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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Characterization of Flashback and Flame-Holding in a Jet-in-Crossflow Mixing Configuration With Methane–Hydrogen Fuel Blends

An approach that combines experimental and numerical analyses has been implemented to characterize the fundamentals of flashback events and flame-holding phenomena during high-hydrogen combustion in a jet-in-crossflow (JICF) configuration. Such flame dynamics are visualized experimentally using nanosecond (ns)-based hydroxyl planar laser-induced fluorescence (OH-PLIF) and chemiluminescence diagnostics techniques. The JICF burner has an optically accessible premixing tube allowing the optical diagnostics. The testing was conducted for varied premixer velocities (V) and equivalence ratio (ϕ) for 90–100% (H 2 , by mole) H 2 /CH 4 reactant mixtures at atmospheric temperature and pressure conditions. Two distinct flashback events were identified – conventional rich flashback and lean flashback, recorded while increasing ϕ and decreasing ϕ, respectively. The cause of lean flashback was attributed to lower momentum flux ratio which bends the jet sharply, closer toward the injection plane. The mean OH-PLIF images characterized the flame-holding behavior, where the flame was found to be stabilized on the leeward side only or on both windward and leeward sides as a lifted flame near the fuel port. A large eddy simulation (LES) with detailed chemistry combustion modeling approach was implemented along with an OH* submechanism, and it showed qualitative agreement with the integrated line-of-sight chemiluminescence results as well as the planar OH-PLIF measurements.

chemiluminescence diagnostic↗
DOE OSTI2026

Quantifying Energy Storage Density Utilization Trends in Redox Flow Battery Chemistries

The transition to new energy resources is driving the need for efficient energy storage. Redox flow batteries (RFBs) are a promising solution due to their flexible design and safer materials, particularly for long-duration storage applications. Despite these advantages, RFB technologies still have considerable room for growth in terms of utilizing all of their available energy storage density. Herein, we assess RFB energy storage density utilization trends for multiple chemistries by accounting for their unique thermodynamic limits, energy efficiencies, and charge capacity constraints. Of the RFBs chemistries analyzed, most still use less than 60% of their theoretical energy storage capacity. The conventional all-vanadium RFB was the closest to its thermodynamic limit available. Moreover, the volumetric footprint and electrolyte cost analyses demonstrate the real-world implications of these inefficiencies. This analysis further indicates that future studies would benefit from clearer reporting of two key quantities: discharge efficiency, which is more directly tied to practically recoverable energy density than round-trip energy efficiency, and state-of-charge or capacity-utilization limits, which govern access to theoretical storage capacity. More consistent reporting of these factors would improve the accuracy and comparability of energy storage utilization analyses across RFB chemistries.

battery energy storage↗
DOE OSTI2025

CALPHAD-based Bayesian optimization to accelerate alloy discovery for high-temperature applications

Two crucial properties influencing the performance of high-temperature alloys are coefficient of thermal expansion (CTE) and phase constitution. It is desirable to have alloys with low CTE, which reduces CTE mismatch with the surface oxide and the likelihood of oxide spallation. Reducing the amount of brittle intermetallic phases such as Sigma (σ) enhances alloy ductility and processability. Here, we propose a multi-objective Bayesian Optimization (BO) model to simultaneously minimize CTE (at an operational temperature of 1150 °C) and T σ (temperature when the Sigma phase completely dissolves in the metal matrix), properties which are obtained from high-throughput CALculation of PHAse Diagrams (CALPHAD). The model successfully identifies several alloys with CTE ≤ 2 × 10 –5 /K and T σ ≤ 500 °C by exploring just 7% of the nickel–chromium–cobalt–aluminum–iron (Ni–Cr–Co–Al–Fe) composition space. Such multi-objective alloy design frameworks can be used to inform additive manufacturing experiments and accelerate alloy discovery for high-temperature energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Geochemical Impact of Acid Spearhead and Slickwater Stimulation on Wolfcamp Shale from the Hydraulic Fracturing Test Site

