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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nanodiffraction imaging of ionically driven phase separation in cobaltite heterostructures

Controlling the anionic stoichiometry and distribution of perovskite cobaltites presents a powerful method for tailoring the magnetic and electronic properties for magneto-ionic applications. Nevertheless, the influence of nanoscale morphology, including phase separation and defects in cobaltite heterostructures, remains largely unexplored. We used x-ray nanodiffraction to directly image the nanoscale topotactic phase transformation in La 1−x Sr x CoO 3 (LSCO) heterostructures capped with a reactive aluminum (Al) layer (i.e., oxygen “getter”) of varying thicknesses (0.5, 3, and 7 nm). Nanodiffraction images reveal the formation of highly elongated BM filaments extending over mesoscopic lengths (>67 μm), indicating a strong tendency toward oxygen vacancy ordering in both P and BM phases in all heterostructures. Local strain and strain gradient analysis shows a strong correlation between the depletion of the P phase and strain gradients. Our measurements suggest that elongation of the BM filaments is the predominant mechanism for topotactic transformation in LSCO/Al heterostructures, preferred over coarsening, branching, and fractal growth. Our study provides a detailed nanoscale analysis of ionically driven phase transitions in LSCO/Al heterostructures, which is crucial for tailoring the functional properties of cobaltites for magneto-ionic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Broadband coplanar-waveguide-based impedance-transformed Josephson parametric amplifier

Quantum-limited Josephson parametric amplifiers play a pivotal role in advancing the field of circuit quantum electrodynamics by enabling the fast and high-fidelity measurement of weak microwave signals. Therefore, it is necessary to develop robust parametric amplifiers with low noise, broad bandwidth, and reduced design complexity for microwave detection. However, current broadband parametric amplifiers either have degraded noise performance or rely on complex designs. Here, we present a device based on the broadband impedance-transformed Josephson parametric amplifier that integrates a hornlike coplanar waveguide transmission line, which significantly decreases the design and fabrication complexity while keeping comparable performance. The device shows an instantaneous bandwidth of 700 (200) MHz for 15 (20) dB gain with an average input saturation power of − 110 dBm and near quantum-limited added noise. The operating frequency can be tuned over 1.4 GHz using an external flux bias. We further demonstrate the negligible backaction from our device on a transmon qubit. The amplification performance and simplicity of our device promise its wide adaptation in quantum metrology, quantum communication, and quantum information processing. Published by the American Physical Society 2024

Qing, Bingcheng (ORCID:0000000345227017)↗
DOE OSTI2025

Electron Beam-Induced Phase Transformations in Different Crystal Orientations of a 2D van der Waals Magnet

To control materials properties at the nanoscale, the well-focused electron beam of the scanning transmission electron microscope (STEM) can be used as a tool to engineer structure with atomic precision. For 2D magnets, especially the highly anisotropic materials AgCrP2S6 and CrSBr, we find here that the STEM serves as a powerful tool for sculpting the arrangement of atoms, with the potential to modulate local magnetic properties.

Park, Eugene [Massachusetts Inst. of Technology (M↗
DOE OSTI2024

Manuscript Workflows from and Processed Organic Matter Composition of Experimentally Burned Open Air and Muffle Furnace Vegetation Chars across Differing Burn Severity and Feedstock Types from Pacific Northwest, USA (v3)

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package.This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details.This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

State-of-Charge Investigation of Lithium Manganese Dioxide Primary Batteries Utilizing X-ray Computed Tomography

Lithium primary batteries (LPBs) represent a class of energy storage devices, uniquely suited for mission-critical applications including emergency backup power, aerospace and defense electronics, implantable medical devices, and remote sensing. Despite their technological maturity and distinct advantages over rechargeable lithium-ion batteries (i.e., superior shelf life and operational simplicity), state-of-charge (SoC) estimation in these batteries remains a persistent challenge due to the lack of a reliable, quantifiable diagnostic technique. In this work, we investigate X-ray computed tomography (X-CT) as a transformative and accurate SoC estimation technique for LPBs. Results gained through X-CT measurements reveal systematic, quantifiable structural changes in cathode morphology and geometry during discharge, establishing a direct structural basis for SoC estimation, with a maximum relative standard deviation of 2.3%. This work establishes a pathway toward operando, imaging-driven SoC diagnostics that can significantly enhance the reliability of SoC estimation in LPBs.

