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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multi-modal tomographic imaging system for poolside characterization of nuclear test fuels: Design considerations and studies

Testing and qualification of advanced nuclear fuels involves an iterative process of prototyping, in-pile irradiation testing, and in-situ or ex-situ examination. Fuel restructuring and fission product migration during burnup are among the most important aspects of fuel evolution that affect several important performance characteristics such as heat removal, accident tolerance, and fission product retention. Pool-side non-destructive characterization techniques provide fuel developers with tools to understand fuel evolution at different points of burnup. A design for a compact, submersible, and multi-modal gamma-ray tomography system for imaging irradiated nuclear fuel is presented here. Detector selection, collimator geometry and fabrication, mechanical design, imaging protocol and acquisition speed are discussed. Modeling calculations show that sub-millimeter resolution can be achieved in both transmission computed tomography images as well as in emission computed tomography images in a matter of hours. Several design compromises and fabrication challenges are discussed which should be taken into consideration for future submersible gamma-ray tomography instruments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Modal dynamics of high-frequency transverse combustion instabilities

This paper investigates the modal dynamics of self-excited high frequency transverse instabilities in a multi-nozzle, swirl-stabilized can combustor. It utilizes results from multiple pressure sensors to decompose the disturbance into clockwise (CW) and counter-clockwise (CCW) waves, enabling a reconstruction of the pressure amplitude, phase, anti-nodal line location, and spin ratio. While these types of decompositions have been demonstrated on small scale combustors, particularly annular combustors, this is the first study to analyze these results for a high power, multi-nozzle can combustor. Its particular focus is in characterizing the system evolution in phase space and the nature of the system attractors under linearly unstable conditions; results are presented in spin ratio-phase difference space, so that limit cycle oscillations appear as fixed points. Results are shown for conditions where three different attractors dominate (standing, CW, and CCW) but are taken for very long time periods (~50,000 cycles) so that the system's interaction with these attractors can be observed. For the standing mode-dominated case, the phase portrait shows spiral trajectories converging to a single fixed point. For the spinning mode dominated cases, however, multiple fixed points and saddle points were observed, and the trajectories showed a more complicated structure. It was also shown that even though the CW mode is dominant, this mode intermittently switches to standing or CCW modes for short period. These results suggest that the strength of each attractor depends on test conditions and that random noise stochastically perturbs the system so that large regions of the phase space are explored. Lastly, one interesting observation is that the angular velocity of the anti-nodal line linearly varies with the spin ratio under standing-mode dominant conditions.

42 ENGINEERING↗
DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Comparison of three measurement modalities for 3D characterization of manufactured features and process-induced porosity in titanium alloy additively manufactured parts

Nondestructive characterization of internal features and defects within complex components is vital for many industrial applications, particularly with the advent of additive manufacturing (AM) technologies. However, community understanding of the limitations of nondestructive methods such as X-ray Computed Tomography (CT) can be limited in certain industrial sectors as these may be emergent applications. In this paper, we investigate the limits of X-ray CT measurements and compare extracted data with mechanical polishing serial sectioning (MPSS) and confocal laser scanning microscopy (CLSM). The test object is an additively manufactured titanium alloy disk that contains both process-induced porosity and machined features, including focused ion beam milled features designed to probe the resolution limits of X-ray CT. Results show that each of these characterization techniques has advantages and disadvantages. We compare data acquisition times, spatial resolution, geometric measurement accuracy and defect visualization fidelity across these modalities to establish a practical framework.

Additive manufacturing↗
DOE OSTI2017

Band-edge engineering for controlled multi-modal nanolasing in plasmonic superlattices

Single band-edge states can trap light and function as high-quality optical feedback for microscale lasers and nanolasers. However, access to more than a single band-edge mode for nanolasing has not been possible because of limited cavity designs. Here, we describe how plasmonic superlattices-finite-arrays of nanoparticles (patches) grouped into microscale arrays-can support multiple band-edge modes capable of multi-modal nanolasing at programmed emission wavelengths and with large mode spacings. Different lasing modes show distinct input-output light behaviour and decay dynamics that can be tailored by nanoparticle size. By modelling the superlattice nanolasers with a four-level gain system and a time-domain approach, we reveal that the accumulation of population inversion at plasmonic hot spots can be spatially modulated by the diffractive coupling order of the patches. Furthermore, we show that symmetry-broken superlattices can sustain switchable nanolasing between a single mode and multiple modes.

