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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Thermal barrier coatings

High temperature stable thermal barrier coatings useful for substrates that form component parts of engines such as a component from a gas turbine engine exposed to high temperatures are provided. The thermal barrier coatings include a multiphase composite and/or a multilayer coating comprised of two or more phases with at least one phase providing a low thermal conductivity and at least one phase providing mechanical and erosion durability. Such low thermal conductivity phase can include a rare earth zirconate and such mechanical durability phase can include a rare earth a rare earth aluminate. The different phases are thermochemically compatible even at high temperatures above about 1200° C.

Wolfe, Douglas E.↗
DOE OSTI2023

Optical tags comprising rare earth metal-organic frameworks

Optical tags provide a way to identify assets quickly and unambiguously, an application relevant to anti-counterfeiting and protection of valuable resources or information. The present invention is directed to a tag fluorophore that encodes multilayer complexity in a family of heterometallic rare-earth metal-organic frameworks (RE-MOFs) based on highly connected polynuclear clusters and carboxylic acid-based linkers. Both overt (visible) and covert (near infrared, NIR) properties with concomitant multi-emissive spectra and tunable luminescence lifetimes impart both intricacy and security. Tag authentication can be validated with a variety of orthogonal detection methodologies. The relationships between structure, composition, and optical properties of the family of RE-MOFs can be used to create a large library of rationally designed, highly complex, difficult to counterfeit optical tags.

Sava Gallis, Dorina F.↗
DOE OSTI2024

NREL Marine Energy Desalination Research and Development Portfolio: Preprint

The National Renewable Energy Laboratory (NREL), in collaboration with the U.S. Department of Energy's (DOE's) Water Power Technologies Office (WPTO), has developed a unique R&D approach to advance marine energy desalination. Desalination is a foundational investment within WPTO's Powering the Blue Economy portfolio, and was the first investment within this portfolio. NREL's marine energy desalination spans techno-economic feasibility studies, numerical modeling, and laboratory testing at the component and subsystem level, as well as development of the Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC). This multilayered approach enables an innovative feedback loop where the data and lessons learned from laboratory and field experiments are used to refine modeling tools and analysis techniques, prioritize out-year activities, and refine strategic directions within NREL and across the WPTO portfolio. The primary objective of the NREL-led research is to identify key barriers associated with the commercialization of wave-powered desalination and develop solutions that can be adopted by the marine energy industry. In parallel, these R&D activities can help inform technical assistance and support of industry and academic technologies. These two tracks help build a common solver community approach, while also identifying key stakeholders, government agencies, and other organizations outside of the marine sector that will be necessary for developing a robust industry. For the Spanish version of this report, see NREL/CP-5700-88483 (https://www.nrel.gov/docs/fy24osti/88483.pdf).

analysis↗
DOE OSTI2023

Current rectification based on noncentrosymmetric quantum materials

Rectification is a process that converts electromagnetic fields into direct current (DC). Such a process underlies a wide range of technologies, including wireless communication, wireless charging, energy harvesting, and infrared detection. Existing rectifiers are mostly based on semiconductor diodes, with limited applicability to small voltages or high frequency inputs. Here, we present an alternative approach to current rectification that uses the electronic properties of quantum crystals without semiconductor junctions. We identify a new mechanism for rectification from skew scattering due to the chirality of itinerant electrons in time-reversal-invariant but inversion-breaking materials. Our calculations reveal large, tunable rectification effects in graphene multilayers and transition metal dichalcogenides. These effects can be used in high-frequency rectifiers by rational material design and quantum wavefunction engineering.