25 ENERGY STORAGE↗
DOE OSTI2023

A one-pot synthesis of high-density biofuels through bifunctional mesoporous zeolite-encapsulated Pd catalysts

Developing a powerful bifunctional catalyst for tandem reactions is essential to the future carbon neutrality by reducing the energy consumption in chemical industries. Herein, mesoporous zeolite-encapsulated palladium (Pd) nanoparticles (Pd@meso-ZSM-5) synthesized via emulsification-demulsification followed by a dry-gel transformation method were demonstrated to have a remarkable catalytic performance for a one-pot multiple tandem reaction of cyclic ketones (cyclopentanone, cyclohexanone) to bicyclic alkanes (bicyclopentane, bicyclohexane). Compared with supported catalysts (Pd/meso-ZSM-5) and microporous zeolite-encapsulated catalysts (Pd@ZSM-5) with a primary product of monocyclic alkane (cyclopentane, cyclohexane), Pd@meso-ZSM-5 shows much higher catalytic efficiency for the bicyclic alkanes synthesis, which was previously unattainable in the conventional two-step synthesis route. Controlled experiments and detailed characterizations show that mesoporosity provides sufficient space for the generation and diffusion of large molecular intermediates, and the intimate acid-Pd interface promotes the conversion of intermediates. As a result, this work proposes a design strategy for a mesoporous zeolite-encapsulated metal catalyst, which efficiently provides cooperative acid-hydrogenation catalysis.

09 BIOMASS FUELS↗
DOE OSTI2025

Testing strong-field QED with the avalanche precursor

A two-beam high-power laser facility is essential for the study of one of the most captivating phenomena predicted by strong-field quantum electrodynamics (QED) and yet unobserved experimentally: the avalanche-type cascade. In such a cascade, the energy of intense laser light can be efficiently transformed into high-energy radiation and electron–positron pairs. The future 50-petawatt-scale laser facility NSF OPAL will provide unique opportunities for studying such strong-field QED effects, as it is designed to deliver two ultra-intense, tightly focused laser pulses onto the interaction point. In this work, we investigate the potential of such a facility for studying elementary particle and plasma dynamics deeply in the quantum radiation-dominated (RD) regime, and the generation of QED avalanches. With three-dimensional particle-in-cell simulations, we demonstrate that QED avalanche precursors can be reliably triggered under realistic laser parameters and layout (namely, focusing f/2, tilted optical axes, and non-ideal co-pointing) with the anticipated capabilities of NSF OPAL. We demonstrate that seed electrons can be efficiently injected into the laser focus by using targets of three types: a gas of heavy atoms, an overcritical plasma, and a thin foil. A strong positron and high-energy photon signal is generated in all cases. The cascade properties can be identified from the final particle distributions, which have a clear directional pattern. At increasing laser field intensity, such distributions provide signatures of the transition, first, to the RD interaction regime, and then to a QED avalanche. Our findings can also be used for designing related future experiments.