42 ENGINEERING↗
DOE OSTI2023

Geospatial mapping of distribution grid with machine learning and publicly-accessible multi-modal data

Abstract Detailed and location-aware distribution grid information is a prerequisite for various power system applications such as renewable energy integration, wildfire risk assessment, and infrastructure planning. However, a generalizable and scalable approach to obtain such information is still lacking. In this work, we develop a machine-learning-based framework to map both overhead and underground distribution grids using widely-available multi-modal data including street view images, road networks, and building maps. Benchmarked against the utility-owned distribution grid map in California, our framework achieves > 80% precision and recall on average in the geospatial mapping of grids. The framework developed with the California data can be transferred to Sub-Saharan Africa and maintain the same level of precision without fine-tuning, demonstrating its generalizability. Furthermore, our framework achieves a R 2 of 0.63 in measuring the fraction of underground power lines at the aggregate level for estimating grid exposure to wildfires. We offer the framework as an open tool for mapping and analyzing distribution grids solely based on publicly-accessible data to support the construction and maintenance of reliable and clean energy systems around the world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Highly stretchable polymer semiconductor thin films with multi-modal energy dissipation and high relative stretchability

Abstract Stretchable polymer semiconductors (PSCs) have seen great advancements alongside the development of soft electronics. But it remains a challenge to simultaneously achieve high charge carrier mobility and stretchability. Herein, we report the finding that stretchable PSC thin films (<100-nm-thick) with high stretchability tend to exhibit multi-modal energy dissipation mechanisms and have a large relative stretchability ( rS ) defined by the ratio of the entropic energy dissipation to the enthalpic energy dissipation under strain. They effectively recovered the original molecular ordering, as well as electrical performance, after strain was released. The highest rS value with a model polymer (P4) exhibited an average charge carrier mobility of 0.2 cm 2 V −1 s −1 under 100% biaxial strain, while PSCs with low rS values showed irreversible morphology changes and rapid degradation of electrical performance under strain. These results suggest rS can be used as a parameter to compare the reliability and reversibility of stretchable PSC thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Correlating activities and defects in (photo)electrocatalysts using in-situ multi-modal microscopic imaging

Photo(electro)catalysts use sunlight to drive chemical reactions such as water splitting. A major factor limiting photocatalyst development is physicochemical heterogeneity which leads to spatially dependent reactivity. To link structure and function in such systems, simultaneous probing of the electrochemical environment at microscopic length scales and a broad range of timescales (ns to s) is required. Here, we address this challenge by developing and applying in- situ (optical) microscopies to map and correlate local electrochemical activity, with hole lifetimes, oxygen vacancy concentrations and photoelectrode crystal structure. Using this multi-modal approach, we study prototypical hematite (α-Fe 2 O 3 ) photoelectrodes. We demonstrate that regions of α-Fe 2 O 3 , adjacent to microstructural cracks have a better photoelectrochemical response and reduced back electron recombination due to an optimal oxygen vacancy concentration, with the film thickness and extended light exposure also influencing local activity. Our work highlights the importance of microscopic mapping to understand activity, in even seemingly homogeneous photoelectrodes.

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

Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Multi-modal characterization of nitrate reduction nano-catalysts with periodic strain distribution

Strain engineering serves as a pivotal strategy to optimize catalytic activity in electrocatalysis. However, the catalyst sizes under industrial conditions are usually large and even beyond nanometer regime. The critical methodological limitations on strain imaging of such catalysts with both large field of view and high spatial resolution obscure the mechanistic understanding of strain-performance correlations. Here, we present an optimized four-dimensional scanning transmission electron microscopy (4D-STEM) method to acquire strain mapping of both bulk and surface across particles up to 500 nm with 0.6 nm spatial resolution and 0.55% precision. We observe the ripple-like periodic strain coupled with elemental fluctuations inside a perovskite-type hydroxide CuCoSn(OH) 6 and find it correlated to electrocatalytic nitrate reduction (NO 3 – RR) absorption energy to achieve the 92.6% Faradaic efficiency and long-term test over 1000 h at membrane electrode assembly (MEA) for ammonia electrosynthesis. This universal framework design offers a practical method that not only develops an advanced measurement combining multi-modal characterization techniques but also reveals the intrinsic structure-property constitutive law of industry-level catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields

The development of high-fidelity mechanical property prediction models for the design of polycrystalline materials relies on large volumes of microstructural feature data. Concurrently, at these same scales, the deformation fields that develop during mechanical loading can be highly heterogeneous. Spatially correlated measurements of 3D microstructure and the ensuing deformation fields at the micro-scale would provide highly valuable insight into the relationship between microstructure and macroscopic mechanical response. They would also provide direct validation for numerical simulations that can guide and speed up the design of new materials and microstructures. However, to date, such data have been rare. Here, a one-of-a-kind, multi-modal dataset is presented that combines recent state-of-the-art experimental developments in 3D tomography and high-resolution deformation field measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An organic electrochemical transistor for multi-modal sensing, memory and processing

