5 states and 2 cities) participated in prospective or retrospective testing of wastewater for poliovirus after a paralytic polio case was identified in New York state. Two distinct vaccine-derived poliovirus type 2 viruses were detected in wastewater from New York state and New York City during 2022, representing 2 separate importation events. Of those viruses, 1 resulted in persistent community transmission in multiple New York counties and 1 paralytic case. No poliovirus was detected in the other participating jurisdictions (Connecticut, New Jersey, Michigan, and Illinois and Chicago, IL). The value of routine wastewater surveillance for poliovirus apart from an outbreak is unclear. However, these results highlight the ongoing risk for poliovirus importations into the United States and the need to identify undervaccinated communities and increase vaccination coverage to prevent paralytic polio.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Phosphate amendment drives bloom of RNA viruses after soil wet-up

Soil rewetting after a dry period results in a surge of activity and succession in both microbial and DNA virus communities. Less is known about the response of RNA viruses to soil rewetting—while they are highly diverse and widely distributed in soil, they remain understudied. We hypothesized that RNA viruses would show temporal succession following rewetting and that phosphate amendment would influence their trajectory, as viral proliferation may cause phosphorus limitation. Using 39 time-resolved metatranscriptomes and amplicon data, 2190 RNA viral populations were identified across five phyla, with 26 % of these predicted to infect bacteria, and 11 % fungi. Only 1.2 % of viral populations had annotated capsid genes, suggesting most persist via intracellular replication without a free virion phase. Phosphate amendment altered RNA viral community composition within the first week and amended vs. unamended communities remained distinguishable for up to three weeks. While the overall host community remained stable, certain bacterial populations showed reduced abundance in phosphate-amended soils, likely due to increased viral lysis, as RNA bacteriophages proliferated significantly. Notably, 60 % of the viruses with increased abundance under phosphate amendment belonged to basal Lenarviricota clades rather than well-known groups like Leviviricetes. We estimate RNA bacteriophage infections may affect 10 7 –10 9 bacteria per gram of soil, aligning with the total bacterial population (10 7 –10 10 g -1 soil), suggesting that RNA phages significantly influence bacterial communities post-wet-up, with phosphorus availability modulating this effect.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quarkonium Spectroscopy in the Quark-Gluon Plasma

The properties of bound states are fundamental to hadronic spectroscopy and play a central role in the transition from hadronic matter to a quark-gluon plasma (QGP). In a strongly coupled QGP (sQGP), the interplay of temperature, binding energy, and large collisional widths of the partons poses formidable challenges in evaluating the in-medium properties of hadronic states and their eventual melting. In particular, the existence of heavy quarkonia in the QGP is a long-standing problem that is hard to solve by considering their spectral properties on the real-energy axis. Here, we address this problem by analyzing in-medium thermodynamic quarkonium 𝑇 matrices in the complex energy plane. We first validate this method in vacuum, where the 𝑇-matrix poles of observed states are readily identified. When deploying this approach to recent self-consistently calculated 𝑇 matrices in the QGP, we find that poles in the complex energy plane can persist to surprisingly large temperatures, depending on the strength of the in-medium interactions. While the masses and widths of the pole positions are precisely defined, the notion of a binding energy is not due to the absence of thresholds caused by the (large) widths of the underlying quark or anti-quark spectral functions. Our method thus provides a new and definitive quantum-mechanical criterion to determine the melting temperature of hadronic states in the sQGP while increasing the accuracy in the theoretical determination of transport parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Minimal cyclic behavior in sheared amorphous solids

Although jammed packings of soft spheres exist in potential energy landscapes with a vast number of minima, when subjected to cyclic shear they may revisit the same configurations repeatedly. Simple hysteretic spin models, in which particle rearrangements are represented by interacting spin flips called hysterons, capture many features of this periodic behavior. Yet it has been unclear to what extent individual rearrangements can be described by such binary objects and how such objects interact with one another. Using a particularly sensitive algorithm, we identify rearrangements in simulated jammed packings and select pairs of rearrangements that undo one another to create periodic cyclic behavior. We find that the rearrangement pairs surprisingly persist down to the smallest increments in strain, even in the smallest systems we can study. We explore the statistics of these rearrangement pairs and find that there is a relation between the amount of hysteresis and the energy drop and mean-square displacement of the particles; these results are inconsistent with the scaling found in models that treat rearrangements as localized buckling events. Finally, our analysis shows that there is no clean distinction between the particle motions that represent the identity of a single, individual rearrangement and the particle motions that lead to interactions between separated rearrangements or hysterons. These results offer insight into how complex systems such as amorphous solids can reach a limit cycle.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗
DOE OSTI2024