Isobe, Hiroki↗
DOE OSTI2024

Cartera de Investigacion y Desarrollo Sobre Desalinizacion de Energia Marina del NREL: Preprint (Spanish Translation)

The National Renewable Energy Laboratory (NREL), in collaboration with the U.S. Department of Energy's (DOE's) Water Power Technologies Office (WPTO), has developed a unique R&D approach to advance marine energy desalination. Desalination is a foundational investment within WPTO's Powering the Blue EconomyTM portfolio [1], and was the first investment within this portfolio. NREL's marine energy desalination spans techno-economic feasibility studies, numerical modeling, and laboratory testing at the component and subsystem level, as well as development of the Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC). This multilayered approach enables an innovative feedback loop where the data and lessons learned from laboratory and field experiments are used to refine modeling tools and analysis techniques, prioritize out-year activities, and refine strategic directions within NREL and across the WPTO portfolio. The primary objective of the NREL-led research is to identify key barriers associated with the commercialization of wave-powered desalination and develop solutions that can be adopted by the marine energy industry. In parallel, these R&D activities can help inform technical assistance and support of industry and academic technologies. These two tracks help build a common solver community approach, while also identifying key stakeholders, government agencies, and other organizations outside of the marine sector that will be necessary for developing a robust industry. For the English version of this report, see NREL/CP-5700-86724 (https://www.nrel.gov/docs/fy24osti/86724.pdf).

analysis↗
DOE OSTI2024

NREL Marine Energy Desalination R&D Portfolio

The National Renewable Energy Laboratory (NREL), in collaboration with the U.S. Department of Energy's (DOE's) Water Power Technologies Office (WPTO), has developed a unique R&D approach to advance marine energy desalination. Desalination is a foundational investment within WPTO's Powering the Blue EconomyTM portfolio [1], and was the first investment within this portfolio. NREL's marine energy desalination spans techno-economic feasibility studies, numerical modeling, and laboratory testing at the component and subsystem level, as well as development of the Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC). This multilayered approach enables an innovative feedback loop where the data and lessons learned from laboratory and field experiments are used to refine modeling tools and analysis techniques, prioritize out-year activities, and refine strategic directions within NREL and across the WPTO portfolio. The primary objective of the NREL-led research is to identify key barriers associated with the commercialization of wave-powered desalination and develop solutions that can be adopted by the marine energy industry. It should be noted, while WPTO's marine energy portfolio includes wave, tidal, ocean current, thermal gradients, and pressure gradients the bulk of the marine energy desalination work has been focused on wave powered desalination. In parallel, these R&D activities can help inform technical assistance and support of industry and academic technologies. These two tracks help build a common solver community approach, while also identifying key stakeholders, government agencies, and other organizations outside of the marine sector that will be necessary for developing a robust industry.

desalination↗
DOE OSTI2023

ICRF wave propagation and absorption modelling via machine learning

A surrogate model of the wave absorption in the ion cyclotron range of frequencies is presented. The model is trained to capture the physics of 1D electron and ion power absorption profiles for both the high harmonic fast wave scheme in NSTX, and the minority heating scheme in WEST. The surrogate models, based on both the random forest regressor and the multilayer perceptron algorithms, reduce inference time of 1D power absorption profiles from 1-5 minutes required by TORIC to ∼50 µs with high accuracy (i.e. R2 = 0.71−0.96).

Sánchez-Villar↗
DOE OSTI2024

Group-III nitride devices and systems on IBAD-textured substrates

A multilayer structure including a hexagonal epitaxial layer, such as GaN or other group III-nitride (III-N) semiconductors, a <111>oriented textured layer, and a non-single crystal substrate, and methods for making the same. The textured layer has a crystalline alignment preferably formed by the ion-beam assisted deposition (IBAD) texturing process and can be biaxially aligned. The in-plane crystalline texture of the textured layer is sufficiently low to allow growth of high quality hexagonal material, but can still be significantly greater than the required in-plane crystalline texture of the hexagonal material. The IBAD process enables low-cost, large-area, flexible metal foil substrates to be used as potential alternatives to single-crystal sapphire and silicon for manufacture of electronic devices, enabling scaled-up roll-to-roll, sheet-to-sheet, or similar fabrication processes to be used. The user is able to choose a substrate for its mechanical and thermal properties, such as how well its coefficient of thermal expansion matches that of the hexagonal epitaxial layer, while choosing a textured layer that more closely lattice matches that layer. Electronic devices such as LEDs can be manufactured from such structures. Because the substrate can act as both a reflector and a heat sink, transfer to other substrates, and use of external reflectors and heat sinks, is not required, greatly reducing costs. Large area devices such as light emitting strips or sheets may be fabricated using this technology.

