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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis

Extreme weather accounts for over 8 0 % of major U.S. power outages since 2000, highlighting the need for spatial tools that align weather data with the irregular boundaries of electric infrastructure. This paper introduces HexWeather, a modular, resolution-aware framework for aggregating historical and forecasted weather data using Uber's H3 hexagonal spatial indexing system. Unlike traditional methods that rely on state or county-level grids, HexWeather enables weather analysis across custom geographies such as utility service areas where public datasets are often unavailable or misaligned. Using Open-Meteo data, we evaluate how H3 resolution affects anomaly detection, spatial variability, and forecast uncertainty across three scales: state, county, and utility. Results show that while coarse resolutions suffice for broad trend tracking, finer resolutions are essential for identifying localized variability and operational risks. By applying metrics like Z-score standard deviation and interquartile range, HexWeather quantifies the spatial spread of both historical anomalies and forecasted conditions, allowing users to assess resolution adequacy for each analysis. This framework supports rapid weather data reuse, reproducible anomaly detection, and predictive modeling for infrastructure resilience. By bridging spatial misalignment in traditional datasets and enabling retrospective and forward-looking analysis within the same pipeline, HexWeather lays the groundwork for better post event analysis, outage prediction, and resilience planning.

Morris, Jacob [ORNL]↗
DOE OSTI2025

Quantifying Moisture Sources of Arctic Atmospheric Rivers During the Recent Historical Period

Atmospheric rivers (ARs), filaments of intense atmospheric moisture transport, play a significant role in delivering moisture poleward into the Arctic and triggering weather extremes. Although previous studies have focused on large‐scale circulations driving these events, this study investigates ARs through attributing their moisture sources using the Community Atmosphere Model version 5 (CAM5) with moisture‐tagging capability. Examining ARs in the Atlantic and Pacific sectors of the Arctic separately revealed distinct contributions from remote versus local, and ocean versus land, moisture sources. Unlike non‐AR events, Arctic ARs primarily draw moisture from their respective ocean basins in lower‐latitude regions during the cold season, and shift to land sources in the warm season. Cold‐season ARs in the Atlantic and Pacific sectors source 73.2% and 85.3% of their moisture from their respective ocean basins at lower latitudes, however warm‐season contributions decrease to 41.3% and 29.4%. In contrast, mid‐ and high‐latitude continents combined contribute 40.1% and 51.3% in the warm season. Trajectory clustering analysis shows that AR moisture sources depend on both their genesis regions and transport pathways. In recent decades, the Arctic has experienced a moistening trend in both the cold and warm seasons. Our results suggest that local and remote sources equally drive the observed cold‐season moistening, whereas remote sources predominantly drive the warm‐season moistening. A better understanding of Arctic AR moisture sources under current climate conditions provides valuable insights into their potential future changes amid the projected heterogeneous northern hemispheric warming.

Arctic↗
DOE OSTI2021

Public data from three US states provide new insights into well integrity

Significance There are over 900,000 active oil and gas wells in the United States. Estimates of the percentage of these wells that leak during their lifetime have been limited by data availability. We mined publicly available records from state regulatory databases and synthesized the results of various well testing methods into a uniform dataset that describes the integrity of 105,031 wells. Our analysis of the dataset provides insight into regional well leakage frequencies in three US states (Colorado, New Mexico, and Pennsylvania), spatial and temporal leakage trends among vertical and directional wells, and the characteristics of leaked fluids. Our findings demonstrate the value of statewide well testing programs and highlight the challenges of interpreting disparate interjurisdictional well testing data.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

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

Investigation of Anchor Link Magnetohydrodynamic Effects in the Toroidally Symmetric Lead-Lithium (TSLL) Blanket Concept