A Novel Membrane-Associated Protein Aids Bacterial Colonization of Maize

The soil environment affected by plant roots and their exudates, termed the rhizosphere, significantly impacts crop health and is an attractive target for engineering desirable agricultural traits. Engineering microbes in the rhizosphere is one approach to improving crop yields that directly minimizes the number of genetic modifications made to plants. Soil microbes have the potential to assist with nutrient acquisition, heat tolerance, and drought response if they can persist in the rhizosphere in the correct numbers. Unfortunately, the mechanisms by which microbes adhere and persist on plant roots are poorly understood, limiting their application. This study examined the membrane proteome shift upon adherence to roots in two bacteria of interest, Klebsiella variicola and Pseudomonas putida. From this surface proteome data, we identified a novel membrane protein from a non-laboratory isolate of P. putida that increases binding to maize roots using unlabeled proteomics. When this protein was moved from the environmental isolate to a common lab strain (P. putida KT2440), we observed increased binding capabilities of P. putida KT2440 to both abiotic mimic surfaces and maize roots. We observed a similar increased binding capability to maize roots when the protein was heterologously expressed in K. variicola and Stutzerimonas stutzeri. With the discovery of this novel binding protein, we outline a strategy for harnessing natural selection and wild isolates to build more persistent strains of bacteria for field applications and plant growth promotion.

rhizosphere, colonization, membrane proteome, plan↗
DOE OSTI2026

Foundational insights into the mechanical and molecular evolution of porcine skin gelatin during gelation

Gelatin is a widely used material in biomedical fields, particularly in regenerative medicine and tissue engineering, due to its biocompatibility and versatile properties. While prior research has explored methods to enhance gelatin's mechanical strength and stability, fundamental studies on gelatin, specifically its curing process, mechanical stiffness, and chemical evolution during gelation, remain limited. This study uses ultrasonic testing and Fourier Transform Infrared Spectroscopy (FTIR) to examine gelatin's stiffness and molecular changes during gelation. Samples of 175 and 300 Porcine Skin Bloom Strength Gelatin at concentrations of 2% and 6% (w/v) were analyzed. Through transmission ultrasonic testing helped identify key transition points in gelation, with higher concentrations exhibiting delayed transitions. FTIR revealed that C-N bond formation peaks early while N-H bond deformation persists. A correlation emerged between sound speed and peak absorbance, suggesting that changes in molecular mobility may contribute to the observed sound speed behavior during periods of active bond formation. However, as gelation continues, fewer bonding components may be available, potentially decreasing molecular movement and contributing to the observed increase in sound speed. These findings provide insights into gelatin's mechanical and chemical evolution, offering a framework for improved control over its gelation kinetics. Swept-Frequency Acoustic Interferometry (SFAI) was performed at the end of the curing process to measure the sound speed, enabling the calculation of the bulk moduli of the gelatin samples. The combined use of ultrasonic and FTIR testing provides a non-destructive method for characterizing gelatin and other biomaterials. This approach advances understanding of gelatin curing behavior and supports the development of safer biomaterials with tailored mechanical properties for various applications such as tissue engineering and regenerative medicine.

Biomaterials↗
DOE OSTI2025

Nonideal stability analysis of differentially rotating plasmas with global curvature effects

The linear stability of global nonaxisymmetric modes in differentially rotating, magnetized, nonideal plasma is critical to classifying turbulence and transport phenomena. We investigate the competition between the local magneto-rotational instability (MRI) and the magneto-curvature instability (MCI)—a distinct nonaxisymmetric low-frequency curvature-driven global branch that appears alongside MRI. Here, to accomplish this, we developed a nonideal global spectral method, which is validated against NIMROD code simulations. This spectral approach allows for the direct derivation of an extended effective potential formalism and a resistive Alfvénic resonance condition, providing a framework for direct analysis of energy contributions and confinement mechanisms. Our study reveals that the global, low-frequency MCI persists at low magnetic Reynolds numbers (Rm), whereas the localized, high-frequency MRI is stabilized by diffusive broadening of its structure around its Alfvénic resonances. Consequently, we identify the global MCI branch as the primary onset mechanism for nonaxisymmetric magnetohydrodynamic instability in systems with finite curvature, e.g., astrophysical rotators. We establish distinct parameter regimes for mode dominance: MCI prevails in geometrically moderate-thickness disks with intermediate curvature and radial gaps, while MRI dominates in thin, low-curvature disks with large radial gaps. Mode competition is also highly sensitive to the flow profile, particularly vorticity and its gradient, with nonuniform shear profiles exhibiting more robust instability due to flow curvature (i.e., the second derivative of the flow profile) and shear contributions. A key outcome is the development of spectral diagrams derived from the global spectral method. These diagrams comprehensively map dominant instabilities and their characteristics, offering a predictive tool for critical onset parameters (i.e., flow curvature, magnetic field, and Rm) and facilitating the interpretation of experimental and simulation results. Notably, these diagrams demonstrate that the global MCI is generally the sole unstable mode at the initial onset of nonaxisymmetric instability.