Lasers↗
DOE OSTI2025

Modeling of the high column density systems in the Lyman-Alpha forest

The Lyman-α forests observed in the spectra of high-redshift quasars can be used as a tracer of the cosmological matter density to study baryon acoustic oscillations (BAO) and the Alcock-Paczynski effect. Extraction of cosmological information from these studies requires modeling of the forest correlations. While the models depend most importantly on the bias parameters of the intergalactic medium (IGM), they also depend on the numbers and characteristics of high-column-density systems (HCDs) ranging from Lyman-limit systems with column densities log N HI /1cm -2 > 17 to damped Lyman-α systems (DLAs) with log N HI /1cm -2 > 20.2. These HCDs introduce broad damped absorption characteristic of a Voigt profile. Consequently they imprint a component on the power spectrum whose modes in the radial direction are suppressed, leading to a scale-dependent bias. Using mock data sets of known HCD content, we test a model that describes this effect in terms of the distribution of column densities of HCDs, the Fourier transforms of their Voigt profiles and the bias of the halos containing the HCDs. Our results show that this physically well-motivated model describes the effects of HCDs with an accuracy comparable to that of the ad-hoc models used in published forest analyses. We also discuss the problems of applying the model to real data, where the HCD content and their bias is uncertain.

Lyman alpha forest↗
DOE OSTI2023

Surface Merging Technique to Design GA-Optimized Heat Sinks

High-power density inverters require efficient and small heat dissipation systems. For liquid cooling systems, an effective heat sink design is important to enable higher heat transfer and keep the pressure drop within reasonable limits. A heat sink geometry generated from an extruded, 1D fast Fourier transform can achieve more even temperature distribution and improved heat transfer than a conventional heat sink. Building on this concept, this paper proposes a new heat sink geometry creation algorithm. Instead of one plane profile being extruded, multiple plane profiles, each created from the fast Fourier transform method, are subsequently merged by smooth surfaces along the flow direction of the heat sink. Thus, a 3D heat sink geometry is created that enables 3D coolant flow and efficient heat transfer. The volume of this design was reduced by 50% compared with pin fin heat sinks. Compared with extruded 1D fast Fourier transform heat sinks, the proposed design showed an approximately 5% device temperature reduction and a 20% pressure drop reduction.

Barua, Himel↗
DOE OSTI2023

Validation of Robustness in TCR Design Strategies

Advanced Manufacturing (AM) has been identified as one of key pathways in accelerating deployment of next generation of nuclear power plants. The nuclear industry continues to predominately rely on fabrication techniques and materials that their codes and standards were approved decades ago. This legacy approach in the highly regulated nuclear sector has brought uncertainty to commercial viability of nuclear energy in the U.S. The Transformational Challenge Reactor (TCR), sought to utilize AM methods for fabrication of a High Temperature Gas Reactor (HTGR). The program sought to leverage AM to construct a non-conventional geometry made up of TRISO fuel and hydride moderator in SiC matrix. This project objective was to provide independent analysis of the core configuration with separate set of tools and approaches than utilized by the TCR team in a 2-year time frame. This NEUP project also tackled a question: Can AM be a cost-effective tool in changing the commercial paradigm of nuclear. We investigated this question in-context of a micro HTGR. While respecting the inherit uncertainty in our input parameters, overall we saw that AM has potential in improving economic competitiveness of nuclear energy when employed on multiple fronts (i.e. few percentage cost improvement per component). Given realizing AM requires mass orders and large R&D investment for commercial utilization, Department of Energy should focus its support on few key enabling technologies and support their codes and standards development and qualification cost (including irradiation as applicable) rather than taking a diluted approach.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Abstract for CRADA between NETL and Rivalia Chemical Co