The Hydraulic Fracturing Test Site 1 (HFTS-1) was a field study performed in the Wolfcamp Formation in the West Texas Permian (Midland) Basin, USA, with a focus on improving the efficiency of hydraulic fracturing. Investigating site-specific rock-fluid geochemical interactions during hydraulic fracturing is an important step to understanding the impact on formation shale porosity, permeability, and long-term shale gas production. During field operations in this region, hydraulic fracturing fluid (HFF) injection usually starts with a concentrated acid spearhead for rapid rock dissolution, followed by the injection of near-neutral pH slickwater containing chemicals and proppants. A multistep sequential injection approach was used to investigate different stages of rock-fluid interactions. The carbonate content in the host rock is important when acid spearhead is considered, as carbonate mineral dissolution is rapid and can result in porosity and permeability changes in the shale matrix. Here, in this study, we designed flow-through experiments using fractured carbonate-rich and clay-rich Wolfcamp shale cores with (1) a short-time acid soaking step and (2) a long-term slickwater flow-through step to simulate the injection method used at HFTS-1. The fluid chemistry was analyzed. A thorough mineralogical progression [e.g., Calcium (Ca) dissolution and iron (Fe) redox progression] in the cores during HFF injection was also characterized and imaged by synchrotron microprobe. Reactive transport modeling was performed based on the experimental setup. The results showed that the acid spearhead is a crucial step in creating a reaction front by mineral dissolution, especially in carbonate-rich shales. A slight layer of ferrihydrite precipitated during the slickwater flow-through period. This study provides insights into potential geochemical impact due to hydraulic fracturing operations in the Permian Basin.

clastic rock↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coarse Graining Discrete Element Method Information in Particle-in-Cell Length Scales Using a Machine Learning Approach

This report details the development of a machine learning (ML)-driven framework to coarse-grain inter-particle collision dynamics from high-fidelity Discrete Element Method (DEM) simulations to Particle-in-Cell (PIC) scales for gas-solid systems. Traditional PIC models, while computationally efficient, rely on empirical granular stress formulations that fail to capture the full complexity of collision physics, particularly the heterogeneity in particle dynamics. This study adopts a bottom-up approach, integrating insights from DEM simulations to improve the physical fidelity and interpretability of PIC-scale models.

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

Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry (Final Technical Report)

Researchers at West Virginia University completed a multi-year project under DE-FE0031865 entitled “Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry”. An assessment of natural gas production site emission sources was completed to quantify the potential for emissions reductions and reductions in fuel consumption. The main sources of fugitive methane emissions at gas productions sites include condensate tanks, produced water tanks, gas compressor packing vents, pneumatic controller vents, and natural gas engine crankcase vents.

03 NATURAL GAS↗
DOE OSTI2025

NETL Energy Related Diagrams 2024 Edition [Slides]

This illustrative report uses Sankey type diagrams to illustrates energy use and CO 2 generation within the U.S. for the year 2024. The diagrams show primary energy consumption from coal, natural gas, nuclear, petroleum, and renewables for the electric, residential, commercial, industrial, and transportation sectors; fossil fuel trade/domestic production; and CO 2 generation by fuel and end use.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Environmentally Friendly Use of Carbon Ore for Advanced Building Materials for Homes and Commercial Buildings

Through this effort, X-MAT CCC sought to confirm the utility and commercialization potential of carbon-derived building materials (CDBM) technology licensed from our partner, Semplastics. These CDBM products contain at least 52% coal-derived carbon by mass. Including the binders within the resin, the products contain at least 71% carbon by mass overall, meeting a key criterion for DE-FOA-0002185 – Area of Interest (AOI) 5 – Design Research and Development, Validation, and Fabrication of a Prototype Carbon-Based Building. The Phase II project has resulted in a technology demonstrator prototype structure, a detailed design for a carbon-based building, and updated techno-economic analysis (TEA) including detailed market surveys to show the commercial viability of CDBM products. We pursued the following objectives in Phase II: (1) construction of a partial building shell as a technology demonstrator, (2) testing of CDBM products, individually and in assemblies, (3) demonstration of bonding of CDBM and traditional building materials (TBM) in structural applications, (4) production of a detailed design for a carbon-based building, and (5) an update of the TEA that was performed in Phase I. In Phase II, X-MAT CCC and our industry team performed the development and testing needed to improve the maturity of the technology from a Technology Readiness Level (TRL) of 5 to TRL 6. CDBM have been shown by our partner Semplastics to exhibit a number of high-performance characteristics, including high strength (five times the flexure strength of the best commercial brick, and more than twice the compressive strength of construction-grade concrete block), lower density, improved mechanical durability and abrasion resistance, very high temperature stability, and resistance to chemicals, acids, salts, and water. These properties offer significant improvements over conventional building materials. Phase II built upon the work accomplished in Phase I by performing technical and economic research and development to confirm the viability of CDBM as commercial products in various markets. Acknowledgment: This material is based upon work supported by the Department of Energy under Award Number DE-FE0031985.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Additively Manufactured Graded Composite Transition Joints for Dissimilar Metal Weldments in Advanced Ultra-Supercritical Power Plant (Final Technical Report)