Matias, Vladimir↗
DOE OSTI2020

Automated Vehicle Detection in a Nuclear Facility Using Low-Frequency Acoustic Sensors

This article presents an analysis of the method of construction and results for a classifier intended to identify vehicles using low-frequency acoustic data collected by a dis-tributed sensor network. This data is collected as part of a venture intended to explore data analytics and multisensor fusion techniques for the monitoring of activities at a test bed nuclear facility located at Oak Ridge National Laboratory in Oak Ridge, Tennessee. We describe the associated target signature and design a classifier based on a multilayer perceptron, followed by an analysis of its results. We discuss how overall accuracy is not the only consideration in constructing this classifier, and how for this application, it is actually desirable to operate at a lower level of accuracy in exchange for a reduction in the false alarm rate, as well as how this relates to the actual deployment of the classifier in practical use.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Power System Feature-Based Event Classification by Means of Multiple PMU Data

Abstract—Phasor Measurement Units (PMUs) provide time synchronized measurements across the power grid, enabling data driven event detection and classification for enhanced system monitoring and situational awareness. However, variations in event duration, spatial extent, and severity, along with coincident events, pose challenges for conventional classification models that require fixed-size inputs. This paper presents a feature-based framework that aggregates diverse attributes from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, and Multilayer Perceptron. A probabilistic post-processing scheme is further introduced to enable multi-label classification in the presence of overlapping events. Experiments using real-world PMU data demonstrate that the Random Forest model achieves 95% accuracy, while the proposed post-processing method yields an additional 3% improvement.

Nematirad, Reza↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

This paper is the basis for a presentation help at the 2026 Georgia Tech Fault & Disturbance Analysis Conference, which can be found at OSTI # 3168287 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danovo Energy Solutions]↗
DOE OSTI2026

Concept of Dynamic Heat Insulation for Rotating Detonation Engines

This work introduces a new class of materials concept to dynamically reduce instantaneous heat fluxes in Rotating Detonation Engine (RDE) combustor chamber walls. The high-frequency and high-amplitude surface heat fluxes observed in RDEs arise from large instantaneous temperature differences between the detonation shockwave and chamber wall surface. These temperature gradients drive substantial energy loss and reduce the chamber gas pressure, ultimately limiting the cycle’s thermodynamic efficiency. This work introduces a concept for dynamically insulating the combustion chamber surfaces using surface layers or coatings with low thermal time scale. With such coatings, the surface temperature may follow the fluctuations of the cyclic detonation wave temperature, thus reducing the instantaneous heat flux therefore cycle-mean heat flux. To analyze these cyclic thermal phenomena, a one-dimensional analytical conduction solver was utilized with the capability to handle multilayered structures. Parametric modeling was performed using transient heat flux boundary conditions representative of a hydrogen–air RDE across a broad range of coating thermal properties and engine conditions. The coating effectiveness scaled with the product of thermal time constant and detonation wave frequency and the results were non-dimensionalized to guide future materials development. This strategy may offer benefits in increasing material survivability, reducing cooling requirements, and enhancing pressure gain.

heat transfer↗
DOE OSTI2025

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Distinguishing antiferromagnetic spin sublattices via the spin Seebeck effect

We measured spin Seebeck signals at the top and bottom surfaces of an antiferromagnetic Cr 2 O 3 film, using a Pt/Cr 2 O 3 /Pt trilayer. Our experimental data, combined with micromagnetic simulations, clearly demonstrate that the uncompensated sublattice at the top and bottom surfaces plays a decisive role in determining the symmetry of the spin Seebeck signals, providing fundamental insight for understanding the generation of spin Seebeck signal in antiferromagnetic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

In-Process Melt Separation of Depolymerized PET in PET/PE Blends for Upcycling via Twin-Screw Extrusion