Haywood, Alexander [Princeton Univ., NJ (United St↗
DOE OSTI2025

Environmental life cycle of fentanyl: From the cradle to an unknown grave

The lack of available information on the presence and persistence of fentanyl in the environment is a significant gap in the technical literature. Although the origins of the opioid in the environment are well-known because they follow the same pathways of other drug-related environmental contaminants, the downstream effects of fentanyl in the water supply and its retention in soil are less understood. The characterization of fentanyl and its potential degradation products in complex environmental samples such as soil is severely understudied. Very few articles are available that work to identify fentanyl and its degradation products in complex samples or name the possible hazards that may result from environmental exposure and degradation. Therefore, the objectives were to identify available articles focused on environmental fentanyl and its pathways and highlight quantifiable research or results that included specific degradation products or downstream effects. Research articles focused on fentanyl between 2000 and 2024 were identified and reviewed and then filtered using Boolean search terms for environmental parameters. Various studies have determined that trace levels of fentanyl can be found in a variety of environments, and additional data suggest preferential partitioning into soils from water and long-term persistence. Despite this knowledge, very little data exists on the long-term downstream effects of fentanyl or its analogs. As the chronic effects from low-level fentanyl exposure are currently unknown, this lack of insight brings to the forefront the need for further research to improve our understanding of fentanyl persistence, degradation, and toxicity within the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Will Nontoxic High‐Performance Perovskite Photovoltaics Ever Be Possible?

Lead-based halide perovskite solar cells represent a significant advancement in photovoltaic technology, achieving certified power conversion efficiencies of over 27%. However, the toxicity of lead poses a major barrier to widespread commercialization. The demand for environmentally safe alternatives has driven extensive research into Pb-free perovskites. Current efforts include replacing Pb with Sn or Ge; forming double perovskites in which Pb is substituted by a monovalent–trivalent cation pair; and developing chalcogenide perovskites where the B site (ABX 3 ) adopts tetravalent cations (rather than Pb) to balance the charge. This concept examines the recent progress in developing Pb-free alternatives, revealing fundamental performance bottlenecks, inherent material limitations, and persistent development challenges. Through a comparative assessment of material properties and device performance limitations, this work highlights the underlying dilemma between environmental safety and efficiency in perovskite photovoltaics. The analysis identifies fundamental material constraints that create substantial barriers to simultaneously achieving both objectives.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A global soil plasmidome resource unveils functional and ecological roles of plasmids in soil microbiomes

Plasmids play significant roles in microbial adaptation to ecosystems, yet their dynamics remain poorly understood due to identification challenges. We present the Global Soil Plasmidome Resource (GSPR), a comprehensive dataset of 98,728 plasmid sequences amassed from 6860 terrestrial microbial communities and isolates. We explore this resource through various computational approaches, including phylogenetic diversity analysis, host prediction, and extensive functional annotation, to understand the contribution of plasmids to the genetic and functional diversity in soil, correlating these findings with sample type, as well as the soil habitat they were retrieved from. Our analysis reveals insights into plasmid-encoded functions such as effector modules, quorum sensing, and stress resistance, which may contribute to their persistence and microbial adaptation in soil. Furthermore, CRISPR analysis suggests a prevalent role of these elements related to intra-plasmid competition. By contrasting plasmids from cultivated and uncultivated organisms, we identify important functions that expand existing knowledge of plasmid roles in these habitats. This study represents a notable step forward in elucidating plasmid diversity and function within soil microbiomes and establishes a foundational framework for exploring their roles in natural environments.

Fiamenghi, Mateus B↗
DOE OSTI2024

Lipid droplet-associated proteins in alcohol-associated fatty liver disease: A proteomic approach

The earliest manifestation of alcohol-associated liver disease (ALD) is steatosis characterized by deposition of fat in specialized organelles called lipid droplets (LDs). While alcohol administration causes a rise in LD numbers in the hepatocytes, little is known regarding their characteristics that allow their accumulation and size to increase. The aim of the present study is to gain insights into underlying pathophysiological mechanisms by investigating the ethanol-induced changes in hepatic LD proteome as a function of LD size. Adult male Wistar rats (180–200 g BW) were fed with ethanol liquid diet for 6 weeks. At sacrifice, large-, medium-, and small-sized hepatic LD subpopulations (LD1, LD2, and LD3, respectively) were isolated and subjected to morphological and proteomic analyses. Morphological analysis of LD1-LD3 fractions of ethanol-fed rats clearly demonstrated that LD1 contained larger LDs compared with LD2 and LD3 fractions. Our preliminary results from principal component analysis showed that the proteome of different-sized hepatic LD fractions was distinctly different. Proteomic data analysis identified over 2000 proteins in each LD fraction with significant alterations in protein abundance among the three LD fractions. Among the altered proteins, several were related to fat metabolism, including synthesis, incorporation of fatty acid, and lipolysis. Ingenuity pathway analysis revealed increased fatty acid synthesis, fatty acid incorporation, LD fusion, and reduced lipolysis in LD1 compared to LD3. Overall, the proteomic findings indicate that the increased level of protein that facilitates fusion of LDs combined with an increased association of negative regulators of lipolysis dictates the generation of large-sized LDs during the development of alcohol-associated hepatic steatosis. Several significantly altered proteins were identified in different-sized LDs isolated from livers of ethanol-fed rats. Ethanol-induced increases in specific proteins that hinder LD lipid metabolism led to the accumulation and persistence of large-sized LDs in the liver.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

54 ENVIRONMENTAL SCIENCES↗