The National Energy Technology Laboratory (NETL) will assist Rivalia Chemical Co (Participant) with system analyses to aid the Participant with setting priorities and securing funding. The Participant is an early-stage startup pioneering new chemical extraction technology to solve two important problems: critical mineral scarcity and coal ash waste management. The U.S. generates coal fly ash from coal combustion for power generation and has amassed over two billion metric tons of ash, which contains valuable rare earth elements. The ash is often stored in unlined ponds and frequently contaminates the local environment. The Participant’s patent-pending process harvests rare earths from ash, then transforms the residual ash for use in green concrete, providing an economic pathway for utilities to empty and remediate the ash ponds. Founder Laura Stoy created the company in July 2022 after developing the core intellectual property during her Ph.D. at the Georgia Institute of Technology. Stoy is currently participating in the Chain Reactions Innovations (CRI) program at the U.S. Department of Energy (DOE) Argonne National Laboratory (ANL) where she will be optimizing the core technology and scaling from bench scale to demonstration scale. The technology has been validated at bench scale (TRL3); the goal is to approach TRL5 by the conclusion of the CRI program and prepare to raise capital investment for a pilot facility. NETL and the Participant will develop an updated technoeconomic analysis (TEA) and identify key sustainability performance parameters to inform ’s research and development priorities and de-risk the technology. NETL will also provide the Participant with guidance to prepare a more detailed life cycle assessment (LCA), and a narrative on the Participant’s product markets. These tools will aid the Participant with the next steps of commercialization.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Instantaneous ultra-wideband sensing using frequency-domain channelization

A radar system wherein a radar return is channelized by frequency into a plurality of channels, and each of the channels is sampled by a respective analog-to-digital converter that has a sampling rate less than the Nyquist rate of the radar return. The digitally sampled channel signals are Fourier transformed into the frequency domain, where each of the frequency-domain channel signals is matched-filtered according to a respective partial matched filter. The channel signals are then transformed back to the time domain, whereupon they are added together to generate the impulse response of the radar system responsive to the radar return.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distributed and Secure Spectrum Sharing for 5G and 6G Networks

Secure spectrum sharing or spectrum co-existence of multiple 5G networks and future 6G networks is a powerful enabler technology. The National Spectrum Strategy (NSS) published by the White House in November, 2023, and the subsequent NSS implementation plan led by the National Telecommunication and Information Administration (NTIA) is the driver of a national effort to enable co-existence of government incumbents and commercial networks in selected spectrum bands. Cellular networks such as 5G & 6G and non-cellular Wi-Fi 6E & 7 are the prominent wireless technologies considered for co-existence with incumbent wireless links. Security of the spectrum sharing solutions is a must to make this transformation of spectrum use possible, specially for mission critical communications. However, current spectrum sharing solutions rely on centralized data bases with inherent vulnerabilities. This paper focuses on secure spectrum sharing among multiple 5G networks using unlicensed and shared frequency bands. It presents an innovative AI/ML based distributed spectrum sharing approach that can be autonomously used by multiple networks. Each sharing network uses its own observation of the Radio Frequency (RF) environment, which consists of RF measurements reported from the 5G User Equipment (UE), to adjust the transmission power levels for secure co-existence. Data is presented to illustrate the superior performance of this solution compared to other spectrum sharing solutions where each network can utilize usage data of the other networks. Finally it discusses how this efficient spectrum sharing solution can evolve in the future for the 6G networks.

5G↗
DOE OSTI2023

A Generalized Approach to Photon Avalanche Upconversion in Luminescent Nanocrystals

Photon avalanching nanoparticles (ANPs) exhibit extremely nonlinear upconverted emission valuable for subdiffraction imaging, nanoscale sensing, and optical computing. Avalanching has been demonstrated with Tm 3+ -, Pr 3+ -, or Nd 3+ -doped nanocrystals, but their emission is limited to a few wavelengths and materials. Here, we utilize Gd 3+ -assisted energy migration to tune the emission wavelengths of Tm 3+ -sensitized ANPs and generate highly nonlinear emission from Eu 3+ , Tb 3+ , Ho 3+ , and Er 3+ ions. The upconversion intensities of these spectrally discrete ANPs scale with nonlinearity factor s = 10-17 under 1064 nm excitation at power densities as low as 7 kW cm -2 . This strategy for imprinting avalanche behavior on remote emitters can be extended to fluorophores adjacent to ANPs, as here we demonstrate with CdS/CdSe/CdS core/shell/shell quantum dots. ANPs with rationally designed energy transfer networks provide the means to transform conventional linear emitters into a highly nonlinear ones, expanding the use of photon avalanching in biological, chemical, and photonic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Zero-day Attack Detection in Digital Substations Using In-Context Learning