By integrating sensing, memory and processing functionalities, biological nervous systems are energy and area efficient. Emulating such capabilities in artificial systems is, however, challenging and is limited by the device heterogeneity of sensing and processing cores. Here we report an organic electrochemical transistor capable of sensing, memory and processing. The device has a vertical traverse architecture and a crystalline–amorphous channel that can be selectively doped by ions to enable two reconfigurable modes: a volatile receptor and a non-volatile synapse. As a volatile receptor, the device is capable of multi-modal sensing and is responsive to stimuli such as ions and light. As a non-volatile synapse, it is capable of 10-bit analogue states, low switching stochasticity and good state retention. We also show that the homogeneous integration of the devices could provide functions such as conditioned reflexes and could be used for real-time cardiac disease diagnoses via reservoir computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Multi-modal, ultrasensitive, wide-range humidity sensing with Ti 3 C 2 film

Gravimetric, direct-current electrical, and electrical impedance sensing modes were used to measure response of high surface area 2D Ti 3 C 2 MXene film to water vapor pressures spanning 3 orders of magnitude (20 mTorr–20 Torr). The Ti 3 C 2 film exhibited reproducible reversible response in 0.1%–95% relative humidity (RH) range with a detection limit of <20 mTorr H 2 O partial pressure (<0.1% RH). DC electrical current-based sensing with 3 mV operating voltage and 0.8 pW power consumption was demonstrated. The highest normalized sensitivity was shown for gravimetric sensing modalities which scale with the overtone number, reaching highest sensitivity of about 12 Hz/% RH at the 9th crystal overtone (45 MHz oscillation).

36 MATERIALS SCIENCE↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗
DOE OSTI2012

Non-modal analysis of the diocotron instability: Plane geometry

The comprehensive investigation of the temporal evolution of the diocotron instability of the plane electron strip on the linear stage of its development is performed. By using the method of Kelvin of the shearing modes, the role of the initial perturbations of the electron density is elucidated, which is connected with the problem of the continuous spectrum. The linear non-modal evolution process detected by the solution of the initial value problem, leads toward convergence to the phase-locking configuration of the mutually growing normal modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Non-modal analysis of the diocotron instability: Cylindrical geometry

The temporal evolution of the linear diocotron instability of the cylindrical annular plasma column is investigated by employing the extension of the shearing modes methodology to the cylindrical geometry. It was obtained that the spatial time-dependent distortion of the electron density initial perturbations by shear flows leads to the non-modal evolution of the potential, which was referred to as the manifestation of the continuous spectrum. The evolution process leads toward the convergence to the phase-locking configuration of the mutually growing normal modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Continuous wavelet transform analysis and modal location analysis acoustic emission source location for nuclear piping crack growth monitoring

Source location is an important feature of acoustic emission (AE) damage monitoring in nuclear piping. The ability to accurately locate sources can assist in source characterisation and early warning of failure. This paper describe the development of a novelAE source location technique termed 'Wavelet Transform analysis and Modal Location (WTML)' based on Lamb wave theory and time-frequency analysis that can be used for global monitoring of plate like steel structures. Source location was performed on a steel pipe of 1500 mm long and 220 mm outer diameter with nominal thickness of 5 mm under a planar location test setup using H-N sources. The accuracy of the new technique was compared with other AE source location methods such as the time of arrival (TOA) techniqueand DeltaTlocation. Theresults of the study show that the WTML method produces more accurate location resultscompared with TOA and triple point filtering location methods. The accuracy of the WTML approach is comparable with the deltaT location method but requires no initial acoustic calibration of the structure.

42 ENGINEERING↗
DOE OSTI2014

Non-modal analysis of the diocotron instability for cylindrical geometry with conducting boundary

The temporal evolution of the linear diocotron instability of a cylindrical annular plasma column surrounded by a conducting boundary has been investigated by using the methodology of the cylindrical shearing modes. The linear solution of the initial and boundary-value problems is obtained which is valid for any time at which linear effects dominate. The solution reveals that the initial perturbations of the electron density pass through the stage of the non-modal evolution when the perturbation experiences spatio-temporal distortion pertinent to the considered geometry of the electron column. The result is confirmed by a two-dimensional cylindrical particle-in-cell simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