This paper presents a comprehensive study on the magnetohydrodynamic (MHD) flow in a slotted channel with a cylindrical anchor link, which is an imperative component of the toroidally symmetric lead-lithium (TSLL) blanket concept. Following the validation of the MHD solver implemented in COMSOL and a proposed subtraction approach to compute the anchor link pressure drop, the effects of computational domain size on the pressure drop and velocity distribution are examined. The results show that the pressure drop associated with the anchor link and the maximum flow velocity follow an asymptotic trend as the domain width increases, with wall-induced pressure drop being more dominant than that of the anchor link. The velocity distribution analysis revealed the formation of an internal boundary layer extending along the magnetic field direction, which is a unique feature of the investigated MHD flow. An estimation of the total MHD pressure drop associated with the array of anchor links under the TSLL blanket conditions suggests ~0.3 MPa, which is significantly lower than the recommended maximum allowable blanket pressure drop of 2 MPa. In conclusion, this work offers valuable insights into the anchor link–associated MHD phenomena and serves as a foundation for further development of the TSLL blanket concept for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Influence of triangularity on the plasma response to resonant magnetic perturbations

The effect of the axisymmetric plasma shape on the non-axisymmetric plasma response to resonant magnetic perturbations is investigated in experiment and modeling for the DIII-D, EAST and ASDEX Upgrade tokamaks. Systematically modeling the effect of the triangularity, whilst keeping other equilibrium quantities largely unchanged, reveals that the plasma response is strongly suppressed at high triangularity compared to that at low triangularity. This is validated through targeted comparison with experiments at DIII-D, EAST, and ASDEX Upgrade. DIII-D and EAST magnetic measurements are used to validate simulations, while at ASDEX Upgrade the plasma edge displacement is measured. Both experiments and modeling find a reduced magnetic plasma response on the high-field side at high triangularity across devices. Multi-modal analysis of the simulation results extracts the mode structure and applied spectrum dependence of each mode. The amplitude of the dominant mode reveals similar trends with the edge resonance and radial displacement near the X-point, which suggests that the multi-mode plasma response provides another way to understand the edge localized mode (ELM) control physics. The plasma response is strongly reduced at high triangularity compared to that at low triangularity, which implies different ELM control effects as shaping is varied. Furthermore, these findings indicate that the plasma shape should be taken into consideration when designing an RMP-ELM control strategy in experiment, and that predictive plasma response calculations can be used to maximize access to RMP-ELM control in future devices by maximizing the coupling between coils and the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Anthropogenic aerosols prolong fog lifetime in China

Investigation of aerosol effects on fog with long-term measurements has generally focused on fog occurrence frequency and intensity; here we examine the effects on fog lifetime, fog formation, and fog dissipation. From analysis of 52 years (1960–2011) of data collected at 404 stations in China, it is found that fog lifetime exhibits a clear increasing trend with time, and the increased lifetime is mainly attributable to delayed fog dissipation. Increased aerosol levels and global warming affect fog lifetime in opposite ways; increased aerosol levels serve to prolong fog lifetime by primarily delaying fog dissipation, whereas warming decreases fog lifetime by primarily delaying fog formation. The overall aerosol effect on fog lifetime in China is shown to predominate, especially in the highly polluted region of Eastern China. The observational findings are confirmed by a suite of WRF-Chem simulations that reveal the influences of both increased aerosol levels and temperatures through a complex chain of interactions among microphysical, dynamical, thermodynamic, and radiative processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview, and Real-World Smart Grid Applications

Novel concepts enabling a resilient future power system and their subsequent experimental evaluation are experiencing a steadily growing challenge: large scale complexity and questionable scalability. The requirements on a research infrastructure (RI) to cope with the trends of such a dynamic system therefore grow in size, diversity and costs, making the feasibility of rigorous advancements questionable by a single RI. Analysis of large scale system complexity has been made possible by the real-time coupling of geographically separated RIs undertaking geographically distributed simulations (GDS), the concept of which brings the equipment, models and expertise of independent RIs, in combination, to optimally address the challenge. This article presents the outputs of IEEE PES Task Force on Interfacing Techniques for Simulation Tools towards standardization of GDS as a concept. First, the taxonomy for setups utilized for GDS is established followed by a comprehensive overview of the advancements in real-time couplings reported in literature. The overview encompasses fundamental technological design considerations for GDS. The article further presents four application oriented case studies (real-world implementations) where GDS setups have been utilized, demonstrating their practicality and potential in enabling the analysis of future complex power systems.

distributed laboratories↗
DOE OSTI2023

Using National-Scale Data to Inform Coal Power Plant Redevelopment and Coal Community Revitalization Planning