In this paper, we address the critical challenge of detecting zero-day attacks in digital substations that employ the IEC-61850 communication protocol to ensure the security and reliability of modern power systems. While many heuristic and machine learning (ML)-based methods have been proposed for attack detection in IEC-61850 digital substations, generalization to unknown or zero-day attacks remains a challenge. We propose an approach that leverages the in-context learning ability of transformer architecture, which enables the model to learn from a few examples of a new task without explicit retraining. Our experiments on the IEC-61850 dataset demonstrate that the proposed method achieves more than 87% detection accuracy on zero-day attacks while the existing baselines fail. We believe this work has the potential to enhance the security of digital substations by enabling the effective detection of zero-day attacks.

LIu, Chen-Ching [Virginia Tech] (ORCID:00000002894↗
DOE OSTI2023

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on Aims III Scenarios

Exposure to outdoor air pollution is the largest environmental risk factor for death and disease worldwide, associated with millions of cases of excess deaths (mortality) each year. Although there are many pollutants in the air that affect our health, the most important class of pollutants is fine particulate matter, PM 2.5 , which are airborne particles of diameter ≤2.5 micrometers (µm). These particles are small enough to deposit deep in the respiratory system where they can then enter the bloodstream, traveling and causing damage to other bodily systems. Exposure to outdoor (ambient) PM 2.5 has been found to be the most important environmental risk factor for mortality in Southeast Asia, associated with 130,000 - 320,000 excess deaths in Association of Southeast Asian Nations (ASEAN) member countries in 2019. Southeast Asia, especially its mega-cities, but also other areas, has some of the worst air quality in the world. Almost all human activity emits air pollutants. Fine particulate matter is both directly emitted and formed in the atmosphere through chemical reactions, the latter of which requires modeling to predict. Power generation is one of the major sources of air pollutants that lead to elevated concentrations of fine particulate matter, including in Southeast Asia. Fossil fuel combustion for power generation, especially coal but also diesel, is the main source of air pollutant emissions from power generation. While natural gas burns cleaner than coal or diesel, in the quantities combusted for power generation in Southeast Asia, it is also a significant emitter. This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what's known as an emissions inventory for each scenario and year evaluated. We then use for the first time a new global, reduced-complexity air quality model to transform the changes in emissions to changes in air pollutant concentration of the deadliest air pollutant for human health, fine particulate matter (or PM 2.5 ). The air quality model, Global InMAP, then utilizes the location of human population in ASEAN countries to calculate exposure to PM 2.5 concentration changes and translates that to estimates of excess mortality attributable to the AIMS III scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Application of a Prize Mechanism to Address Data Utilization Challenges at Utilities

The electric industry sector is facing an “explosion” of data from a variety of sources. Electric sector stakeholders need to define how to capitalize on large datasets, both those they create and those from other sources (like data on weather, buildings, electric vehicles, etc.), to improve reliability and resilience and meet the changing system dynamics from renewable integration. For the electricity sector to fully utilize these vast new datasets, it must undergo a transformation in how it manages data quality, storage, and processing. The U.S. Department of Energy (DOE) Office of Electricity (OE) is committed to accelerating research, development, and demonstration of new technologies and tools within the electricity sector to advance reliability, resilience, and affordable operation of the power system. Through the prize mechanism, OE identified two widespread data-related challenges for utilities—load modeling and data analysis automation—and offered an opportunity for utilities and teams of software engineers to identify additional challenges faced by utilities. After completing one round of the American-Made Digitizing Utilities Prize, OE, the National Renewable Energy Laboratory (NREL) as the prize administrator, and Pacific Northwest National Laboratory (PNNL) as the domain experts have compiled the results and lessons learned to feed into the second round of the prize.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