Our previous work focused on depolymerizing polyethylene terephthalate (PET) in twin-screw extrusion, as part of a broader project to continuously separate PET from polyolefins in the melt. This study focused on linear low-density polyethylene (LLDPE) and PET films and the use of ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and bis(2-hydroxyethyl) terephthalate (BHET) to depolymerize the PET in the extruder to levels above 90% Mw. In this work, the focus will shift to achieving separation of the two polymers in the twin-screw extruder, which is made possible due to a 90% reduction in the Mw of the PET, which caused a decrease of its viscosity by several orders of magnitude. Owing to the viscosity difference and pressure buildup in the die, the low-viscosity PET preferentially exited a degassing vent instead of going through the die. This is because the flow of the PET would travel through a non-pressure vent rather than through a high-pressure die. However, owing to the higher viscosity of the LLDPE, the pressure was too high to pass through such a small diameter vent hole. Supercritical CO 2 (SCCO 2 ) was used to assist in this extraction, but SCCO 2 negatively impacted the overall degree of separation. Through analysis of the separated materials, it was concluded that a high separation of the two materials was achieved. TGA and FTIR confirmed that the material separated from the vent was 100% PET. The material removed from the die was composed of 95% LLDPE and 5% PET.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In‐Process Melt Separation of PE/PET Blends for Upcycling via Twin‐Screw Extrusion. Impact of Catalyst Reagents on PET Depolymerization

Part 1 of this work focused on depolymerizing polyethylene terephthalate (PET) in twin-screw extrusion, as part of a broader project to continuously separate PET from polyolefins in the melt. This study focused on linear low-density polyethylene (LLDPE) and PET films and the use of ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and bis(2-hydroxyethyl) terephthalate (BHET) to depolymerize the PET in the extruder to levels above 90% Mw. In part 2, the focus will shift to achieving separation of the two polymers in the twin-screw extruder, which is made possible due to a 90% reduction in the Mw of the PET, which caused a decrease of its viscosity by several orders of magnitude. Owing to the viscosity difference and pressure buildup in the die, the low-viscosity PET preferentially exited a degassing vent instead of going through the die. This is because the flow of the PET would travel through a non-pressure vent rather than through a high-pressure die. However, owing to the higher viscosity of the LLDPE, the pressure was too high to pass through such a small diameter vent hole. Supercritical CO₂ (SCCO₂) was used to assist in this extraction, but SCCO₂ negatively impacted the overall degree of separation. Through analysis of the separated materials, it was concluded that a very high separation of the two materials was achieved. TGA and FTIR confirmed that the material separated from the vent was 100% PET. The material removed from the die was composed of 90% LLDPE and 10% PET.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spectroscopic evaluation of tribologically-induced changes in surface chemistry of Zr-based bulk metallic glass

Bulk metallic glasses (BMGs) are promising structural materials owing to their high elastic limit and yield strength-to-weight ratio. While BMGs also exhibit attractive tribological properties (e.g., high wear resistance), the scientific basis for this behavior is not yet established. In particular, tribologically-induced changes in surface chemistry upon sliding are still an open topic of research. Here, we evaluated by X-ray photoelectron spectroscopy (XPS) the evolution of the surface chemistry of Vitreloy 105 (a Zr-rich BMG) upon sliding under different contact conditions against a tungsten carbide countersurface. The spectroscopic results indicate that the relative fraction of the metallic elements in the near-surface region is not affected by the sliding speed when the applied contact pressure is lower than 1.37 GPa, while a decrease in metallic zirconium was observed at lower sliding speeds and higher applied contact pressure (i.e., 1.71 GPa). Based on the spectroscopic results, a model is proposed for the effect of mechanical stress on the extent of oxidation of the near-surface region of Zr-based BMGs. In conclusion, the results of this work provide novel insights into the surface phenomena occurring on BMGs upon sliding and add significantly to our understanding of the tribological response of this class of promising structural materials.

Bulk metallic glasses↗