In the United States, individual coal plants have high variation in their construction and operation. Coal plants commonly have multiple units, with different commissioning ages, operational position, and maintenance conditions – even multiple fuels. These units may be in changing states of utilization, with variation in productivity depending on economic contexts. Coal plants themselves may be temporarily offline, mothballed, retired, or decommissioned due to owner/operator portfolios or market conditions, and the current posture of the plant may be difficult to ascertain without local news sources (Tarekegne et al. 2021). Anticipated dates of plant closures are prospectively represented to regulators and to the Energy Information Administration (EIA), but may also experience uncertainty due to the engineering, environmental, economic and social complexity of closing a very large power plant. As noted in this report, closure of the first unit to the last within a single plant may span more than 20 years. Yet tracking and predicting the position of our nation’s coal fleets on a national scale is deeply important. In developing a case for federal datasets and an approach to building and curating these data, this report identified that data must have high fidelity at the plant-level to be meaningful in aggregate. Plant-scale detail is also a match for its application: national priorities in federal investment range from economic revitalization for coal plant communities to maintaining reliable electric grid operations. This document is organized into a statistical review of coal plant retirements, past and prospective, in the United States; trends in the relationship between closures and existing federal investment programs for community revitalization; and potential methods for accelerating site redevelopment through advanced geospatial analysis based on federal data.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2024 Edition [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.7 million systems installed through year-end 2023, representing close to 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, roof-coverage ratios, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and customer segmentation -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive analysis and a multi-variate regression to estimate the effects of key pricing drivers for residential systems installed in 2023.

14 SOLAR ENERGY↗
DOE OSTI2022

Utility-Scale Solar, 2022 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2022 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developments in 2021, this report explores trends in deployment, technology, capital and operating costs, capacity factors, the levelized cost of solar energy (LCOE), power purchase agreement (PPA) prices, wholesale market value, and interconnection queue data.

2022↗
DOE OSTI2023

Quantifying airborne fraction trends and the destination of anthropogenic CO 2 by tracking carbon flows in a simple climate model

Abstract Atmospheric carbon dioxide (CO 2 ) concentrations have increased as a direct result of human activity and are at their highest level over the last 2 million years, with profound impacts on the Earth system. However, the magnitude and future dynamics of land and ocean carbon sinks are not well understood; therefore, the amount of anthropogenic fossil fuel emissions that remain in the atmosphere (the airborne fraction) is poorly constrained. This work aims to quantify the sources and controls of atmospheric CO 2 , the fate of anthropogenic CO 2 over time, and the likelihood of a trend in the airborne fraction. We use Hector v3.0, a coupled simple climate and carbon cycle model with the novel ability to explicitly track carbon as it flows through the Earth system. We use key model parameters in a Monte Carlo analysis of 15 000 model runs from 1750 to 2300. Results are filtered for physical realism against historical observations and CMIP6 projection data, and we calculate the relative importance of parameters controlling how much anthropogenic carbon ends up in the atmosphere. Modeled airborne fraction was roughly 52%, consistent with observational studies. The overwhelming majority of model runs exhibited a negative trend in the airborne fraction from 1960–2020, implying that current-day land and ocean sinks are proportionally taking up more carbon than the atmosphere. However, the percentage of atmospheric CO 2 derived from anthropogenic origins can be much higher because of Earth system feedbacks. We find it peaks at over 90% between 2010–2050. Moreover, when looking at the destination of anthropogenic fossil fuel emissions, only a quarter ends up in the atmosphere while more than half of emissions are taken up by the land sink on centennial timescales. This study evaluates the likelihood of airborne fraction trends and provides insights into the dynamics of anthropogenic CO 2 in the Earth system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis

The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

High Throughput Data-Driven Design of Laser-Crystallized 2D MoS 2 Chemical Sensors: A Demonstration for NO 2 Detection