In this project, we successfully achieved all the goals we proposed: ① Code Development; ② Transition Joint Design; ③ Lab-scale GCTJ Testing Piece Development; ④ Heat Treatment; ⑤ Welding of DMW; ⑥ Mechanical Characterization; ⑦ Corrosion; ⑧ Fabrication of Prototype GCTJ; ⑨In-field Test in SWRI and ⑩Tech-economic Analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Flame Characterization and Flashback Studies of Hydrogen-Enriched Low-Swirl Flames Using High-Speed OH-PLIF

Here, this paper reports the flashback mechanism observed in hydrogen-enriched flames stabilized in a low-swirl burner (LSB) at atmospheric temperature and pressure. The fundamentals of hydrogen-rich stable flames and spatiotemporal information of flashback phenomena were observed experimentally using a high-repetition-rate nanosecond (ns)-duration hydroxyl planar laser-induced fluorescence (OH-PLIF) diagnostic. Testing was conducted for methane and hydrogen (50–90%H 2 , by mole) blends in an optically accessible LSB premixer with measured swirl numbers varying from 0.43 to 0.49. The flashback propensity showed dependence on liftoff length, which was dependent on premixer velocity (𝑉), hydrogen content (𝑋 H 2 ), and equivalence ratio (𝜙) at constant temperature and pressure. High-speed OH-PLIF images revealed that lifted flames were first observed at low 𝜙/𝑋 H 2 conditions, which were changed to an M-shaped flame attached to the burner rim with an increase in 𝜙/𝑋 H 2 . A further increase in 𝜙/𝑋 H 2 triggered the flame flashback into the premixer. Flame 𝜙 at flashback (𝜙 FB ) showed an expected linearly increasing trend with increasing 𝑉 and decreasing 𝑋 H 2 , and the conclusions drawn aligned well with detailed liftoff length investigations. The 𝜙 FB increased with increasing perforated plate hole diameter and increasing swirler vane angle. The vane angle had little effect on flashback tendency at high premixer velocity.

combustion↗
DOE OSTI2025

Outflow Boundary Conditions for Turbine-Integrated Rotating Detonation Combustors

This study examines outflow boundary conditions (BCs) in computational fluid dynamics (CFD) simulations of a transition duct with and without guide vanes that converts supersonic flow exiting a rotating detonation combustor (RDC) to subsonic flow to drive a turbine. Since the flow exiting the transition duct has swirling shock waves with significant spatial and temporal variations in pressure, temperature, and Mach number, imposing proper BCs poses a challenge. To ensure all swirling shock waves exit the transition duct without creating non-physical reflected waves at its outlet, this study examined three outflow BCs: (1) the average pressure imposed at the duct’s outlet, (2) a nonreflecting BC (NRBC) with a specified average pressure imposed at the duct’s outlet, (3) the average pressure imposed at the outlet of an extension duct made up of a buffer layer and a sponge layer. This study is based on the three-dimensional, unsteady density-weighted-ensemble-averaged continuity, Navier–Stokes, and energy equations for a thermally perfect gas closed by the realizable k–ε model and “enhanced” wall functions. The results obtained show that imposing an average pressure at the transition duct’s outlet produces spurious waves that degrade the physical meaningfulness of the solution. When the NRBC was applied, swirling shock waves exited the duct’s outlet without creating spurious waves. However, its usage requires the gas to be thermally, as well as calorically, perfect, which this study shows could be a concern. By imposing the average pressure at the outlet of an extension duct, the gas does not need to be calorically perfect. The results obtained show the effects of the sponge layer’s length and coarsening ratio on damping nonuniformities in non-physical reflected waves to ensure the flow exiting the transition duct’s outlet can do so as if there are no boundaries present and has the desired average pressure—even though the BC is applied at the extension duct’s outlet.

gas turbines↗
DOE OSTI2025

Wireless Patch Antenna Characterization for Live Health Monitoring Using Machine Learning

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 $\frac{𝑀𝐻𝑧}{°C}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Movement Models to Predict Low‐Altitude Flight of Soaring Birds Using Look‐Ahead Environmental Factors

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤ 200 m above ground level), which puts them at risk of collision with wind turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles (Aquila chrysaetos) as a function of ecological covariates at the current location as well as those within an eagle's line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of change of heading and the orographic updraft conditions within an eagle's line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

17 WIND ENERGY↗
DOE OSTI2024

Anthromes and forest carbon responses to global change

Human effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling. Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900-present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO 2 and temperature change for different anthromes among regions. Modeled global forest carbon stock responses are positive for CO 2 increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO 2 and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests. The net effect of anthropogenic activities—including land-use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands.

54 ENVIRONMENTAL SCIENCES↗