High throughput characterization and processing techniques are becoming increasingly necessary to navigate multivariable, data-driven design challenges for sensors and electronic devices. For two-dimensional materials, device performance is highly dependent upon a vast array of material properties including the number of layers, lattice strain, carrier concentration, defect density, and grain structure. In this work, laser crystallization was used to locally pattern and transform hundreds of regions of amorphous MoS 2 thin films into 2D 2H-MoS 2 . Here a high throughput Raman spectroscopy approach was subsequently used to assess the process-dependent structural and compositional variations for each illuminated region, yielding over 6000 distinct nonresonant, resonant, and polarized Raman spectra. The rapid generation of a comprehensive library of structural and compositional data elucidated important trends between structure–property processing relationships involving laser-crystallized MoS 2 , including the relationships between grain size, grain orientation, and intrinsic strain. Moreover, extensive analysis of structure/property relationships allowed for intelligent design and evaluation of major contributions to device performance in MoS 2 chemical sensors. In particular, it is found that NO 2 sensor performance is strongly dependent on the orientation of the MoS 2 grains relative to the crystal plane.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Carnegie Supernova Project I: Spectroscopic analysis of stripped-envelope supernovae

An analysis leveraging 170 optical spectra of 35 stripped-envelope (SE) core-collapse supernovae (SNe) observed by the Carnegie Supernova Project I and published in a companion paper is presented. Mean template spectra were constructed for the SNe IIb, Ib, and Ic subtypes, and parent ions associated with designated spectral features are identified with the aid of the spectral synthesis code SYNAPPS. Our modeled mean spectra suggest the ~6150 Å feature in SNe IIb may have an underlying contribution due to silicon, while the same feature in some SNe Ib may have an underlying contribution due to hydrogen. Standard spectral line diagnostics consisting of pseudo-equivalent widths (pEWs) and blue-shifted Doppler velocity were measured for each of the spectral features. Correlation matrices and rolling mean values of both spectral diagnostics were constructed. A principle component analysis (PCA) was applied to various wavelength ranges of the entire dataset and suggests clear separation among the different SE SN subtypes, which follows from trends previously identified in the literature. In addition, our findings reveal the presence of two SNe IIb subtypes, a select number of SNe Ib displaying signatures of weak, high-velocity hydrogen, and a single SN Ic with evidence of weak helium features. Our PCA results can be leveraged to obtain robust subtyping of SE SNe based on a single spectrum taken during the so-called photospheric phase, separating SNe IIb from SNe Ib with ~80% completion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗
DOE OSTI2021

A Conceptual Framework for HPC Operational Data Analytics

This paper provides a broad framework for under- standing trends in Operational Data Analytics (ODA) for High- Performance Computing (HPC) facilities. The goal of ODA is to allow for the continuous monitoring, archiving, and analysis of near real-time performance data, providing immediately actionable information for multiple operational uses. In this work, we combine two models to provide a comprehensive HPC ODA framework: one is an evolutionary model of analytics capabilities that consists of four types, which are descriptive, diagnostic, predictive and prescriptive, while the other is a four- pillar model for energy-efficient HPC operations that covers facility, system hardware, system software, and applications. This new framework is then overlaid with a description of current development and production deployments of ODA within leading- edge HPC facilities. Finally, we perform a comprehensive survey of ODA works and classify them according to our framework, in order to demonstrate its effectiveness.

Netti, Alessio↗
DOE OSTI2023

Catalyst Layer Resistance and Utilization in PEM Electrolysis

Improving utilization, performance, and stability of low iridium (Ir)-loaded anodes is a key goal to enable widespread adoption of polymer electrolyte membrane water electrolysis (PEMWE) for clean hydrogen production. A potential limitation is high ionic or electronic resistance of the anode catalyst layer, which leads to poor catalyst utilization, increased voltage losses, and high local overpotentials that can accelerate degradation. While catalyst layer resistance is relatively well-understood in fuel cells and other porous electrode systems, characterization of these effects is not as well established in PEMWE research. Here we present in-situ methods for measuring catalyst layer resistance in electrolysis cells using a non-faradaic H 2 /H 2 O condition as well as methods for calculating the associated voltage losses. These methods are applied to anode catalyst layers based on IrO 2 nanoparticles as well as dispersed nano-structured thin film (NSTF) Ir catalysts. Trends with anode catalyst loading and interactions between the porous transport layer and catalyst layer are investigated for IrO 2 anodes. Post-mortem microscopic analysis of durability-tested anodes is also presented, showing uneven degradation of the catalyst layer caused by catalyst layer resistance.

08 HYDROGEN↗